Prerpints.org logo
Preprint
Article

The Relationship of Plasma Biomarkers of Alzheimer’s Disease and Neuropsychological Test Performance in Older Adults with Unimpaired Cognition: The Impact of Ethnicity

Altmetrics

Downloads

160

Views

74

Comments

0

Submitted:

01 April 2024

Posted:

02 April 2024

You are already at the latest version

Alerts
Abstract
There has been significant increase of studies investigating plasma biomarkers of Alzheimer’s and their relationship to cognitive functioning. The impact of ethnicity on this relationship has not been extensively studied. The current research investigated the relationship between the plasma biomarkers of total tau, Aβ40, Aβ42 and NfL and neuropsychological test performance in a bi-ethnic sample of cognitively unimpaired, older community dwelling adults. The 1326 cognitively unimpaired participants drawn from The Health & Aging Brain Study – Health Disparities (HABS-HD) study included 765 Mexican American participants and 860 non-Hispanic White participants with complete plasma biomarkers and neuropsychological testing. Plasma samples were assayed using Simoa technology. Significant differences in concentrations were found for all of the plasma biomarkers. NHWs had significantly higher levels of each of the biomarkers with a lower Aβ42/ Aβ40. With none of the biomarkers related to performance on any of the neuropsychological tests. For MAs, Aβ40 was the only biomarker that was significantly related to neuropsychological test performance. Aβ40 levels were negatively related to performance on Trails A, Trails B and Digit Symbol Substitution. Results suggest that the relationship of these biomarkers to cognitive functioning is impacted by ethnicity and may be domain specific.
Keywords: 
Subject: Medicine and Pharmacology  -   Neuroscience and Neurology

1. Introduction

The AT(N) framework[1] provides a biologically based approach to understanding the nature of Alzheimer’s and its diagnosis and progression. Initially the AT(N) framework emphasized imaging and CSF biomarkers as reflecting the nature of the pathological processes underlying AD. Subsequently there has been an increased interest in blood-based biomarkers of these processes due to the cost-effective, minimally invasive and highly scalable nature of these biofluids[2,3,4,5,6]. The advent of single molecule array technology has made the reliable assessment of plasma biomarkers of amyloid (Aβ40 & Aβ42), tau (total tau) and neurodegeneration (NfL) possible.
High levels of baseline Aβ42 has been shown to predictive of cognitive decline in cognitively unimpaired[7] and higher levels of Aβ42 and total tau were predictive of cognitive decline in healthy older adults. [8]. Studies of the relationship of Aβ40 and cognitive decline have generally failed to show a strong relationship although the ratio of Aβ42 to Aβ40 (Aβ42/ Aβ40) has been related to cognitive decline[9] and conversion from MCI to dementia[10]. In studies of cognitively unimpaired individuals, the ratio has been shown to significantly predict brain amyloidosis in in a multinational study[11] and to predict cognitive changes in non-demented study participants[12]. Lower plasma Aβ42/ Aβ40 has been associated with cognitive decline over time in a community-based cohort[14]. Lower plasma Aβ42/ Aβ40 has also been found to predict cognitive decline in healthy individuals with subjective cognitive complaints[13] and is associated with a steeper rate of decline on test scores of attention, memory and executive functions in cognitively normal elderly[4].
Total tau has been associated with increased declines in neuropsychological performance on measures of attention, memory and visuospatial and the risk for developing MCI[15]. Pase et al.[16] found total tau was related to measures of memory, attention and executive functioning and increased risk for dementia in the Framingham Dementia study.
Neurofilament Light (NfL), a marker of neurodegeneration that has been related to a number of neurological diseases, has been shown to be related to memory, language and executive functions in non-dementia elders and MCI[17]. Marks et al.[18] in a longitudinal study of cognitive decline found baseline plasma NfL to be associated with decline in global cognition and the combination of elevated NfL and elevated plasma total tau was associated with declines in global cognition and memory.
Even with the significant increase in research investigating the utility of plasma biomarkers there are a number of gaps in our understanding of the factors influencing the level of these biomarkers and their relationship to measures of cognitive impairment. One of the gaps in understanding is the impact of ethnicity on plasma biomarkers. Little of the research on plasma biomarkers has focused on diverse United States populations in community settings. Among those studies that have been conducted on plasma biomarkers of AD and ethnicity, the vast majority have been biethnic/bi-racial studies comparing Hispanics or African Americans (AA) to Non-Hispanic Whites (NHW) across diagnostic groups or research on one of the ethnoracial groups comparing diagnostic groups. A cross-sectional study of elderly Mexican Americans (MA) found NfL having a negative impact on performance on neurocognitive testing for both cognitively unimpaired and MCI[19]. Gonzales et al.[20] found that total tau and NfL discriminated between diagnostic groups for both Hispanics (predominately Mexican Americans) and NHWs. The same study found no difference in NfL levels in a demographically matched subset of the two ethnic groups. O’Bryant et al.[21] in a bi-ethnic study of Mexican Americans (MAs) and NHWs found NfL significantly associated with diagnostic groups for both ethnic groups. A study of a diverse Florida sample found no effect for Hispanic ethnicity (predominately Caribbean background) on NfL levels[22].
A study of plasma biomarkers in African Americans including tau and Aβ42 comparing cognitively normal controls with Alzheimer’s patients found that tau was significantly higher in the AD group and Aβ42 level was not associated with Alzheimer’s[23]. A WHICAP community-based study of plasma biomarkers found no significant differences across Hispanic, Black and Non-Hispanic Whites in concentrations of t tau, Aβ40, Aβ42 or NfL[24]. A study of ADNI participants comparing matched samples of African Americans, Non-Hispanic Whites and Hispanics found no significant difference in plasma p-tau 181 and NfL across the racial/ethnic groups[25]. Whereas, a community based study of MAs, AAs and NHWs found significant differences between the groups on these biomarkers in both cognitively unimpaired and those with MCI[26].
These mixed findings suggest the need for further investigations to assess the effect of ethnicity on plasma biomarkers. The current research investigated the relationship between the plasma biomarkers of total tau, Aβ40, Aβ42 and NfL and neuropsychological test performance in a bi-ethnic sample of cognitively unimpaired, older community dwelling adults.

