Blood-based biomarkers for Down syndrome and Alzheimer's disease: A systematic review

Prognostic value of plasma Aβ1-40 for Alzheimer's disease

OBJECTIVE

To investigate the clinical significance of plasma p-amyloid 1-40 (Aβ1-40) in patients with Alzheimer's disease (AD).

METHODS

In this retrospective study, the clinical data of 305 patients, with or without Alzheimer's disease (AD), who were treated at the Affiliated Hospital of Youjiang Medical University for Nationalities and the People's Hospital of Baise between January 2018 and December 2021 were analyzed. Patients were divided into two groups: an AD group (n=147) and a non-AD group (without AD, n=158 cases). Blood test indices, including serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), creatinine (CRE), high-sensitivity C-reactive protein (hsCRP), and plasma β-amyloid 1-40 were collected and compared between the two groups.

RESULTS

The plasma β-amyloid 1-40 in the AD group was (3.71±3.45) mol/L, which was significantly higher than (2.8±1.35) mmol/L in the non-AD group (P<0.05). Similarly, hsCRP expression was significantly higher in the AD group than that in the non-AD group (P<0.05). There were no significant differences in AST, ALT, UA, T-tau, NFL or Cr levels between the two groups (all P>0.05). Moreover, univariate regression analysis showed that plasma β-amyloid 1-40 and hsCRP were significantly correlated with AD. Multiple regression analysis demonstrated that plasma p-amyloid 1-40 (P<0.0001) and hsCRP (P=0.002) were independent predictors of AD.

CONCLUSION

Plasma p-amyloid 1-40 and hsCRP are closely related to AD, and may serve as important clinical predictors of AD.

Cognitive and functional performance and plasma biomarkers of early Alzheimer's disease in Down syndrome

INTRODUCTION

People with Down syndrome (DS) have a 75% to 90% lifetime risk of Alzheimer's disease (AD). AD pathology begins a decade or more prior to onset of clinical AD dementia in people with DS. It is not clear if plasma biomarkers of AD pathology are correlated with early cognitive and functional impairments in DS, and if these biomarkers could be used to track the early stages of AD in DS or to inform inclusion criteria for clinical AD treatment trials.

METHODS

This large cross-sectional cohort study investigated the associations between plasma biomarkers of amyloid beta (Aβ)42/40, total tau, and neurofilament light chain (NfL) and cognitive (episodic memory, visual-motor integration, and visuospatial abilities) and functional (adaptive behavior) impairments in 260 adults with DS without dementia (aged 25-81 years).

RESULTS

In general linear models lower plasma Aβ42/40 was related to lower visuospatial ability, higher total tau was related to lower episodic memory, and higher NfL was related to lower visuospatial ability and lower episodic memory.

DISCUSSION

Plasma biomarkers may have utility in tracking AD pathology associated with early stages of cognitive decline in adults with DS, although associations were modest.

Highlights

Plasma Alzheimer's disease (AD) biomarkers correlate with cognition prior to dementia in Down syndrome.Lower plasma amyloid beta 42/40 was related to lower visuospatial abilities.Higher plasma total tau and neurofilament light chain were associated with lower cognitive performance.Plasma biomarkers show potential for tracking early stages of AD symptomology.

