CDH6 and HAGH protein levels in plasma associate with Alzheimer's disease in APOE ε4 carriers

Proximity extension assay-based proteomics studies in neurodegenerative disorders and multiple sclerosis

Neurodegenerative diseases impact the structure and operation of the nervous system, causing progressive and irreparable harm. Efforts for distinguishing neurodegenerative diseases in their early stages are continuing. Despite several biomarkers being identified, there is always search for more accurate and abundant ones. Additionally, it can be difficult to pinpoint the precise neurodegenerative disorder affecting a patient as the symptoms of these conditions frequently overlap. Numerous studies have shown that pathological changes occur years before clinical signs appear. Therefore, it is crucial to discover blood-based biomarkers for neurodegenerative diseases for easier and earlier diagnosis. Proximity extension assay is a unique proteomics method that uses antibodies linked to oligonucleotides for quantifying proteins with real-time PCR. Proximity extension assay can identify even low-quantity proteins using a small volume of specimens with increased sensitivity compared to conventional methods. In this article, we reviewed the employment of proximity extension assay technology to detect biomarkers or protein profiles for several neurodegenerative diseases.

Plasma levels of neurology-related proteins are associated with cognitive performance in an older population with overweight/obesity and metabolic syndrome

Cognitive impairment is present in a broad spectrum of medical conditions and in aging. Here, we aimed to identify plasma proteins related to cognitive function in a sample of older adults with overweight/obesity and metabolic syndrome. A total of 129 subjects (mean age 64.7 years; 36% females) were grouped according to low (l-GCF, N=65) or high (h-GCF, N=64) global cognitive function and matched according to education, sex, age, and body mass index. Cognitive performance was assessed using neuropsychological tests. Plasma levels of 92 neurology-related proteins were assessed using a proximity extension assay. An elastic net regression analysis was used to identify proteins more associated with cognitive performance. Additionally, the protein expression levels were compared between the two groups by means of a t-test with false discovery rate correction. Pearson correlations were used to assess associations between the protein levels and scores from the neurocognitive tests. Six proteins (alpha-2-MRAP, HAGH, Siglec-9, MDGA1, IL12, and EDA2R) were identified as potential contributors to cognitive performance, remaining significantly increased in l-GCF compared to h-GCF participants after correction for multiple testing. Negative correlations (r= -0.23 to -0.18, i.e., lower protein levels, higher cognitive function) were found between global cognitive function and Siglec-9, NMNAT1, HAGH, LXN, gal-8, alpha-2-MRAP, IL12, PDGF-R-alpha, NAAA, EDA2R, CLEC1B, and LAT. Mini-mental state examination z scores showed the strongest correlations with protein levels, specifically negative correlations with CLEC1b, LXN, LAT, PLXNB3, NMNAT1, gal-8, HAGH, NAAA, CTSS, EZR, KYNU, MANF (r=-0.38 to -0.26) and a positive correlation with ADAM23 (r= 0.26). In summary, we identified several plasma proteins that were significantly associated with cognitive performance in older adults with obesity and metabolic syndrome, although further research is needed to replicate the results in larger samples and to include a predictive perspective.

Blood-Based Proteomic Profiling Identifies Potential Biomarker Candidates and Pathogenic Pathways in Dementia