2. Methods

Participants & Assessment

The current study included 1326 participants with unimpaired cognition drawn from The Health & Aging Brain Study – Health Disparities (HABS-HD) study. The HABS-HD study is an ongoing, longitudinal, project examining health disparities in cognitive aging among community dwelling older Mexican Americans. The study cohort is composed of Mexican Americans (MA) and non-Hispanic whites (NHW) and was recently expanded to include African Americans[27]. The HABS-HD methods have been described in detail elsewhere[28]. Recruitment utilizes a community-based participatory research (CBPR) approach .which has been used successfully as a recruitment modality for reaching underserved and minority populations. This approach involves collaborating with local communities through outreach (holding community events, seminars), word of mouth, marketing modalities (newspaper, television, radio). Feedback related to clinical lab work, MRI clinical reads, and neuropsychological test results is provided to the participants and their health care providers.
Criteria for inclusion in the study include 1) self-reported ethnicity of African American (AA), Mexican American (MA) or Non-Hispanic White (NHW), 2) willingness to provide blood samples, 3) capable of undergoing neuroimaging studies, 4) age 50 and above, and 5) fluent in English or Spanish. Study exclusion criteria include 1) Type 1 diabetes, 2) presence of active infection, 3) current/recent (12 month) cancer (other than skin cancer), 4) current severe mental illness that could impact cognition (other than depression), 5) recent (12 months) traumatic brain injury with loss of consciousness, 6) current/recent alcohol/substance abuse, 7) active severe medical condition that could impact cognition such as end stage renal failure, chronic heart failure or chronic obstructive pulmonary disease and 8) current diagnosis of non-Alzheimer’s related dementia.
The HABS-HD protocol includes an interview, functional exam, blood draw for clinical labs and biobanking, neuropsychological testing and 3T MRI of the brain. Amyloid and tau PET scans are ongoing for the full cohort. All aspects of the study protocol can be conducted in Spanish or English based on the preference of the participant. The HABS-HD study is conducted under IRB approved protocols and each participant (or his/her legal representative) signs written informed consent. The data included in this study includes only Mexican American and non-Hispanic white participants since the recruitment of the African American participants is ongoing. The data is available through the UNTHSC Institute for Translational Research (ITR) website[29].

