Molecular markers of amnestic mild cognitive impairment among Mexican Americans

Genome-Wide Methylation of Mild Cognitive Impairment in Mexican Americans Highlights Genes Involved in Synaptic Transport, Alzheimer's Disease-Precursor Phenotypes, and Metabolic Morbidities

The Mexican American population is among the fastest growing aging population and has a younger onset of cognitive decline. This group is also heavily burdened with metabolic conditions such as hypertension, diabetes, and obesity. Unfortunately, limited research has been conducted in this group. Understanding methylation alterations, which are influenced by both genetic and lifestyle factors, is key to identifying and addressing the root cause for mild cognitive impairment, a clinical precursor for dementia. We conducted an epigenome-wide association study on a community-based Mexican American population using the Illumina EPIC array. Following rigorous quality control measures, we identified 10 CpG sites to be differentially methylated between normal controls and individuals with mild cognitive impairment annotated to PKIB, KLHL29, SEPT9, OR2C3, CPLX3, BCL2L2-PABPN1, and CCNY. We found four regions to be differentially methylated in TMEM232, SLC17A8, ALOX12, and SEPT8. Functional gene-set analysis identified four gene-sets, RIN3, SPEG, CTSG, and UBE2L3, as significant. The gene ontology and pathway analyses point to neuronal cell death, metabolic dysfunction, and inflammatory processes. We found 1,450 processes to be enriched using empirical Bayes gene-set enrichment. In conclusion, the functional overlap of differentially methylated genes associated with cognitive impairment in Mexican Americans implies cross-talk between metabolically-instigated systemic inflammation and disruption of synaptic vesicular transport.

Proteomic profiles of incident mild cognitive impairment and Alzheimer's disease among adults with Down syndrome

INTRODUCTION

We sought to determine if proteomic profiles could predict risk for incident mild cognitive impairment (MCI) and Alzheimer's disease (AD) among adults with Down syndrome (DS).

METHODS

In a cohort of 398 adults with DS, a total of n = 186 participants were determined to be non-demented and without MCI or AD at baseline and throughout follow-up; n = 103 had incident MCI and n = 81 had incident AD. Proteomics were conducted on banked plasma samples from a previously generated algorithm.

RESULTS

The proteomic profile was highly accurate in predicting incident MCI (area under the curve [AUC] = 0.92) and incident AD (AUC = 0.88). For MCI risk, the support vector machine (SVM)-based high/low cut-point yielded an adjusted hazard ratio (HR) = 6.46 (P < .001). For AD risk, the SVM-based high/low cut-point score yielded an adjusted HR = 8.4 (P < .001).

DISCUSSION

The current results provide support for our blood-based proteomic profile for predicting risk for MCI and AD among adults with DS.

Combining Select Blood-Based Biomarkers with Neuropsychological Assessment to Detect Mild Cognitive Impairment among Mexican Americans

BACKGROUND

Recent work has supported use of blood-based biomarkers in detection of amnestic mild cognitive impairment (MCI). Inclusion of neuropsychological measures has shown promise in enhancing utility of biomarkers to detect disease.

OBJECTIVE

The present study sought to develop cognitive-biomarker profiles for detection of MCI.

METHODS

Data were analyzed on 463 participants (normal control n = 378; MCI n = 85) from HABLE. Random forest analyses determined proteomic profile of MCI. Separate linear regression analyses determined variance accounted for by select biomarkers per neuropsychological measure. When neuropsychological measure with the least shared variance was identified, it was then combined with select biomarkers to create a biomarker-cognitive profile.

RESULTS

The biomarker-cognitive profile was 90% accurate in detecting MCI. Among amnestic MCI cases, the detection accuracy of the biomarker-cognitive profile was 92% and increased to 94% with demographic variables.

CONCLUSION

The biomarker-cognitive profile for MCI was highly accurate in its detection with use of only five biomarkers.

Proteomic profiles of prevalent mild cognitive impairment and Alzheimer's disease among adults with Down syndrome

INTRODUCTION

We sought to determine if a proteomic profile approach developed to detect Alzheimer's disease (AD) in the general population would apply to adults with Down syndrome (DS).

METHODS

Plasma samples were obtained from 398 members of a community-based cohort of adults with DS. A total of n = 186 participants were determined to be non-demented and without mild cognitive impairment (MCI) at baseline and throughout follow-up; n = 50 had prevalent MCI; n = 42 had prevalent AD.