Dementia is a progressive and debilitating neurological disease that affects millions of people worldwide. Identifying the minimally invasive biomarkers associated with dementia that could provide insights into the disease pathogenesis, improve early diagnosis, and facilitate the development of effective treatments is pressing. Proteomic studies have emerged as a promising approach for identifying the protein biomarkers associated with dementia. This pilot study aimed to investigate the plasma proteome profile and identify a panel of various protein biomarkers for dementia. We used a high-throughput proximity extension immunoassay to quantify 1090 proteins in 122 participants (22 with dementia, 64 with mild cognitive impairment (MCI), and 36 controls with normal cognitive function). Limma-based differential expression analysis reported the dysregulation of 61 proteins in the plasma of those with dementia compared with controls, and machine learning algorithms identified 17 stable diagnostic biomarkers that differentiated individuals with AUC = 0.98 ± 0.02. There was also the dysregulation of 153 plasma proteins in individuals with dementia compared with those with MCI, and machine learning algorithms identified 8 biomarkers that classified dementia from MCI with an AUC of 0.87 ± 0.07. Moreover, multiple proteins selected in both diagnostic panels such as NEFL, IL17D, WNT9A, and PGF were negatively correlated with cognitive performance, with a correlation coefficient (r²) ≤ -0.47. Gene Ontology (GO) and pathway analysis of dementia-associated proteins implicated immune response, vascular injury, and extracellular matrix organization pathways in dementia pathogenesis. In conclusion, the combination of high-throughput proteomics and machine learning enabled us to identify a blood-based protein signature capable of potentially differentiating dementia from MCI and cognitively normal controls. Further research is required to validate these biomarkers and investigate the potential underlying mechanisms for the development of dementia.

Investigation of 91 proteins implicated in neurobiological processes identifies multiple candidate plasma biomarkers of stroke outcome

The inter-individual variation in stroke outcomes is large and protein studies could point to potential underlying biological mechanisms. We measured plasma levels of 91 neurobiological proteins in 209 cases included in the Sahlgrenska Academy Study on Ischemic Stroke using a Proximity Extension Assay, and blood was sampled in the acute phase and at 3-month and 7-year follow-ups. Levels were also determined once in 209 controls. Acute stroke severity and neurological outcome were evaluated by the National Institutes of Health Stroke Scale. In linear regression models corrected for age, sex, and sampling day, acute phase levels of 37 proteins were associated with acute stroke severity, and 47 with 3-month and/or 7-year outcome at false discovery rate < 0.05. Three-month levels of 8 proteins were associated with 7-year outcome, of which the associations for BCAN and Nr-CAM were independent also of acute stroke severity. Most proteins followed a trajectory with lower levels in the acute phase compared to the 3-month follow-up and the control sampling point. Conclusively, we identified multiple candidate plasma biomarkers of stroke severity and neurological outcome meriting further investigation. This study adds novel information, as most of the reported proteins have not been previously investigated in a stroke cohort.

ApoE in Alzheimer’s disease: pathophysiology and therapeutic strategies

Alzheimer’s disease (AD) is the most common cause of dementia worldwide, and its prevalence is rapidly increasing due to extended lifespans. Among the increasing number of genetic risk factors identified, the apolipoprotein E (APOE) gene remains the strongest and most prevalent, impacting more than half of all AD cases. While the ε4 allele of the APOE gene significantly increases AD risk, the ε2 allele is protective relative to the common ε3 allele. These gene alleles encode three apoE protein isoforms that differ at two amino acid positions. The primary physiological function of apoE is to mediate lipid transport in the brain and periphery; however, additional functions of apoE in diverse biological functions have been recognized. Pathogenically, apoE seeds amyloid-β (Aβ) plaques in the brain with apoE4 driving earlier and more abundant amyloids. ApoE isoforms also have differential effects on multiple Aβ-related or Aβ-independent pathways. The complexity of apoE biology and pathobiology presents challenges to designing effective apoE-targeted therapeutic strategies. This review examines the key pathobiological pathways of apoE and related targeting strategies with a specific focus on the latest technological advances and tools.