Neuropsychological Assessment

The neuropsychological test battery includes: Mini Mental Status Exam[30] (MMSE); Wechsler Memory Scale- Third Edition (WMS-III)[31]; Digit Span, Logical Memory, Digit Symbol Substitution; Trail Making Test Parts A and B[32] ; Spanish-English Verbal Learning Test (SEVLT)[33] ; Animal Naming (semantic fluency)[34], FAS (phonemic fluency)[35] as well as the American National Adult Reading Test (English-speakers)[36], Word Accentuation Test (Spanish-speakers)[37], and depression (30-item Geriatric Depression Scale[38]). Norms specific to the study population were utilized where available[39]. A study partner with knowledge of the participant is interviewed for clinician completion of the Clinical Dementia Rating (CDR) Scale[40].

Diagnostic Classification

Cognitive diagnoses are assigned using an algorithm (decision tree) that is verified at consensus review. Unimpaired Cognition (UC) = no cognitive complaints, CDR sum of boxes score of 0 and cognitive test scores broadly within normal limits (i.e. performance no more than 1.5 standard deviations below the mean of the normative range on any test]); Mild Cognitive Impairment (MCI): cognitive complaint (self or other), CDR sum of boxes score between 0.5- 2.0 and at least one cognitive test score falling <=1.5 standard deviation below normative ranges; Dementia: CDR sum of boxes score >=2.5 and at least two cognitive test scores 2 standard deviation below normative ranges. For the current study, only those meeting criteria for unimpaired cognition were included.

Assays

Blood Collection & Processing Procedures

Samples were assayed by the Institute for Translational Research (ITR) Biomarker Core in the University of North Texas Health Science Center ITR Laboratory. Fasting blood collection and processing followed the international guidelines for AD biomarker studies[41]. The ITR laboratory utilized the Hamilton Robotics EasyBlood for blood processing, aliquoting and re-aliquoting and a custom Hamilton Robotics StarPlus system was utilized for preparation of all plates. Proteomic assays for this study were processed on a multi-plex biomarker assay platform using electrochemiluminescence (ECL) using commercially available kits (Quanterix, Lexington, MA, USA).

Samples

A total of 500µl of plasma was utilized to measure biomarker levels using the Single Molecule Array (Simoa) technology from Quanterix. The NfL calibration range was 0-500pg/mL with the dynamic range of 0-2000pg/mL. CV for NFL was 0.038 and LLOD was 0.038pg/mL.
Multiplexed detection of Aβ42, Aβ40 and Total Tau was conducted using Simoa technology. Calibration ranges for Aβ42, Aβ40 and Total Tau were 0-60pg/mL, 0-140pg/mL, 0-100pg/mL and dynamic ranges of 0-240pg/mL, 0-560pg/mL, 0-400pg/mL, respectively. CVs for Aβ42, Aβ40 and Total Tau were reported at 0.043, 0.043 and 0.061 respectively. LLODs for Aβ42, Aβ40 and Total Tau were reported at 0.045pg/mL, 0.196pg/mL, and 0.019pg/mL, respectively. Interplate CVs were derived for high and low pooled controls from the Quanterix automated system: NFL (high control CV= 0.035, Low control CV= 0.092); Aβ42 (High control CV= 0.051, Low control CV=0.040); Aβ40 (High control CV=0.050, Low control CV= 0.042); Total Tau (High control CV=0.040, Low control CV= 0.047).

Statistical Analysis

The relationship between the biomarkers and neuropsychological tests was assessed using SPSS-25 (IBM). Neuropsychological test scores were transformed to z scores .For MMSE raw scores were used. Demographic data were analyzed using independent group t tests and chi squared. ANOVAs co-varying sex and age assessed differences between the two ethnic groups. Regression models including age and sex were created to examine the link between the blood-based biomarkers of Aβ40, Aβ42, Total Tau, NfL and neuropsychological test performance. Regression models were created for Mexican Americans and Non-Hispanic Whites separately. Statistical significant was set at p<0.05.

