Comparing fluid biomarkers of Alzheimer's disease between African American or Black African and white groups: A systematic review and meta-analysis

Maximizing Analytical Performance in Biomolecular Discovery with LC-MS: Focus on Psychiatric Disorders

In this review, we discuss the cutting-edge developments in mass spectrometry proteomics and metabolomics that have brought improvements for the identification of new disease-based biomarkers. A special focus is placed on psychiatric disorders, for example, schizophrenia, because they are considered to be not a single disease entity but rather a spectrum of disorders with many overlapping symptoms. This review includes descriptions of various types of commonly used mass spectrometry platforms for biomarker research, as well as complementary techniques to maximize data coverage, reduce sample heterogeneity, and work around potentially confounding factors. Finally, we summarize the different statistical methods that can be used for improving data quality to aid in reliability and interpretation of proteomics findings, as well as to enhance their translatability into clinical use and generalizability to new data sets.

The 2022 symposium on dementia and brain aging in low- and middle-income countries: Highlights on research, diagnosis, care, and impact

Two of every three persons living with dementia reside in low- and middle-income countries (LMICs). The projected increase in global dementia rates is expected to affect LMICs disproportionately. However, the majority of global dementia care costs occur in high-income countries (HICs), with dementia research predominantly focusing on HICs. This imbalance necessitates LMIC-focused research to ensure that characterization of dementia accurately reflects the involvement and specificities of diverse populations. Development of effective preventive, diagnostic, and therapeutic approaches for dementia in LMICs requires targeted, personalized, and harmonized efforts. Our article represents timely discussions at the 2022 Symposium on Dementia and Brain Aging in LMICs that identified the foremost opportunities to advance dementia research, differential diagnosis, use of neuropsychometric tools, awareness, and treatment options. We highlight key topics discussed at the meeting and provide future recommendations to foster a more equitable landscape for dementia prevention, diagnosis, care, policy, and management in LMICs. HIGHLIGHTS: Two-thirds of persons with dementia live in LMICs, yet research and costs are skewed toward HICs. LMICs expect dementia prevalence to more than double, accompanied by socioeconomic disparities. The 2022 Symposium on Dementia in LMICs addressed advances in research, diagnosis, prevention, and policy. The Nairobi Declaration urges global action to enhance dementia outcomes in LMICs.

Circulating Biomarkers for Alzheimer's Disease: Unlocking the Diagnostic Potential in Low- and Middle-Income Countries, Focusing on Africa

BACKGROUND

Alzheimer's disease (AD) is emerging as a significant public health challenge in Africa, with predictions indicating a tripling in incidence by 2050. The diagnosis of AD on the African continent is notably difficult, leading to late detection that severely limits treatment options and significantly impacts the quality of life for patients and their families.

SUMMARY

This review focuses on the potential of high-sensitivity specific blood biomarkers as promising tools for improving AD diagnosis and management globally, particularly in Africa. These advances are particularly pertinent in the continent, where access to medical and technical resources is often limited.

KEY MESSAGES

Identifying precise, sensitive, and specific blood biomarkers could contribute to the biological characterization and management of AD in Africa. Such advances promise to improve patient care and pave the way for new regional opportunities in pharmaceutical research and drug trials on the continent for AD.

Blood Markers in Relation to a History of Traumatic Brain Injury Across Stages of Cognitive Impairment in a Diverse Cohort

BACKGROUND

Traumatic brain injury (TBI) has been linked to multiple pathophysiological processes that could increase risk for Alzheimer's disease and related dementias (ADRD). However, the impact of prior TBI on blood biomarkers for ADRD remains unknown.

OBJECTIVE

Using cross-sectional data, we assessed whether a history of TBI influences serum biomarkers in a diverse cohort (approximately 50% Hispanic) with normal cognition, mild cognitive impairment, or dementia.

METHODS

Levels of glial fibrillary acidic protein (GFAP), neurofilament light (NFL), total tau (T-tau), and ubiquitin carboxy-terminal hydrolase-L1 (UCHL1) were measured for participants across the cognitive spectrum. Participants were categorized based on presence and absence of a history of TBI with loss of consciousness, and study samples were derived through case-control matching. Multivariable general linear models compared concentrations of biomarkers in relation to a history of TBI and smoothing splines modelled biomarkers non-linearly in the cognitively impaired groups as a function of time since symptom onset.

RESULTS

Each biomarker was higher across stages of cognitive impairment, characterized by clinical diagnosis and Mini-Mental State Examination performance, but these associations were not influenced by a history of TBI. However, modelling biomarkers in relation to duration of cognitive symptoms for ADRD showed differences by history of TBI, with only GFAP and UCHL1 being elevated.