Low TGF-β1 plasma levels are associated with cognitive decline in Down syndrome

Almost all individuals with Down's syndrome (DS) show the characteristic neuropathological features of Alzheimer's disease (AD) by the age of 40, yet not every individual with DS experiences symptoms of AD later in life. Similar to neurotypical developing subjects, AD in people with DS lasts for a long preclinical phase in which biomarkers follow a predictable order of changes. Hence, a prolonged asymptomatic period precedes the onset of dementia, underscoring the importance of identifying new biomarkers for the early detection and monitoring of cognitive decline in individuals with DS. Blood-based biomarkers may offer an alternative non-invasive strategy for the detection of peripheral biological alterations paralleling nervous system pathology in an early phase of the AD continuum. In the last few years, a strong neurobiological link has been demonstrated between the deficit of transforming growth factor-β1 (TGF-β1) levels, an anti-inflammatory cytokine endowed with neuroprotective activity, and early pro-inflammatory processes in the AD brain. In this clinical prospective observational study, we found significant lower plasma TGF-β1 concentrations at the first neuropsychological evaluation (baseline = T0) both in young adult DS individuals (19-35 years) and older DS subjects without AD (35-60 years) compared to age- and sex-matched healthy controls. Interestingly, we found that the lower TGF-β1 plasma concentrations at T0 were strongly correlated with the following cognitive decline at 12 months. In addition, in young individuals with DS, we found, for the first time, a negative correlation between low TGF-β1 concentrations and high TNF-α plasma concentrations, a pro-inflammatory cytokine that is known to be associated with cognitive impairment in DS individuals with AD. Finally, adopting an ex vivo approach, we found that TGF-β1 concentrations were reduced in parallel both in the plasma and in the peripheral blood mononuclear cells (PBMCs) of DS subjects, and interestingly, therapeutic concentrations of fluoxetine (FLX) applied to cultured PBMCs (1 µM for 24 h) were able to rescue TGF-β1 concentrations in the culture media from DS PBMCs, suggesting that FLX, a selective serotonin reuptake inhibitor (SSRI) endowed with neuroprotective activity, might rescue TGF-β1 concentrations in DS subjects at higher risk to develop cognitive decline.

Comorbidities Incorporated to Improve Prediction for Prevalent Mild Cognitive Impairment and Alzheimer's Disease in the HABS-HD Study

BACKGROUND

Blood biomarkers have the potential to transform Alzheimer's disease (AD) diagnosis and monitoring, yet their integration with common medical comorbidities remains insufficiently explored.

OBJECTIVE

This study aims to enhance blood biomarkers' sensitivity, specificity, and predictive performance by incorporating comorbidities. We assess this integration's efficacy in diagnostic classification using machine learning, hypothesizing that it can identify a confident set of predictive features.

METHODS

We analyzed data from 1,705 participants in the Health and Aging Brain Study-Health Disparities, including 116 AD patients, 261 with mild cognitive impairment, and 1,328 cognitively normal controls. Blood samples were assayed using electrochemiluminescence and single molecule array technology, alongside comorbidity data gathered through clinical interviews and medical records. We visually explored blood biomarker and comorbidity characteristics, developed a Feature Importance and SVM-based Leave-One-Out Recursive Feature Elimination (FI-SVM-RFE-LOO) method to optimize feature selection, and compared four models: Biomarker Only, Comorbidity Only, Biomarker and Comorbidity, and Feature-Selected Biomarker and Comorbidity.

RESULTS

The combination model incorporating 17 blood biomarkers and 12 comorbidity variables outperformed single-modal models, with NPV12 at 92.78%, AUC at 67.59%, and Sensitivity at 65.70%. Feature selection led to 22 chosen features, resulting in the highest performance, with NPV12 at 93.76%, AUC at 69.22%, and Sensitivity at 70.69%. Additionally, interpretative machine learning highlighted factors contributing to improved prediction performance.

CONCLUSIONS

In conclusion, combining feature-selected biomarkers and comorbidities enhances prediction performance, while feature selection optimizes their integration. These findings hold promise for understanding AD pathophysiology and advancing preventive treatments.

Ultrasensitive detection of blood biomarkers of Alzheimer's and Parkinson's diseases: a systematic review

Purpose: Neurodegenerative disorders are a global health burden with costly and invasive diagnoses relying on brain imaging technology or CSF-based biomarkers. Therefore, considerable efforts to identify blood-biomarkers for Alzheimer's (AD) and Parkinson's diseases (PD) are ongoing. Objectives: This review evaluates the blood biomarkers for AD and PD for their diagnostic value. Methods: This study systematically reviewed articles published between July 1984 and February 2021. Among 1266 papers, we selected 42 studies for a systematic review and 23 studies for meta-analysis. Results & conclusion: Our analysis highlights P-tau181, T-tau and Nfl as promising blood biomarkers for AD diagnosis. Nfl levels were consistently raised in 16 AD and three PD cohorts. P-tau181 and T-tau were also significantly increased in 12 and eight AD cohorts, respectively.