3. Results

Table 1 presents the characteristics of the sample which included 765 Mexican Americans (Males N= 245, Females N= 520) and 860 Non-Hispanic Whites (Males N=378, Females N= 482) with unimpaired cognition. The MAs were significantly younger than the NHW and had significantly fewer years of education. The MA group was composed of a significantly higher percent of females. Although the MMSE scores fell within the normal range for both groups, the NHWs scored significantly higher than the MAs did. Significant differences in concentrations were found for all of the plasma biomarkers co-varying sex, age, education and APOEε4 status. NHWs had significantly higher levels of each of the biomarkers with a lower Aβ42/ Aβ40.
On neuropsychological testing NHWs scored significantly higher on Trails A (F(1, 1, 1623)= 99.457, p= .000), Trails B (F(1, 1623)= 58.22, p= .000 along with MMSE (F(1, 1623)= 530.36, p= .000). No statistically significant difference between the two groups was found for Digit Symbol Substitution (F(1, 1623)= .076, p= .783), FAS (F(1, 1623)= ..229, p= .632), Animal Naming (F(1, 1623)= .386, p= .533) , Digit Span (F(1, 1623)= .436, p= .509), Logical Memory 1 (F(1, 1623)= .007, p= .935), Logical Memory 2 (F(1, 1623)= .047, p= .892) SVELT Immediate Memory (F(1, 1288)= .135, p= .714) or SVELT Delayed (F(1, 1623)= .099, p= .5753).
Table 2 presents the relationship of the plasma biomarkers to the neuropsychological test performance. The regression models reveal that none of the biomarkers was related to performance on any of the neuropsychological tests for the NHW participants. For the MA participants, Aβ40 was a significant predictor of performance on Trails A and B and Digit Symbol Substitution. The Aβ42/Aβ40 ratio was negatively related to performance on Digit Symbol Substitution. Neither Aβ42, Total Tau nor NfL were significantly related to performance on any of the neuropsychological measures.

4. Discussion

The findings of the current research show that the relationship of select plasma biomarkers of AD to neuropsychological performance in cognitively normal participants is different for the two ethnic groups under study. For MA participants, Aβ40 was related in the expected direction to attention, processing speed and executive functions but neither Aβ42 the other biomarker of amyloid nor t tau or NfL were related to any of the cognitive domains assessed. Although the NHW participants had significantly higher levels of each of the biomarkers and lower levels of the amyloid ratio, there was no relationship to test performance. Scores on measures of language were not related to any of the plasma biomarkers in either group.
Possible explanations for the relationship of Aβ40 to specific domains of cognitive functioning for the Mexican American sample may be related to the nature of the neuropsychological tests, the characteristics of Aβ40 and the level of vascular risks in our cohort. The Trail Making Tests (A&B) and Digit Symbol Substitution Test as measures of attention, processing speed and executive functioning have been shown to activate the prefrontal cortex[42,43], an area of the brain significantly impacted by vascular disease. Aβ40 deposition has been related to cerebrovascular impairment involved in cognitive impairment and Alzheimer’s[44] . Mexican American participants in the current study had significantly higher rates of hypertension and diabetes, two vascular-related risks related to cognitive decline[45,46].
Although the current study has relatively large, well-characterized samples of two distinct ethnic groups from a community-based cohort, there are limitations that may affect the generalizability of our results. The diagnostic assignment was based on clinical rather than imaging-based criteria. The issue of diagnostic validity will be resolved in the ongoing study as the entire HABS-HD cohort is undergoing brain amyloid imaging. The study population was limited to MA and NHW participants and our knowledge of the effect of diverse ethnoracial groups on these biomarkers will be greatly enhanced as we add 1000 African Americans to our cohort. Medical co-morbidities such as chronic kidney disease, which have been shown to effect the level of plasma biomarkers of amyloid and neurodegeneration[47,48,49] were not considered in our analyses. Other research has shown that the plasma biomarkers of Aβ42/ Aβ40 and NfL when added to demographic data are useful in the prediction of cognitive decline in cognitively unimpaired[50]. Given that our data was cross-sectional, we cannot assess the ability of our baseline levels to predict cognitive decline for either MA or NHW participants. As longitudinal data becomes available for our cohort the meaningfulness of our baseline measures as predictors of cognitive change will be assessed. The current study indicates that in cognitively unimpaired, ethnic factors significantly affect the relationship of select blood based biomarkers to neuropsychological test performance. In light of these findings, ethnicity needs to be considered when evaluating the impact of these biomarkers on cognition.