RESULTS

The proteomic profile yielded an area under the curve (AUC) of 0.92, sensitivity (SN) = 0.80, and specificity (SP) = 0.98 detecting prevalent MCI. For detecting prevalent AD, the proteomic profile yielded an AUC of 0.89, SN = 0.81, and SP = 0.97. The overall profile closely resembled our previously published profile of AD in the general population.

DISCUSSION

These data provide evidence of the applicability of our blood-based algorithm for detecting MCI/AD among adults with DS.

The impact of comorbid depression-diabetes on proteomic outcomes among community-dwelling Mexican Americans with mild cognitive impairment

BACKGROUND

Mexican Americans suffer from a disproportionate burden of modifiable risk factors, which may contribute to the health disparities in mild cognitive impairment (MCI) and Alzheimer's disease (AD).

OBJECTIVE

The purpose of this study was to elucidate the impact of comorbid depression and diabetes on proteomic outcomes among community-dwelling Mexican American adults and elders.

METHODS

Data from participants enrolled in the Health and Aging Brain among Latino Elders study was utilized. Participants were 50 or older and identified as Mexican American (N = 514). Cognition was assessed via neuropsychological test battery and diagnoses of MCI and AD adjudicated by consensus review. The sample was stratified into four groups: Depression only, Neither depression nor diabetes, Diabetes only, and Comorbid depression and diabetes. Proteomic profiles were created via support vector machine analyses.

RESULTS

In Mexican Americans, the proteomic profile of MCI may change based upon the presence of diabetes. The profile has a strong inflammatory component and diabetes increases metabolic markers in the profile.

CONCLUSION

Medical comorbidities may impact the proteomics of MCI and AD, which lend support for a precision medicine approach to treating this disease.

A proteomic signature for dementia with Lewy bodies

INTRODUCTION

We sought to determine if a proteomic profile approach developed to detect Alzheimer's disease would distinguish patients with Lewy body disease from normal controls, and if it would distinguish dementia with Lewy bodies (DLB) from Parkinson's disease (PD).

METHODS

Stored plasma samples were obtained from 145 patients (DLB n = 57, PD without dementia n = 32, normal controls n = 56) enrolled from patients seen in the Behavioral Neurology or Movement Disorders clinics at the Mayo Clinic, Florida. Proteomic assays were conducted and analyzed as per our previously published protocols.

RESULTS

In the first step, the proteomic profile distinguished the DLB-PD group from controls with a diagnostic accuracy of 0.97, sensitivity of 0.91, and specificity of 0.86. In the second step, the proteomic profile distinguished the DLB from PD groups with a diagnostic accuracy of 0.92, sensitivity of 0.94, and specificity of 0.88.

DISCUSSION

These data provide evidence of the potential utility of a multitiered blood-based proteomic screening method for detecting DLB and distinguishing DLB from PD.

Potential two-step proteomic signature for Parkinson's disease: Pilot analysis in the Harvard Biomarkers Study

Introduction

We sought to determine if our previously validated proteomic profile for detecting Alzheimer's disease would detect Parkinson's disease (PD) and distinguish PD from other neurodegenerative diseases.

Methods

Plasma samples were assayed from 150 patients of the Harvard Biomarkers Study (PD, n = 50; other neurodegenerative diseases, n = 50; healthy controls, n = 50) using electrochemiluminescence and Simoa platforms.

Results

The first step proteomic profile distinguished neurodegenerative diseases from controls with a diagnostic accuracy of 0.94. The second step profile distinguished PD cases from other neurodegenerative diseases with a diagnostic accuracy of 0.98. The proteomic profile differed in step 1 versus step 2, suggesting that a multistep proteomic profile algorithm to detecting and distinguishing between neurodegenerative diseases may be optimal.

Discussion

These data provide evidence of the potential use of a multitiered blood-based proteomic screening method for detecting individuals with neurodegenerative disease and then distinguishing PD from other neurodegenerative diseases.

Characteristics of Cognitively Normal Mexican-Americans with Cognitive Complaints

BACKGROUND

Subjective cognitive complaints in cognitively normal adults have been linked to later cognitive decline and dementia. Research on the characteristics of this group has been conducted on a variety of clinical and community-based populations. The current study focuses on the rapidly expanding population of Mexican-American elders.

OBJECTIVE

The objective of the study is the determination of characteristics of cognitively normal Mexican-Americans with cognitive complaints.

METHODS

Data on 319 cognitively normal participants in a large-scale community-based study of elderly Mexican-Americans (HABLE) were analyzed comparing those with cognitive complaints with those without on clinical characteristics, affective status, neuropsychological functioning, and proteomic markers.

