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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 datasets. Herein, we leveraged six existing bottom-up proteomics datasets, 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 datasets 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 it is a potential candidate that should be further explored in AD biomarker discovery efforts.

African American/Black adults are twice as likely to have Alzheimer’s disease (AD) compared to non-Hispanic White adults. Genetics partially contributes to this disparity in AD risk, among other factors, as there are several genetic variants associated with AD that are more prevalent in individuals of African or European ancestry. The phospholipid-transporting ATPase ABCA7 (ABCA7) gene has stronger associations with AD risk in individuals with African ancestry than in individuals with European ancestry. In fact, ABCA7 has been shown to have a stronger effect size than the apolipoprotein E (APOE) ɛ4 allele in African American/Black adults. ABCA7 is a transmembrane protein involved in lipid homeostasis and phagocytosis. ABCA7 dysfunction is associated with increased amyloid-beta production, reduced amyloid-beta clearance, impaired microglial response to inflammation, and endoplasmic reticulum stress. This review explores the impact of ABCA7 mutations that increase AD risk in African American/Black adults on ABCA7 structure and function and their contributions to AD pathogenesis. The combination of biochemical/biophysical and ‘omics-based studies of these variants needed to elucidate their downstream impact and molecular contributions to AD pathogenesis is highlighted.

We have prepared and characterized seven new nickel(II) complexes that each incorporate tris(2-aminoethyl)amine (tren) and a deprotonated carbonyl-containing compound, both as two separate ligands and when condensed into a 1:1 Schiff-base ligand. We found the application of an existing literature procedure to be unsuccessful in procuring the Schiff-base variants without first assembling the ligand. IR, UV–VIS, magnetic susceptibility, elemental, and melting point data were obtained for the complexes prepared. Three of these compounds were also characterized through X-ray diffraction, and the resulting crystal structures are presented here for [Ni(acac)(tren)]BPh4 (1), [Ni(trensal)(OH2)]ClO4 (5), and [Ni(trenvan)]BPh4·H2O (7) ([acac]- = acetylacetonate ligand, [trensal]- = deprotonated 1:1 condensation product of tren and salicylaldehyde, [trenvan]- = deprotonated 1:1 condensation product of tren and ortho-vanillin). We also screened a selection of the complexes for biological activity. Two of the complexes, [Ni(trenacac)]BPh4 (4) and [Ni(trensal)]BPh4·½H2O (6) were found to fully inhibit the growth of the pathogenic yeast Candida albicans at the sub-micromolar concentration range ([trenacac]- = deprotonated 1:1 condensation product of tren and acetylacetone).

Alzheimer’s disease (AD) disproportionately affects African Americans (AAs) and Hispanics, who are more likely to have AD than non-Hispanic Whites (NHWs) and Asian Americans. Racial disparities in AD are multifactorial, with potential contributing factors including genetics, comorbidities, diet and lifestyle, education, healthcare access, and socioeconomic status. Interestingly, comorbidities such as hypertension, type 2 diabetes mellitus, and cardiovascular disease also impact AAs. It is plausible that a common underlying molecular basis to these higher incidences of AD and comorbidities exists especially among AAs. A likely common molecular pathway that is centrally linked to AD and these noted comorbidities is alterations in lipid metabolism. Several genes associated with AD risk—most notably, the e4 allele of the apolipoprotein E (APOE) gene and several mutations in the ATP-binding cassette transporter A7 (ABCA7) gene—are linked to altered lipid metabolism, especially in AAs. This review explores the role of lipid metabolism in AD broadly, as well as in other comorbidities that are prevalent in AAs. Because there are gaps in our understanding of the molecular basis of higher incidences of AD in AAs, ‘omics approaches such as proteomics and lipidomics are presented as potential methods to improve our knowledge in these areas.