Author Contributions

JRH = conceptualization and design of study; acquisition and interpretation of data; drafting and revising manuscript; final approval of version to be published; agreement to be accountable for the accuracy and integrity of the work. MP = design of study; acquisition and interpretation of data; drafting and revising manuscript; final approval of version to be published; agreement to be accountable for the accuracy and integrity of the work. SEO = conceptualization and design of study; acquisition, analysis and interpretation of data; drafting and revising manuscript; final approval of version to be published; agreement to be accountable for the accuracy and integrity of the work.

Source of Funding

Research reported here was supported by the National Institute on Aging of the National Institutes of Health under Award Numbers U19AG078109, R01AG054073 and R01AG058533. This work was also supported in part by NIH/NIBIB award P41-EB015992.The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Institutional Review Board Statement

All participants (or his/her legal representative) signed written informed consent before they participated in the study. The study was conducted in accordance with the Declaration of Helsinki and the protocol was reviewed and approved by the UNTHSC IRB protocols UNTHSC 2016–128 & 2020–125.

Data Availability

Data is available by contacting the University of North Texas Health Science Center Institute for Translational Research https://apps.unthsc.edu/itr/.

Conflicts of Interest Disclosures

SEO has multiple patents on precision medicine for neurodegenerative diseases and is the founding scientist of Cx Precision Medicine. No other authors reported any potential conflicts of interest.