RESULTS

Those expressing concern about cognitive decline scored lower on the MMSE, were more likely to have significantly more affective symptoms, higher levels of diabetic markers, poorer performance on attention and executive functioning, and a different pattern of inflammatory markers.

CONCLUSION

Although longitudinal research is needed to determine the impact of these differences on later cognition, possible targets for early intervention with Mexican-Americans were identified.

Omics-based Biomarkers for the Early Alzheimer Disease Diagnosis and Reliable Therapeutic Targets Development

BACKGROUND

Alzheimer's disease (AD), the most common cause of dementia in adulthood, has great medical, social, and economic impact worldwide. Available treatments result in symptomatic relief, and most of them are indicated from the early stages of the disease. Therefore, there is an increasing body of research developing accurate and early diagnoses, as well as diseasemodifying therapies.

OBJECTIVE

Advancing the knowledge of AD physiopathological mechanisms, improving early diagnosis and developing effective treatments from omics-based biomarkers.

METHODS

Studies using omics technologies to detect early AD, were reviewed with a particular focus on the metabolites/lipids, micro-RNAs and proteins, which are identified as potential biomarkers in non-invasive samples.

RESULTS

This review summarizes recent research on metabolomics/lipidomics, epigenomics and proteomics, applied to early AD detection. Main research lines are the study of metabolites from pathways, such as lipid, amino acid and neurotransmitter metabolisms, cholesterol biosynthesis, and Krebs and urea cycles. In addition, some microRNAs and proteins (microglobulins, interleukins), related to a common network with amyloid precursor protein and tau, have been also identified as potential biomarkers. Nevertheless, the reproducibility of results among studies is not good enough and a standard methodological approach is needed in order to obtain accurate information.

CONCLUSION

The assessment of metabolomic/lipidomic, epigenomic and proteomic changes associated with AD to identify early biomarkers in non-invasive samples from well-defined participants groups will potentially allow the advancement in the early diagnosis and improvement of therapeutic interventions.

Factor structure and measurement invariance of a neuropsychological test battery designed for assessment of cognitive functioning in older Mexican Americans

INTRODUCTION

The present study sought to investigate the measurement invariance of commonly used neuropsychological tests in an ethnically (Hispanic vs. non-Hispanic) and linguistically (Spanish vs. English) diverse sample.

METHODS

Participants were 736 middle-aged and older adults (M Age = 62.1, SD = 9.1) assessed at baseline. Measurement invariance testing was performed using multiple-group confirmatory factor analysis.

RESULTS

A five-factor model (memory, attention/executive functioning/processing speed, language, visuospatial, and motor) fit the data well (CFI = 0.979, RMSEA = 0.047) and the composite reliability of the factors ranged from .76 (visuospatial) to .97 (motor). The five-factor model was found to possess strict measurement invariance for ethnicity and language without a decrement in fit compared to a strong (scalar) invariance model (ΔCFI = .000, ΔRMSEA = .002).

DISCUSSION

These results indicate that a five-factor model is suitable for estimating cognitive functioning in Mexican Americans and non-Hispanic whites without bias by ethnicity or language.

Cerebrospinal fluid and blood biomarkers for neurodegenerative dementias: An update of the Consensus of the Task Force on Biological Markers in Psychiatry of the World Federation of Societies of Biological Psychiatry

In the 12 years since the publication of the first Consensus Paper of the WFSBP on biomarkers of neurodegenerative dementias, enormous advancement has taken place in the field, and the Task Force takes now the opportunity to extend and update the original paper. New concepts of Alzheimer's disease (AD) and the conceptual interactions between AD and dementia due to AD were developed, resulting in two sets for diagnostic/research criteria. Procedures for pre-analytical sample handling, biobanking, analyses and post-analytical interpretation of the results were intensively studied and optimised. A global quality control project was introduced to evaluate and monitor the inter-centre variability in measurements with the goal of harmonisation of results. Contexts of use and how to approach candidate biomarkers in biological specimens other than cerebrospinal fluid (CSF), e.g. blood, were precisely defined. Important development was achieved in neuroimaging techniques, including studies comparing amyloid-β positron emission tomography results to fluid-based modalities. Similarly, development in research laboratory technologies, such as ultra-sensitive methods, raises our hopes to further improve analytical and diagnostic accuracy of classic and novel candidate biomarkers. Synergistically, advancement in clinical trials of anti-dementia therapies energises and motivates the efforts to find and optimise the most reliable early diagnostic modalities. Finally, the first studies were published addressing the potential of cost-effectiveness of the biomarkers-based diagnosis of neurodegenerative disorders.

