Polanco, Jean M Marrero

Abstract Background African Americans (AA) are twice as likely to develop dementia than non‐Hispanic Whites but remain underrepresented in Alzheimer's Disease (AD) research. Recent studies have identified AA specific risk factors for AD. Therefore, targeted biomarkers and/or therapies may be needed to effectively treat AD in AA. In this study, we aimed to determine if genetic variants that show association with AD‐risk, plasma transcript or protein levels in AA, may serve as accurate and accessible AD biomarkers. Method In 189 clinically diagnosed AA AD cases and 183 AA cognitively unimpaired (CU) controls, we performed targeted DNA sequencing of 10 AD‐associated loci. Genetic variants at these loci were tested for association with corresponding plasma transcripts and total tau protein levels previously measured in this cohort using a custom nanoString panel and Simoa assays, respectively. Utilizing phased haplotypes (SHAPEIT4) from target sequencing, we inferred local ancestry (RFMix v2) using five superpopulations from the 1000 Genomes Project as anchors. Subsequently, we tested the association of each ancestry specific allelic dosages with endophenotypes using Tractor. In receiver operating characteristic (ROC) analyses, the most significant e/pQTLs were added sequentially to a base model that included age and sex to identify e/pQTLs that improved the accuracy to correctly classify AD cases and CU controls. Result Of the 5,112 variants that were tested, 70 were nominally associated with AD‐risk and with plasma transcript or protein levels. Seven of these 70 variants also showed nominally significant associations of AD‐risk and transcript levels with either African or East Asian local ancestry. ROC analysis of age, sex, 33 e/pQTLs in APOE , SORL1 , TLR4 , EPHA1 , ABCA7 , CLU , and CR1 , and plasma levels of APP, ABCA7, AKAP9, CD14, CLU, and APOE ‐ɛ4 dosage achieved 88.2% area under the curve to discriminate AD vs. CU, a 30.4% improvement over the base model that only included age and sex. Conclusion Plasma transcript levels and e/pQTLs are promising diagnostic biomarkers for AD that may improve accessibility and reduce costs for a more accurate diagnosis of AD.

AbstractBackgroundGiven the overlap of symptoms between Alzheimer’s disease (AD) and other dementias, it is essential to develop widely accessible biomarkers that will ensure an accurate diagnosis of AD to enable its proper treatment. African Americans (AA) are twice more likely to develop AD than non‐Hispanic whites (NHW) and yet they remain underrepresented in AD research. The few studies conducted in AA suggest that there are different factors that influence AD in this population; therefore, it is possible that different biomarkers and/or therapies may be needed to effectively treat AD in AA. In this study we are testing the hypothesis that genetic variants that show association with AD‐risk in AA and with plasma levels of transcript and proteins may serve as AD biomarkers which are more accessible and less costly than cerebrospinal fluid or neuroimaging biomarkers.MethodsIn 189 AD cases and 183 cognitively unimpaired (CU) AA participants of the Florida Consortium of African American Alzheimer’s Disease Studies (FCA3DS), we performed targeted DNA sequencing of 10 AD‐associated loci. Genetic variants were tested for association with plasma transcripts and plasma total tau protein levels previously measured in this cohort using a nanoString® custom panel (Reddy J, et al. 2022) and Simoa assays (Deniz K, et al. 2021), respectively. In receiver operating characteristic (ROC) analyses, the most significant expression/protein quantitative trait loci (eQTL/pQTL) were added sequentially to a base model that included only age and sex to identify eQTL/pQTL that improved the accuracy to correctly classify AD cases vs. CU.ResultsOf the 5112 variants identified in the targeted sequencing, 71 were nominally associated (p<0.05) with plasma transcript/protein levels and with AD‐risk. ROC analysis of age, sex, eQTL/pQTL in APOE, ABCA7, AKAP9, EPHA1, SORL1, and TLR4, and plasma levels of APP, ABCA7, AKAP9, CD14, CLU, and APOE‐ɛ4 dosage achieved 77.6% area under the curve (AUC) to discriminate AD vs. CU, a 19.9% improvement over a model that only included age and sex.ConclusionsPlasma transcript levels and eQTL/pQTL are promising diagnostic biomarkers for AD that may improve accessibility and reduce costs for a more accurate diagnosis of AD.