References

  1. Jack CR Jr, Bennett DA, Blennow K, et al. NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease. Alzheimers Dement. 2018;14(4):535-562. [CrossRef]
  2. Lue L-F, Sabbagh MN, Chiu M-J, Jing N, Snyder NL, Schmitz C, et al. Plasma levels of Aβ42 and tau identified probable Alzheimer’s dementia: findings in two cohorts. Front Aging Neurosci. 2017;9:226. [CrossRef]
  3. Nakamura A, Kaneko N, Villemagne VL, Kato T, Doecke J, Doré V, et al. High performance plasma amyloid-β biomarkers for Alzheimer’s disease. Nature 2018;554:249–54. [CrossRef]
  4. Hampel H, O’Bryant SE, Molinuevo JL, Zetterberg H, Masters CL, Lista S, et al. Blood-based biomarkers for Alzheimer disease: mapping the road to the clinic. Nat Rev Neurol. 2018. [CrossRef]
  5. Chatterjee P, Pedrini S, Ashton NJ, et al. Diagnostic and prognostic plasma biomarkers for preclinical Alzheimer's disease [published online ahead of print, 2021 Sep 8]. Alzheimers Dement. 2021;10.1002/alz.12447. [CrossRef]
  6. Simrén J, Leuzy A, Karikari TK, et al. The diagnostic and prognostic capabilities of plasma biomarkers in Alzheimer's disease. Alzheimers Dement. 2021;17(7):1145-1156. [CrossRef]
  7. Wang J, Gao L, Liu J, et al. The Association of Plasma Amyloid-β and Cognitive Decline in Cognitively Unimpaired Population. Clin Interv Aging. 2022;17:555-565. Published 2022 Apr 20. [CrossRef]
  8. Lee YJ, Lin SY, Peng SW, et al. Predictive Utility of Plasma Amyloid and Tau for Cognitive Decline in Cognitively Normal Adults. J Prev Alzheimers Dis. 2023;10(2):178-185. [CrossRef]
  9. Aschenbrenner AJ, Li Y, Henson RL, et al. Comparison of plasma and CSF biomarkers in predicting cognitive decline. Ann Clin Transl Neurol. 2022;9(11):1739-1751. [CrossRef]
  10. Hanon O, Vidal JS, Lehmann S, et al. Plasma amyloid beta predicts conversion to dementia in subjects with mild cognitive impairment: The BALTAZAR study. Alzheimers Dement. 2022;18(12):2537-2550. [CrossRef]
  11. Li Y, Schindler SE, Bollinger JG, Ovod V, Mawuenyega KG, Weiner MW, et al. Validation of Plasma Amyloid-β 42/40 for Detecting Alzheimer Disease Amyloid Plaques. Neurology 2021. [CrossRef]
  12. Pereira JB, Janelidze S, Stomrud E, et al. Plasma markers predict changes in amyloid, tau, atrophy and cognition in non-demented subjects. Brain. 2021;144(9):2826-2836. [CrossRef]
  13. Giudici KV, de Souto Barreto P, Guyonnet S, Li Y, Bateman RJ, Vellas B. Assessment of Plasma Amyloid-β42/40and Cognitive Decline among Community-Dwelling Older Adults. JAMA Network Open 2020;3:e2028634. [CrossRef]
  14. Pascual-Lucas M, Allué JA, Sarasa L, et al. Clinical performance of an antibody-free assay for plasma Aβ42/Aβ40 to detect early alterations of Alzheimer's disease in individuals with subjective cognitive decline. Alzheimers Res Ther. 2023;15(1):2. Published 2023 Jan 5. [CrossRef]
  15. Mielke MM, Hagen CE, Wennberg AMV, Airey DC, Savica R, Knopman DS, et al. Association of plasma total tau Level with cognitive decline and risk of mild cognitive impairment or dementia in the Mayo Clinic study on aging. JAMA Neurol. 2017;74:1073–80. [CrossRef]
  16. Pase MP, Beiser AS, Himali JJ, Satizabal CL, Aparicio HJ, DeCarli C, et al. Assessment of plasma total tau level as a predictive biomarker for dementia and related endophenotypes. JAMA Neurol. 2019. [CrossRef]
  17. Osborn KE, Khan OA, Kresge HA, et al. Cerebrospinal fluid and plasma neurofilament light relate to abnormal cognition. Alzheimers Dement (Amst). 2019;11:700-709. Published 2019 Oct 22. [CrossRef]
  18. Marks JD, Syrjanen JA, Graff-Radford J, et al. Comparison of plasma neurofilament light and total tau as neurodegeneration markers: associations with cognitive and neuroimaging outcomes. Alzheimers Res Ther. 2021;13(1):199. Published 2021 Dec 14. [CrossRef]
  19. Hall JR, Johnson LA, Peterson M, Julovich D, Como T, O'Bryant SE. Relationship of Neurofilament Light (NfL) and Cognitive Performance in a Sample of Mexican Americans with Normal Cognition, Mild Cognitive Impairment and Dementia. Curr Alzheimer Res. 2020;17(13):1214-1220. [CrossRef]