CONCLUSIONS

Serum GFAP, NFL, T-tau, and UCHL1 were higher across stages of cognitive impairment in this diverse clinical cohort, regardless of TBI history, though longitudinal investigation of the timing, order, and trajectory of the biomarkers in relation to prior TBI is warranted.

Racial differences in the effect of APOE-ε4 genotypes on trail making test B in Alzheimer's disease: A longitudinal study

OBJECTIVES

The trail making test part B (TMT-B) evaluates executive functions, memory, and sensorimotor functions. No previous study was found to examine the longitudinal effect of APOE-ε4 genotypes on the TMT-B scores in Alzheimer's disease (AD) across racial groups.

METHODS

This study used the data from Alzheimer's Disease Neuroimaging Initiative (ADNI): 382 participants with AD, 503 with cognitive normal (CN), 1293 with mild cognitive impairment (MCI) at baseline and follow-up of four years. The multivariable linear mixed model was used to investigate the effect of APOE-ε4 genotypes on changes in TMT-B scores.

RESULTS

Compared with Whites, African Americans (AA) and Hispanics had higher TMT-B scores (poor cognitive function). Furthermore, Whites subjects with 1 or 2 APOE-ε4 alleles had significantly higher TMT-B scores compared with individuals without APOE-ε4 allele at baseline and four follow-up visits; however, no differences in TMT-B were found between APOE-ε4 alleles in the Hispanic and AA groups. No APOE-ε4 by visit interactions was found for 3 racial groups. Stratified by AD diagnosis, the APOE-ε4 allele was associated with TMT-B scores only in the MCI group, while there were significant interactions for visit by education, APOE-ε4 allele, and the Mini Mental State Examination (MMSE) score in the MCI group. In addition, TMT-B was significantly correlated with the MMSE, AD Assessment Scale-cognitive subscale 13 (ADAS13), tTau, pTau, Aβ42, and hippocampus.

CONCLUSIONS

APOE-ɛ4 allele is associated with TMT-B scores in Whites subjects, but not in the Hispanic and AA groups. APOE-ε4 showed interaction with visit in the MCI group.

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

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

Understanding ethnic diversity in open dementia neuroimaging data sets

Ethnic differences in dementia are increasingly recognized in epidemiological measures and diagnostic biomarkers. Nonetheless, ethnic diversity remains limited in many study populations. Here, we provide insights into ethnic diversity in open-access neuroimaging dementia data sets. Data sets comprising dementia populations with available data on ethnicity were included. Statistical analyses of sample and effect sizes were based on the Cochrane Handbook. Nineteen databases were included, with 17 studies of healthy groups or a combination of diagnostic groups if breakdown was unavailable and 12 of mild cognitive impairment and dementia groups. Combining all studies on dementia patients, the largest ethnic group was Caucasian (20 547 participants), with the next most common being Afro-Caribbean (1958), followed by Asian (1211). The smallest effect size detectable within the Caucasian group was 0.03, compared to Afro-Caribbean (0.1) and Asian (0.13). Our findings quantify the lack of ethnic diversity in openly available dementia data sets. More representative data would facilitate the development and validation of biomarkers relevant across ethnicities.

A global view of the genetic basis of Alzheimer disease

The risk of Alzheimer disease (AD) increases with age, family history and informative genetic variants. Sadly, there is still no cure or means of prevention. As in other complex diseases, uncovering genetic causes of AD could identify underlying pathological mechanisms and lead to potential treatments. Rare, autosomal dominant forms of AD occur in middle age as a result of highly penetrant genetic mutations, but the most common form of AD occurs later in life. Large-scale, genome-wide analyses indicate that 70 or more genes or loci contribute to AD. One of the major factors limiting progress is that most genetic data have been obtained from non-Hispanic white individuals in Europe and North America, preventing the development of personalized approaches to AD in individuals of other ethnicities. Fortunately, emerging genetic data from other regions - including Africa, Asia, India and South America - are now providing information on the disease from a broader range of ethnicities. Here, we summarize the current knowledge on AD genetics in populations across the world. We predominantly focus on replicated genetic discoveries but also include studies in ethnic groups where replication might not be feasible. We attempt to identify gaps that need to be addressed to achieve a complete picture of the genetic and molecular factors that drive AD in individuals across the globe.

Factors influencing the participation of Black and White Americans in Alzheimer's disease biomarker research

Introduction

Alzheimer's disease (AD) is a public health priority. AD biomarkers may vary based on race, but the recruitment of diverse participants has been challenging.