Investigation of Mitochondrial Related Variants in a Cerebral Small Vessel Disease Cohort

Monogenic forms of cerebral small vessel disease (CSVD) can be caused by both variants in nuclear DNA and mitochondrial DNA (mtDNA). Mitochondrial encephalopathy, lactic acidosis, and stroke-like episodes (MELAS) is known to have a phenotype similar to Cerebral Autosomal Dominant Arteriopathy with Sub-cortical Infarcts and Leukoencephalopathy (CADASIL), and can be caused by variants in the mitochondrial genome and in several nuclear-encoded mitochondrial protein (NEMP) genes. The aim of this study was to screen for variants in the mitochondrial genome and NEMP genes in a NOTCH3-negative CADASIL cohort, to identify a potential link between mitochondrial dysfunction and CSVD pathology. Whole exome sequencing was performed for 50 patients with CADASIL-like symptomology on the Ion Torrent system. Mitochondrial sequencing was performed using an in-house designed protocol with sequencing run on the Ion GeneStudio S5 Plus (S5 +). NEMP genes and mitochondrial sequencing data were examined for rare (MAF < 0.001), non-synonymous variants that were predicted to have a deleterious effect on the protein. We identified 29 candidate NEMP variants that had links to either MELAS-, encephalopathy-, or Alzheimer's disease-related phenotypes. Based on these changes, variants affecting POLG, MTO1, LONP1, NDUFAF6, NDUFB3, and TCIRG1 were thought to play a potential role in CSVD pathology in this cohort. Overall, the exploration of the mitochondrial genome identified a potential role for mitochondrial related proteins and mtDNA variants contributing to CSVD pathologies.

Cross-tissue analysis of blood and brain epigenome-wide association studies in Alzheimer's disease

To better understand DNA methylation in Alzheimer's disease (AD) from both mechanistic and biomarker perspectives, we performed an epigenome-wide meta-analysis of blood DNA methylation in two large independent blood-based studies in AD, the ADNI and AIBL studies, and identified 5 CpGs, mapped to the SPIDR, CDH6 genes, and intergenic regions, that are significantly associated with AD diagnosis. A cross-tissue analysis that combined these blood DNA methylation datasets with four brain methylation datasets prioritized 97 CpGs and 10 genomic regions that are significantly associated with both AD neuropathology and AD diagnosis. An out-of-sample validation using the AddNeuroMed dataset showed the best performing logistic regression model includes age, sex, immune cell type proportions, and methylation risk score based on prioritized CpGs in cross-tissue analysis (AUC = 0.696, 95% CI: 0.616 - 0.770, P-value = 2.78 × 10^-5). Our study offers new insights into epigenetics in AD and provides a valuable resource for future AD biomarker discovery.

Modelling the Human Blood-Brain Barrier in Huntington Disease

While blood–brain barrier (BBB) dysfunction has been described in neurological disorders, including Huntington’s disease (HD), it is not known if endothelial cells themselves are functionally compromised when promoting BBB dysfunction. Furthermore, the underlying mechanisms of BBB dysfunction remain elusive given the limitations with mouse models and post mortem tissue to identify primary deficits. We established models of BBB and undertook a transcriptome and functional analysis of human induced pluripotent stem cell (iPSC)-derived brain-like microvascular endothelial cells (iBMEC) from HD patients or unaffected controls. We demonstrated that HD-iBMECs have abnormalities in barrier properties, as well as in specific BBB functions such as receptor-mediated transcytosis.

Blood DNA methylation patterns in older adults with evolving dementia

Dementia and cognitive disorders are major aging-associated pathologies. The prevalence and severity of these conditions are influenced by both genetic and environmental factors. Reflecting this, epigenetic alterations have been associated with each of these processes, especially at the level of DNA methylation, and such changes may help explain the observed interindividual variability in the development of the 2 pathologies. However, the importance of epigenetic alterations in explaining their etiology is unclear because little is known about the timing of when they appear. Here, using Illumina MethylationEPIC arrays, we have longitudinally analyzed the peripheral blood methylomes of cognitively healthy older adults (>70 year), some of whom went on to develop dementia while others stayed healthy. We have characterized 34 individuals at the prediagnosis stage and at a 4-year follow-up in the postdiagnosis stage (total n = 68). Our results show multiple DNA methylation alterations linked to dementia status, particularly at the level of differentially methylated regions. These loci are associated with several dementia-related genes, including PON1, AP2A2, MAGI2, POT1, ITGAX, PACSIN1, SLC2A8, and EIF4E. We also provide validation of the previously reported epigenetic alteration of HOXB6 and PM20D1. Importantly, we show that most of these regions are already altered in the prediagnosis stage of individuals who go on to develop dementia. In conclusion, our observations suggest that dementia-associated epigenetic patterns that have specific biological features are already present before diagnosis, and thus may be important in the design of epigenetic biomarkers for disease detection based on peripheral tissues.