Aging with Down Syndrome-Where Are We Now and Where Are We Going?

Down syndrome (DS) is a form of accelerated aging, and people with DS are highly prone to aging-related conditions that include vascular and neurological disorders. Due to the overexpression of several genes on Chromosome 21, for example genes encoding amyloid precursor protein (APP), superoxide dismutase (SOD), and some of the interferon receptors, those with DS exhibit significant accumulation of amyloid, phospho-tau, oxidative stress, neuronal loss, and neuroinflammation in the brain as they age. In this review, we will summarize the major strides in this research field that have been made in the last few decades, as well as discuss where we are now, and which research areas are considered essential for the field in the future. We examine the scientific history of DS bridging these milestones in research to current efforts in the field. We extrapolate on comorbidities associated with this phenotype and highlight clinical networks in the USA and Europe pursuing clinical research, concluding with funding efforts and recent recommendations to the NIH regarding DS research.

Innate Immune System Activation and Neuroinflammation in Down Syndrome and Neurodegeneration: Therapeutic Targets or Partners?

Innate immune system activation and inflammation are associated with and may contribute to clinical outcomes in people with Down syndrome (DS), neurodegenerative diseases such as Alzheimer's disease (AD), and normal aging. In addition to serving as potential diagnostic biomarkers, innate immune system activation and inflammation may play a contributing or causal role in these conditions, leading to the hypothesis that effective therapies should seek to dampen their effects. However, recent intervention studies with the innate immune system activator granulocyte-macrophage colony-stimulating factor (GM-CSF) in animal models of DS, AD, and normal aging, and in an AD clinical trial suggest that activating the innate immune system and inflammation may instead be therapeutic. We consider evidence that DS, AD, and normal aging are accompanied by innate immune system activation and inflammation and discuss whether and when during the disease process it may be therapeutically beneficial to suppress or promote such activation.

Nerve Growth Factor Compromise in Down Syndrome

The basal forebrain cholinergic system relies on trophic support by nerve growth factor (NGF) to maintain its phenotype and function. In Alzheimer's disease (AD), basal forebrain cholinergic neurons (BFCNs) undergo progressive atrophy, suggesting a deficit in NGF trophic support. Within the central nervous system, NGF maturation and degradation are tightly regulated by an activity-dependent metabolic cascade. Here, we present a brief overview of the characteristics of Alzheimer's pathology in Down syndrome (DS) with an emphasis on this NGF metabolic pathway's disruption during the evolving Alzheimer's pathology. Such NGF dysmetabolism is well-established in Alzheimer's brains with advanced pathology and has been observed in mild cognitive impairment (MCI) and non-demented individuals with elevated brain amyloid levels. As individuals with DS inexorably develop AD, we then review findings that support the existence of a similar NGF dysmetabolism in DS coinciding with atrophy of the basal forebrain cholinergic system. Lastly, we discuss the potential of NGF-related biomarkers as indicators of an evolving Alzheimer's pathology in DS.

Recursive Support Vector Machine Biomarker Selection for Alzheimer's Disease

BACKGROUND

There is a need for more reliable diagnostic tools for the early detection of Alzheimer's disease (AD). This can be a challenge due to a number of factors and logistics making machine learning a viable option.

OBJECTIVE

In this paper, we present on a Support Vector Machine Leave-One-Out Recursive Feature Elimination and Cross Validation (SVM-RFE-LOO) algorithm for use in the early detection of AD and show how the SVM-RFE-LOO method can be used for both classification and prediction of AD.

METHODS

Data were analyzed on n = 300 participants (n = 150 AD; n = 150 cognitively normal controls). Serum samples were assayed via a multi-plex biomarker assay platform using electrochemiluminescence (ECL).

RESULTS

The SVM-RFE-LOO method reduced the number of features in the model from 21 to 16 biomarkers and achieved an area under the curve (AUC) of 0.980 with a sensitivity of 94.0% and a specificity of 93.3%. When the classification and prediction performance of SVM-RFE-LOO was compared to that of SVM and SVM-RFE, we found similar performance across the models; however, the SVM-RFE-LOO method utilized fewer markers.