Methods

Three groups of Black and White participants with and without prior research advocacy or participation were interviewed individually or in focus groups to better understand perspectives related to AD biomarker research participation. A rapid qualitative data analytic approach was used to analyze the data.

Results

Identified barriers to AD biomarker research participation included hesitancy due to fear, distrust of research and researchers, lack of relevant knowledge, and lack of research test results disclosure. Drivers for engagement in biomarker research procedures included knowledge about research, AD, and related clinical procedures, perceived benefits of participation, and outreach from trusted sources.

Discussion

Participants' comments related to the need for diversity in research and desire for results disclosure suggest opportunities to engage Black individuals.

Highlights

Black Americans experience more salient barriers to Alzheimer's disease (AD) biomarker research participation.Concerns about research diversity influence research participation decisions.Research test disclosure may affect research participation and retention.

The complex relationship between depression and progression to incident cognitive impairment across race and ethnicity

INTRODUCTION

We examined baseline differences in depression and antidepressant use among cognitively normal older adults in five ethnoracial groups and assessed whether depression predicted a faster progression to incident cognitive impairment across groups.

METHODS

Data from the National Alzheimer's Coordinating Center (n = 8168) were used to examine differences between non-Hispanic Whites (nHW), African Americans (AA), Hispanics, Asians, and American Indian and Alaskan Natives in cross-sectional and longitudinal models.

RESULTS

AA had a lower risk of depression compared to nHW at baseline. No statistical interactions were noted between ethnoracial groups and depression. However, depression independently predicted a faster progression to incident cognitive impairment. Hispanics and Asian participants had a higher hazard for progression compared to nHW.

DISCUSSION

Previously established risk factors between depression and dementia were not found among AA and nHW participants. The relationship between depression and ethnoracial groups is complex and suggests differential effects on progression from cognitive normality to impairment.

Association of Plasma and Cerebrospinal Fluid Alzheimer Disease Biomarkers With Race and the Role of Genetic Ancestry, Vascular Comorbidities, and Neighborhood Factors

IMPORTANCE

Differences in cerebrospinal fluid (CSF) tau Alzheimer dementia (AD) biomarkers by self-identified race have been observed in prior studies. More recently, plasma biomarkers have been gaining recognition, but whether they exhibit similar differences is unclear. Furthermore, the underlying explanation for these differences in AD biomarkers is still unexplored.

OBJECTIVES

To investigate differences in plasma biomarkers by race and genetic ancestry and explore potential underlying explanations for these differences.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used participant data from the Brain, Stress, Hypertension, and Aging Research Program (B-SHARP), an observational study conducted in the greater Atlanta metropolitan area. Participants were enrolled from March 1, 2016, to January 1, 2020.

MAIN OUTCOMES AND MEASURES

Main outcomes were plasma and CSF amyloid-β (Aβ) 42, Aβ40, phosphorylated tau181 (p-tau181), and neurofilament light. General linear models were used for key comparisons.

EXPOSURES

Main independent variables were self-identified race and genetic ancestry. Additional variables were cardiovascular factors, APOE4, educational attainment, Area Deprivation Index, and C-reactive protein (reflecting systemic inflammation state).

RESULTS

This analysis included 617 participants (mean [SD] age, 66 [7.9] years; 300 [49%] African American and 317 [51%] White; 429 [70%] with mild cognitive impairment). On the basis of self-reported race, plasma levels of Aβ42 (adjusted mean difference, -1.20 pg/mL; 95% CI, -2.33 to -0.07 pg/mL), Aβ40 (adjusted mean difference, -37.78 pg/mL; 95% CI, -60.16 to -15.39 pg/mL), p-tau181 (adjusted mean difference, -4.66 pg/mL; 95% CI, -7.05 to -1.90 pg/mL), and neurofilament light (adjusted mean difference, -1.58; 95% CI, -2.83 to -0.19 pg/mL) were consistently lower in African American individuals after adjusting for demographic characteristics, educational attainment, cognition, APOE4, and cardiovascular factors. A similar pattern was observed in the CSF biomarkers except for Aβ42 and Aβ40. Although unadjusted analyses revealed an association between these biomarkers and African ancestry, these associations were not significant after adjusting for the same covariates. Differences by self-reported race were not explained by varied cardiovascular risk factors, C-reactive protein, educational attainment, or Area Deprivation Index.