  20. Gonzalez HM, Mungas D, Haan MN. A verbal learning and memory test for English- and Spanish-speaking older Mexican-American adults. Clin Neuropsychol. 2002; 16(4): 439–51.
  21. O'Bryant S, Petersen M, Hall J, et al. Characterizing plasma NfL in a community-dwelling multi-ethnic cohort: Results from the HABLE study. Alzheimers Dement. 2022;18(2):240-250. [CrossRef]
  22. Deniz K, Ho CCG, Malphrus KG, et al. Plasma Biomarkers of Alzheimer's Disease in African Americans. J Alzheimers Dis. 2021;79(1):323-334. [CrossRef]
  23. Barker W, Quinonez C, Greig MT, et al. Utility of Plasma Neurofilament Light in the 1Florida Alzheimer's Disease Research Center (ADRC). J Alzheimers Dis. 2021;79(1):59-70. [CrossRef]
  24. Brickman AM, Manly JJ, Honig LS, et al. Plasma p-tau181, p-tau217, and other blood-based Alzheimer's disease biomarkers in a multi-ethnic, community study. Alzheimers Dement. 2021;17(8):1353-1364. [CrossRef]
  25. Windon C, Iaccarino L, Mundada N, et al. Comparison of plasma and CSF biomarkers across ethnoracial groups in the ADNI. Alzheimers Dement (Amst). 2022;14(1):e12315. Published 2022 May 1. [CrossRef]
  26. Hall JR, Petersen M, Johnson L, O'Bryant SE. Characterizing Plasma Biomarkers of Alzheimer's in a Diverse Community-Based Cohort: A Cross-Sectional Study of the HABS-HD Cohort. Front Neurol. 2022;13:871947. Published 2022 Aug 18. [CrossRef]
  27. O'Bryant SE, Zhang F, Petersen M, et al. A blood screening tool for detecting mild cognitive impairment and Alzheimer's disease among community-dwelling Mexican Americans and non-Hispanic Whites: A method for increasing representation of diverse populations in clinical research. Alzheimers Dement. 2022;18(1):77-87. [CrossRef]
  28. O'Bryant SE, Johnson LA, Barber RC, et al. The Health & Aging Brain among Latino Elders (HABLE) study methods and participant characteristics. Alzheimers Dement (Amst). 2021;13(1):e12202. Published 2021 Jun 21. [CrossRef]
  29. Institute for Translational Research n.d. https://apps.unthsc.edu/itr/.
  30. Folstein MF, Folstein SE, McHugh PR. "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189-198. [CrossRef]
  31. Weschler D. Weschler Memory Scale: revised. San Antonio: Psychological Corporation;1987.
  32. Reitan RM, Wolfson D. The Halstead-Reitan Neuropsychological Test Battery: theory and interpretation. Tucson, AZ: Neuropsychology Press; 1985.
  33. Gonzalez HM, Mungas D, Haan MN. A verbal learning and memory test for English- and Spanish-speaking older Mexican-American adults. Clin Neuropsychol. 2002; 16(4): 439–51. [CrossRef]
  34. Rosser A, Hodges JR. Initial letter and semantic category fluency in Alzheimer's disease, Huntington's disease, and progressive supranuclear palsy. J Neurol Neurosurg Psychiatry. 1994;57(11):1389-1394. [CrossRef]
  35. Benton AL, Hamsher K, Sivan AB. Multilingual Aphasia Examination. 3rd ed. San Antonio: Psychological Corporation; 1994.
  36. Grober E, Sliwinski M. Development and validation of a model for estimating premorbid verbal intelligence in the elderly. J Clin Exp Neuropsychol. 1991;13(6):933-949. [CrossRef]
  37. Del Ser T, González-Montalvo JI, Martínez-Espinosa S, Delgado-Villapalos C, Bermejo F. Estimation of premorbid intelligence in Spanish people with the Word Accentuation Test and its application to the diagnosis of dementia. Brain Cogn. 1997;33(3):343-356. [CrossRef]
  38. Yesavage JA, Brink TL, Rose TL, et al. Development and validation of a geriatric depression screening scale: a preliminary report. J Psychiatr Res. 1982;17(1):37-49. [CrossRef]
  39. O'Bryant SE, Edwards M, Johnson L, Hall J, Gamboa A, O'jile J. Texas Mexican American adult normative studies: Normative data for commonly used clinical neuropsychological measures for English- and Spanish-speakers. Dev Neuropsychol. 2018;43(1):1-26. [CrossRef]