CONCLUSION

We found that 1) the SVM-RFE-LOO is suitable for analyzing noisy high-throughput proteomic data, 2) it outperforms SVM-RFE in the robustness to noise and in the ability to recover informative features, and 3) it can improve the prediction performance. Our recursive feature elimination model can serve as a general model for biomarker discovery in other diseases.

Blood-Based Biomarkers for Predictive Diagnosis of Cognitive Impairment in a Pakistani Population

Numerous studies have identified an association between age-related cognitive impairment (CI) and oxidative damage, accumulation of metals, amyloid levels, tau, and deranged lipid profile. There is a concerted effort to establish the reliability of these blood-based biomarkers for predictive diagnosis of CI and its progression. We assessed the serum levels of high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, triglycerides, total cholesterol, selected metals (Cu, Al, Zn, Pb, Mn, Cad), and total-tau and amyloid beta-42 protein in mild (n = 71), moderate (n = 86) and severe (n = 25) cognitively impaired patients and compared them with age-matched healthy controls (n = 90) from Pakistan. We found that a decrease in HDL cholesterol (correlation coefficient r = 0.467) and amyloid beta-42 (r = 0.451) were associated with increased severity of CI. On the other hand, an increase in cholesterol ratio (r = -0.562), LDL cholesterol (r = -0.428), triglycerides, and total-tau (r = -0.443) were associated with increased severity of CI. Increases in cholesterol ratio showed the strongest association and correlated with increases in tau concentration (r = 0.368), and increased triglycerides were associated with decreased amyloid beta-42 (r = -0.345). Increased Cu levels showed the strongest association with tau increase and increased Zn and Pb levels showed the strongest association with reduced amyloid beta-42 levels. Receiver Operating Characteristic (ROC) showed the cutoff values of blood metals (Al, Pb, Cu, Cad, Zn, and Mn), total-tau, and amyloid beta-42 with sensitivity and specificity. Our data show for the first time that blood lipids, metals (particularly Cu, Zn, Pb, and Al), serum amyloid-beta-42/tau proteins modulate each other's levels and can be collectively used as a predictive marker for CI.

Down syndrome and dementia: advances in the field

PURPOSE OF REVIEW

People with Down syndrome represent the world's largest population with a genetic risk for Alzheimer's disease. This review will provide a short summary of what is known and will include recent findings from the field.

RECENT FINDINGS

There has been an increasing focus on biomarker research in this population, with a number of studies presenting findings on promising new markers - Neurofilament Light (NfL) appears to be one such promising marker that has emerged. Imaging studies have increased our knowledge on the progression of Alzheimer's disease in this population.

SUMMARY

The inclusion of people with Down syndrome in dementia research is vital from a scientific and an equity perspective. Recent advances in the field can have further impact with multisite, cross country collaborative efforts. For this to happen, instruments need to be validated across language and cultures.

Metabolic correlates of prevalent mild cognitive impairment and Alzheimer's disease in adults with Down syndrome

INTRODUCTION

Disruption of metabolic function is a recognized feature of late onset Alzheimer's disease (LOAD). We sought to determine whether similar metabolic pathways are implicated in adults with Down syndrome (DS) who have increased risk for Alzheimer's disease (AD).

METHODS

We examined peripheral blood from 292 participants with DS who completed baseline assessments in the Alzheimer's Biomarkers Consortium-Down Syndrome (ABC-DS) using untargeted mass spectrometry (MS). Our sample included 38 individuals who met consensus criteria for AD (DS-AD), 43 who met criteria for mild cognitive impairment (DS-MCI), and 211 who were cognitively unaffected and stable (CS).

RESULTS

We measured relative abundance of 8,805 features using MS and 180 putative metabolites were differentially expressed (DE) among the groups at false discovery rate-corrected q< 0.05. From the DE features, a nine-feature classifier model classified the CS and DS-AD groups with receiver operating characteristic area under the curve (ROC AUC) of 0.86 and a two-feature model classified the DS-MCI and DS-AD groups with ROC AUC of 0.88. Metabolite set enrichment analysis across the three groups suggested alterations in fatty acid and carbohydrate metabolism.