CONCLUSIONS AND RELEVANCE

In this cross-sectional study of plasma biomarkers by race and genetic ancestry, the results indicated that plasma p-tau181, Aβ40, and NFL were lower in African American individuals based on self-reported race but not genetic ancestry. These differences were not explained by cardiovascular risks or clinical stage differences. These racial differences should be considered in clinical interpretations and clinical trial screenings to avoid an additional increase in underrepresentation of African American individuals in AD trials.

Characterizing Plasma Biomarkers of Alzheimer's in a Diverse Community-Based Cohort: A Cross-Sectional Study of the HAB-HD Cohort

Background

Due to their low cost, less invasive nature, and ready availability, plasma biomarkers of Alzheimer's disease have been proposed as one-time screening tools for clinical trials and research. The impact of ethnoracial factors on these biomarkers has received little attention. The current cross-sectional study investigated the levels of Aβ₄₀, Aβ₄₂, total tau (t tau), and neurofilament light (NfL) across diagnoses for each of the three major ethnoracial groups in the United States in a community-based cohort of older adults.

Methods

A total of 1,862 participants (852 Mexican Americans (MAs); 775 non-Hispanic Whites (NHWs), and 235 African Americans (AAs)) drawn from The Health & Aging Brain Study—Health Disparities (HABS-HD) study were included. Diagnoses were assigned using an algorithm (decision tree) verified by consensus review. Plasma samples were assayed using Simoa technology. Levels of each biomarker were compared for the three ethnoracial groups across cognitive diagnoses using ANOVA covarying sex and age.

Results

Significant differences were found across the groups at each level of cognitive impairment. Cognitively unimpaired (CU) AA had significantly lower levels of each of the biomarkers than cognitively unimpaired MA or NHW and NHW had higher levels of Aβ₄₀, and NfL than the other two groups. MA had higher t tau than AA or NHW. Mild cognitive impairment (MCI) group NHW had the highest levels on all the biomarkers and AA had the lowest. NHW and MA have higher levels of Aβ₄₀, Aβ₄₂, and t tau there was no difference between the groups for Aβ₄₂. NHW had significantly higher levels of Aβ₄₀, t tau, and NfL than AA. AA had a higher Aβ₄₂/Aβ₄₀ ratio than either NHW or MA for CU MCI.

Conclusions

The use of plasma biomarkers of cognitive decline is promising given their advantages over other biomarkers such as CSF and imaging but as the current research shows, ethnoracial differences must be considered to enhance accuracy and utility. Developing ethnoracial-specific cut points and establishing normative ranges by assay platform for each of the biomarkers are needed. Longitudinal research to assess changes in biomarkers during a cognitive decline is ongoing.

Blood phospho-tau in Alzheimer disease: analysis, interpretation, and clinical utility

Well-authenticated biomarkers can provide critical insights into the biological basis of Alzheimer disease (AD) to enable timely and accurate diagnosis, estimate future burden and support therapeutic trials. Current cerebrospinal fluid and molecular neuroimaging biomarkers fulfil these criteria but lack the scalability and simplicity necessary for widespread application. Blood biomarkers of adequate effectiveness have the potential to act as first-line diagnostic and prognostic tools, and offer the possibility of extensive population screening and use that is not limited to specialized centres. Accelerated progress in our understanding of the biochemistry of brain-derived tau protein and advances in ultrasensitive technologies have enabled the development of AD-specific phosphorylated tau (p-tau) biomarkers in blood. In this Review we discuss how new information on the molecular processing of brain p-tau and secretion of specific fragments into biofluids is informing blood biomarker development, enabling the evaluation of preanalytical factors that affect quantification, and informing harmonized protocols for blood handling. We also review the performance of blood p-tau biomarkers in the context of AD and discuss their potential contexts of use for clinical and research purposes. Finally, we highlight outstanding ethical, clinical and analytical challenges, and outline the steps that need to be taken to standardize inter-laboratory and inter-assay measurements.

Blood-Based Biomarkers for Alzheimer's Disease Diagnosis and Progression: An Overview

Alzheimer's Disease (AD) is a progressive neurodegenerative disease characterized by amyloid-β (Aβ) plaque deposition and neurofibrillary tangle accumulation in the brain. Although several studies have been conducted to unravel the complex and interconnected pathophysiology of AD, clinical trial failure rates have been high, and no disease-modifying therapies are presently available. Fluid biomarker discovery for AD is a rapidly expanding field of research aimed at anticipating disease diagnosis and following disease progression over time. Currently, Aβ1-42, phosphorylated tau, and total tau levels in the cerebrospinal fluid are the best-studied fluid biomarkers for AD, but the need for novel, cheap, less-invasive, easily detectable, and more-accessible markers has recently led to the search for new blood-based molecules. However, despite considerable research activity, a comprehensive and up-to-date overview of the main blood-based biomarker candidates is still lacking. In this narrative review, we discuss the role of proteins, lipids, metabolites, oxidative-stress-related molecules, and cytokines as possible disease biomarkers. Furthermore, we highlight the potential of the emerging miRNAs and long non-coding RNAs (lncRNAs) as diagnostic tools, and we briefly present the role of vitamins and gut-microbiome-related molecules as novel candidates for AD detection and monitoring, thus offering new insights into the diagnosis and progression of this devastating disease.