  40. Morris JC. The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology. 1993;43(11):2412-2414. [CrossRef]
  41. O'Bryant SE, Gupta V, Henriksen K, et al. Guidelines for the standardization of preanalytic variables for blood-based biomarker studies in Alzheimer's disease research. Alzheimers Dement. 2015;11(5):549-560. [CrossRef]
  42. Hagen K, Ehlis AC, Haeussinger FB, et al. Activation during the Trail Making Test measured with functional near-infrared spectroscopy in healthy elderly subjects. Neuroimage. 2014;85 Pt 1:583-591. [CrossRef]
  43. Nakahachi T, Ishii R, Iwase M, et al. Frontal activity during the digit symbol substitution test determined by multichannel near-infrared spectroscopy. Neuropsychobiology. 2008;57(4):151-158. [CrossRef]
  44. Stakos DA, Stamatelopoulos K, Bampatsias D, et al. The Alzheimer's Disease Amyloid-Beta Hypothesis in Cardiovascular Aging and Disease: JACC Focus Seminar. J Am Coll Cardiol. 2020;75(8):952-967. [CrossRef]
  45. Walker KA, Power MC, Gottesman RF. Defining the relationship between hypertension, cognitive decline, and dementia: a review. Curr Hypertens Rep. 2017; 19:24. [CrossRef]
  46. Dal Canto E, Ceriello A, Rydén L, et al. Diabetes as a cardiovascular risk factor: An overview of global trends of macro and micro vascular complications. Eur J Prev Cardiol. 2019;26(2_suppl):25-32. [CrossRef]
  47. Syrjanen JA, Campbell MR, Algeciras-Schimnich A, et al. Associations of amyloid and neurodegeneration plasma biomarkers with comorbidities. Alzheimers Dement. 2022;18(6):1128-1140. [CrossRef]
  48. O'Bryant SE, Petersen M, Hall J, Johnson LA; HABS-HD Study Team. Medical comorbidities and ethnicity impact plasma Alzheimer's disease biomarkers: Important considerations for clinical trials and practice. Alzheimers Dement. 2023;19(1):36-43. [CrossRef]
  49. Hall JR, Petersen M, Johnson LA& O’Bryant SE. for the HABS-HD Study Team (2023) Kidney Function Impacts Plasma Alzheimer’s Biomarkers in a Cognitively Normal Multi-Ethnic Cohort. Archives of Nephrology and Urology 6 (2023) 23-30. [CrossRef]
  50. Cullen, N.C., Leuzy, A., Janelidze, S. et al. Plasma biomarkers of Alzheimer’s disease improve prediction of cognitive decline in cognitively unimpaired elderly populations. Nat Commun 12, 3555 (2021). [CrossRef]
Table 1. Characteristics of the Sample.
Table 1. Characteristics of the Sample.
Mexican American
N= 765		 Non-Hispanic White
N= 860
Age M= 62.88
SD= 7.690		 M=68.29
SD= 8.335		 t= 13.543
df= 1623
p= .000*
Education M= 9.96
SD= 4.509
 M= 15.75
SD= 2.645		 t= 31.977
df= 1623
p= .000*
Gender
% Female		 68% 56% X2 = 13.924
p= .000*
MMSE M= 27.353
SD= 2.033
 M= 29.77
SD= 1.042		 F= 530.36
df= 1, 1623
p= .000*
Aβ40 M= 2.635
SD= .6209
 M= 2.795
SD= .6825
 F= 24.215
df= 1, 1623
p= .000*
Aβ42 M=1.552
SD= 1.108
 M= 1.798
SD= 1.267
 F= 17.630
df= 1, 1623
p= .000*
NfL M= 1.645
SD= 1.099
 M=1.931
SD= 1.200
 F= 24.886
df= 1, 1623
p= .000*
t-Tau M= .9896
SD= 1.356
 M= 1.252
SD= 1.581
 F= 12.738
df= 1, 1623
p= .000*
Aβ42/ Aβ40 M= .5790
SD= .2402		 M= .5402
SD= .2139		 F= 11.864
df= 1, 1623
p= .000*
*p= ≤.05.
Table 2. Regression of Plasma Biomarkers and Neuropsychological Tests by Ethnicity.
Table 2. Regression of Plasma Biomarkers and Neuropsychological Tests by Ethnicity.
Mexican Americans
N= 765		 Non-Hispanic Whites
N= 860
Digit Span NS NS
Trails A Aβ40 t= -2.612 p= .009*
 NS
Trails B Aβ40 t= -2.290 p= .022* NS
Digit Symbol Substitution Aβ40 t= -2.265 p= .024*
Aβ42/Aβ40 ratio t= -1.961 p=.050*		 NS
FAS NS NS
Animals NS NS
SEVLT Immediate Memory NS NS
SEVLT Delayed Memory NS NS
Logical Memory Immediate NS NS
Logical Memory Delayed NS NS
MMSE NS NS
*p= ≤.05 NS= Not Significant.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
Prerpints.org logo

Preprints.org is a free preprint server supported by MDPI in Basel, Switzerland.

facebook logotwitter logolinkedin logo
MDPI Initiatives
Important Links
Subscribe

Disclaimer

Terms of Use

Privacy Policy

© 2024 MDPI (Basel, Switzerland) unless otherwise stated