DISCUSSION

Our results reveal metabolic alterations in DS-AD that are similar to those seen in LOAD. The pattern of results in this cross-sectional DS cohort suggests a dynamic time course of metabolic dysregulation which evolves with clinical progression from non-demented, to MCI, to AD. Metabolomic markers may be useful for staging progression of DS-AD.

Dynamics of plasma biomarkers in Down syndrome: the relative levels of Aβ42 decrease with age, whereas NT1 tau and NfL increase

Background

Down syndrome (DS) is the most common genetic cause of Alzheimer’s disease (AD), but diagnosis of AD in DS is challenging due to the intellectual disability which accompanies DS. When disease-modifying agents for AD are approved, reliable biomarkers will be required to identify when and how long people with DS should undergo treatment. Three cardinal neuropathological features characterize AD, and AD in DS—Aβ amyloid plaques, tau neurofibrillary tangles, and neuronal loss. Here, we quantified plasma biomarkers of all 3 neuropathological features in a large cohort of people with DS aged from 3 months to 68 years. Our primary aims were (1) to assess changes in the selected plasma biomarkers in DS across age, and (2) to compare biomarkers measured in DS plasma versus age- and sex-matched controls.

Methods

Using ultra-sensitive single molecule array (Simoa) assays, we measured 3 analytes (Aβ42, NfL, and tau) in plasmas of 100 individuals with DS and 100 age- and sex-matched controls. Tau was measured using an assay (NT1) which detects forms of tau containing at least residues 6–198. The stability of the 3 analytes was established using plasma from ten healthy volunteers collected at 6 intervals over a 5-day period.

Results

High Aβ42 and NT1 tau and low NfL were observed in infants. Across all ages, Aβ42 levels were higher in DS than controls. Levels of Aβ42 decreased with age in both DS and controls, but this decrease was greater in DS than controls and became prominent in the third decade of life. NT1 tau fell in adolescents and young adults, but increased in older individuals with DS. NfL levels were low in infants, children, adolescents, and young adults, but thereafter increased in DS compared to controls.

Conclusions

High levels of Aβ42 and tau in both young controls and DS suggest these proteins are produced by normal physiological processes, whereas the changes seen in later life are consistent with emergence of pathological alterations. These plasma biomarker results are in good agreement with prior neuropathology studies and indicate that the third and fourth decades (i.e., 20 to 40 years of age) of life are pivotal periods during which AD processes manifest in DS. Application of the assays used here to longitudinal studies of individuals with DS aged 20 to 50 years of age should further validate the use of these biomarkers, and in time may allow identification and monitoring of people with DS best suited for treatment with AD therapies.

Predictive Value of Routine Peripheral Blood Biomarkers in Alzheimer's Disease

Background

Biomarker screening is of major significance for the early diagnosis and prevention of Alzheimer’s disease (AD). Routine peripheral blood parameters are easy to collect and detect, making them ideal potential biomarkers. Thus, we aimed to evaluate the parameters from routine blood as potential biomarkers for AD.

Methods

We enrolled 56 AD patients, 57 mild cognitive impairment (MCI) patients, and 59 healthy elderly controls. Receiver operating characteristic (ROC) curves were used to assess the diagnostic values of routine blood biomarkers in patients with cognitive impairment.

Results

There were significant differences in eight parameters between the groups. Logistic regression revealed that the neutrophil% (odds ratio (OR) 1.34, 95% confidence interval [CI] 1.03–1.75, p = 0.031) and neutrophil-to-lymphocyte ratio (NLR; OR 6.27, 95% CI 3.98–9.82, p = 0.003) differentiated AD patients and controls (areas under the curve [AUCs], 0.728 and 0.721) and that the NLR (OR 1.93, 95% CI 1.07–3.47, p = 0.028) and mean platelet volume (OR 1.67, 95% CI 1.04–2.70, p = 0.036) differentiated MCI patients and controls (AUCs, 0.60 and 0.638). There were no effective diagnostic biomarkers to distinguish AD from MCI.

Conclusion

Some routine blood biomarkers may correlate with cognitive impairment. Analysis of these biomarkers, such as the NLR, may be useful for the identification of patients with cognitive impairment.