Exposing the Brain Proteomic Signatures of Alzheimer's Disease in Diverse Racial Groups: Leveraging Multiple Data Sets and Machine Learning

Recent studies have highlighted that the proteome can be used to identify potential biomarker candidates for Alzheimer's disease (AD) in diverse cohorts. Furthermore, the racial and ethnic background of participants is an important factor to consider to ensure the effectiveness of potential biomarkers for representative populations. A promising approach to survey potential biomarker candidates for diagnosing AD in diverse cohorts is the application of machine learning to proteomics data sets. Herein, we leveraged six existing bottom-up proteomics data sets, which included non-Hispanic White, African American/Black, and Hispanic participants, to study protein changes in AD and cognitively unimpaired participants. Machine learning models were applied to these data sets and resulted in the identification of amyloid-β precursor protein (APP) and heat shock protein β-1 (HSPB1) as two proteins that have high ability to distinguish AD; however, each protein's performance varied based upon the racial and ethnic background of the participants. HSPB1 particularly was helpful for generating high areas under the curve (AUCs) for African American/Black participants. Overall, HSPB1 improved the performance of the machine learning models when combined with APP and/or participant age and is a potential candidate that should be further explored in AD biomarker discovery efforts.

Blood biomarkers for cognitive decline and clinical progression in a Mexican American cohort

Introduction: The clinical translation of biofluid markers for dementia requires validation in diverse cohorts. The study goal was to evaluate if blood biomarkers reflecting diverse pathophysiological processes predict disease progression in Mexican American adults. Methods: Mexican American adults (n = 745), 50 years of age and older, completed annual assessments over a mean of 4 years. Serum collected at baseline was assayed for total tau, neurofilament light (NFL), ubiquitin carboxyl-terminal hydrolase LI, glial fibrillary acidic protein (GFAP), soluble cluster of differentiation 14 (sCD14), and chitinase-3-like protein 1 (YKL-40). Results: Higher GFAP and NFL were associated with global cognitive decline. Only GFAP was associated with increased incident dementia risk (hazard ratio: 1.611 (95% confidence interval: 1.204-2.155)) and inclusion of additional biomarkers did not improve model fit. Discussion: Among a panel of six blood biomarkers previously associated with neurodegenerative disease, only GFAP predicted incident dementia in our cohort. The findings suggest that blood GFAP levels may aid dementia-risk prediction among Mexican American adults.

Culture, Ethnicity, and Level of Education in Alzheimer's Disease

Alzheimer's disease (AD) is the most frequent cause of dementia, where the abnormal accumulation of beta-amyloid (Aβ) and tau lead to neurodegeneration as well as loss of cognitive, behavioral, and functional abilities. The present review analyzes AD from a cross-cultural neuropsychological perspective, looking at differences in culture-associated variables, neuropsychological test performance and biomarkers across ethnic and racial groups. Studies have found significant effects of culture, preferred language, country of origin, race, and ethnicity on cognitive test performance, although the definition of those grouping terms varies across studies. Together, with the substantial underrepresentation of minority groups in research, the inconsistent classification might conduce to an inaccuratte diagnosis that often results from biases in testing procedures that favor the group to which test developers belong. These biases persist even after adjusting for variables related to disadvantageous societal conditions, such as low level of education, unfavorable socioeconomic status, health care access, or psychological stressors. All too frequently, educational level is confounded with culture. Minorities often have lower educational attainment and lower quality of education, causing differences in test results that are then attributed to culture. Higher levels of education are also associated with increased cognitive reserve, a protective factor against cognitive decline in the presence of neurodegeneration. Biomarker research suggests there might be significant differences in specific biomarker profiles for each ethnicity/race in need of accurate cultural definitions to adequately predict risk and disease progression across ethnic/racial groups. Overall, this review highlights the need for diversity in all domains of AD research that lack inclusion and the collection of relevant information from these groups.