Harnessing the Potential of Multiomics Studies for Precision Medicine in Infectious Disease

The field of infectious diseases currently takes a reactive approach and treats infections as they present in patients. Although certain populations are known to be at greater risk of developing infection (eg, immunocompromised), we lack a systems approach to define the true risk of future infection for a patient. Guided by impressive gains in "omics" technologies, future strategies to infectious diseases should take a precision approach to infection through identification of patients at intermediate and high-risk of infection and deploy targeted preventative measures (ie, prophylaxis). The advances of high-throughput immune profiling by multiomics approaches (ie, transcriptomics, epigenomics, metabolomics, proteomics) hold the promise to identify patients at increased risk of infection and enable risk-stratifying approaches to be applied in the clinic. Integration of patient-specific data using machine learning improves the effectiveness of prediction, providing the necessary technologies needed to propel the field of infectious diseases medicine into the era of personalized medicine.

Blood biomarkers for dementia in Hispanic and non-Hispanic White adults

INTRODUCTION

The study evaluated if blood markers reflecting diverse biological pathways differentiate clinical diagnostic groups among Hispanic and non-Hispanic White adults.

METHODS

Within Hispanic (n = 1193) and non-Hispanic White (n = 650) participants, serum total tau (t-tau), neurofilament light (NfL), ubiquitin carboxyl-terminal hydrolase LI, glial fibrillary acidic protein (GFAP), soluble cluster of differentiation-14, and chitinase-3-like protein 1 (YKL-40) were quantified. Mixed-effects partial proportional odds ordinal logistic regression and linear mixed-effects models were used to evaluate the association of biomarkers with diagnostic group and cognition, adjusting for age, sex, ethnicity, apolipoprotein E ε4, education, and site.

RESULTS

T-tau, NfL, GFAP, and YKL-40 discriminated between diagnostic groups (receiver operating curve: 0.647-0.873). Higher t-tau (odds ratio [OR] = 1.671, 95% confidence interval [CI] = 1.457-1.917, P < .001), NfL (OR = 2.150, 95% CI = 1.819-2.542, P < .001), GFAP (OR = 2.283, 95% CI = 1.915-2.722, P < .001), and YKL-40 (OR = 1.288, 95% CI = 1.125-1.475, P < .001) were associated with increased likelihood of dementia relative to cognitively unimpaired and mild cognitive impairment groups. Higher NfL was associated with poorer global cognition (β = -0.455, standard error [SE] = 0.083, P < .001), semantic fluency (β = -0.410, SE = 0.133, P = .002), attention/processing speed (β = 2.880, SE = 0.801, P < .001), and executive function (β = 5.965, SE = 2.037, P = .003). Higher GFAP was associated with poorer global cognition (β = -0.345, SE = 0.092, P = .001), learning (β = -1.426, SE = 0.359, P < .001), and memory (β = -0.890, SE = 0.266, P < .001). Higher YKL-40 (β = -0.537, SE = 0.186, P = .004) was associated with lower memory scores. Interactions with ethnicity were observed for learning (NfL, GFAP, YKL-40), memory (NfL, GFAP), and semantic fluency (NfL; interaction terms P < .008), which were generally no longer significant in a demographically matched subset of Hispanic and non-Hispanic White participants.

DISCUSSION

Blood biomarkers of neuronal/axonal and glial injury differentiated between clinical diagnostic groups in a bi-ethnic cohort of Hispanic and non-Hispanic Whites. Our results add to the growing literature indicating that blood biomarkers may be viable tools for detecting neurodegenerative conditions and highlight the importance of validation in diverse cohorts.