Texas Mexican American adult normative studies: Normative data for commonly used clinical neuropsychological measures for English- and Spanish-speakers

This study aimed to provide normative references for Mexican Americans on neuropsychological measures of cognitive functioning. Data were analyzed from a total of 797 Mexican-Americans recruited across three Texas-based studies with approximately one-half of the participants tested in Spanish. Normative tables include: MMSE, AMNART, WMS-III (Logical Memory I, II; Visual Reproduction I, II; Digit Span), CERAD, RAVLT, Exit25, CLOX 1 & 2, Trail Making Test- A&B, BNT, COWA, and Animal Naming. The norms were stratified by education then age. Normative references were generated for Texas-based Mexican Americans and data may be limited to the population sampled.

Texas Mexican American adult normative studies: Normative data for the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS)

The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) is an assessment of neuropsychological functioning commonly used in clinical and research settings. To our knowledge, normative data for the RBANS is not available for Hispanic, Mexican Americans, which the current study sought to establish. Data from 136 Hispanic, Mexican Americans from Project FRONTIER were analyzed. Approximately half of the sample was administered testing in Spanish. Normative tables were created for English and Spanish speaking Mexican Americans. Generated RBANS normative references are provided for unadjusted raw scores as well as output adjusted by education level.

Association of anti-inflammatory cytokine IL10 polymorphisms with motoric cognitive risk syndrome in an Ashkenazi Jewish population

Motoric cognitive risk (MCR) syndrome is a newly described predementia syndrome characterized by the presence of cognitive complaints and slow gait, which is associated with increased risk of conversion to dementia. The underlying biological mechanisms for MCR have not yet been established. Neuroinflammation mediated through cytokines plays a pivotal role in the pathogenesis of dementia. Hence, our objective was to prospectively examine whether variations in cytokine genes (CRP, IFNG, IL1A, IL1B, IL4, IL6, IL10, IL18, TNF, and IL12A) play a role in MCR incidence in 530 community-dwelling Ashkenazi Jewish adults aged 65 years and older without MCR or dementia at baseline enrolled in the LonGenity study. Over a median follow-up of 2.99 years, 70 participants developed MCR. Single nucleotide polymorphisms (SNPs) in the transcriptional regulatory regions of cytokine IL10, rs1800896 (hazard ratio adjusted for age, gender, and education, aHR: 1.667; 95% CI: 1.198-2.321) and rs3024498 (aHR: 1.926; 95% CI: 1.315-2.822), were associated with incident MCR. Functional analysis using in silico approaches indicated associated SNP rs3024498 "C" allele being the local expression quantitative trait locus. Associated alleles of both the SNPs, rs1800896 and rs3024498, were implicated with overexpression of IL10 gene. None of the variants in the neuroinflammatory pathway studied were associated with incident mild cognitive impairment syndrome. These observations support a role for the IL10 gene in dementia pathogenesis by increasing risk of developing MCR in older adults.

The effectiveness and unique contribution of neuropsychological tests and the δ latent phenotype in the differential diagnosis of dementia in the uniform data set

OBJECTIVE

Two main approaches to the interpretation of cognitive test performance have been utilized for the characterization of disease: evaluating shared variance across tests, as with measures of severity, and evaluating the unique variance across tests, as with pattern and error analysis. Both methods provide necessary information, but the unique contributions of each are rarely considered. This study compares the 2 approaches on their ability to differentially diagnose with accuracy, while controlling for the influence of other relevant demographic and risk variables.

METHOD

Archival data requested from the NACC provided clinical diagnostic groups that were paired to 1 another through a genetic matching procedure. For each diagnostic pairing, 2 separate logistic regression models predicting clinical diagnosis were performed and compared on their predictive ability. The shared variance approach was represented through the latent phenotype δ, which served as the lone predictor in 1 set of models. The unique variance approach was represented through raw score values for the 12 neuropsychological test variables comprising δ, which served as the set of predictors in the second group of models.

RESULTS

Examining the unique patterns of neuropsychological test performance across a battery of tests was the superior method of differentiating between competing diagnoses, and it accounted for 16-30% of the variance in diagnostic decision making.

CONCLUSION

Implications for clinical practice are discussed, including test selection and interpretation. (PsycINFO Database Record