Janve, Vaibhav A.

Abstract Background pTau217 is a well validated plasma biomarker for Alzheimer's disease (AD), sensitive to the accumulation of amyloid pathology in the preclinical stages of disease. We leveraged whole blood RNA sequencing and plasma pTau217 measures of amyloid burden to identify blood transcriptomic gene‐network changes that relate to plasma pTau217 levels in cognitively normal older adults. We then quantified the abundance of cell populations from the transcriptomic data to identify blood cell abundance alterations that correlate with plasma ptau217 levels. Method Whole blood RNA sequencing and plasma pTau217 data were obtained from 1739 participants in the Anti‐Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) Study. RNAseq data were aligned, sorted, counted, batch normalized, and iteratively adjusted for covariates. 20,718 genes were available for analysis following quality control. Plasma samples ( n = 1597) were analyzed for pTau217 using the Eli Lilly and Company Diagnostics Laboratory immunoassay. Samples from 724 participants (63% females, mean age 71, 61% amyloid+) with RNA sequencing and biomarker data were used for analysis. Cell fractions were quantified using CIBERSORTx (LM22 used as reference) and WGCNA was used to calculate gene co‐expression modules. Linear regression related gene module expression or cell fraction to mean pTau217 levels covarying for age, sex, education, APOE ε2 and ε4 status. Correction for multiple comparisons used the false discovery rate. Gene enrichment was performed using Gene Ontology. Result Five gene modules were associated with plasma pTau217. For the turquoise module (β=‐0.81, p.fdr=0.005), higher expression was associated with higher p ‐tau217 while higher expression in the blue (β=‐0.70, p.fdr=0.01), lightcyan (β=‐0.68, p.fdr=0.01), grey60 (β=‐0.64, p.fdr=0.02), and brown (β=‐0.55, p.fdr=0.04) modules were associated with lower p ‐tau217. These modules were enriched for phagocytosis, ribonucleoprotein complex biogenesis, immunoglobulin mediated immune response, nucleosome assembly, and cytoplasmic translation pathway genes. In cell fraction analysis, higher predicted abundance of neutrophils related to ptau217 levels (β=0.33, p.fdr=0.03). Conclusion Our results demonstrate an association between immune response and epigenetic pathway genes with plasma pTau217 levels in preclinical AD. Future work will seek to clarify whether these signatures also relate to brain amyloid PET to evaluate blood transcription networks as complementary biomarkers to improve preclinical prediction.

Abstract INTRODUCTION New methods estimate amyloid positivity onset age (EAOA) from amyloid positron emission tomography (PET). We explore the genetics of EAOA to identify molecular factors underlying the earliest Alzheimer's disease (AD) changes. METHODS Harmonized amyloid PET data from 4216 participants were used in genome‐wide survival, tissue‐specific gene expression, and genetic covariance analyses of EAOA. RESULTS Variants in apolipoprotein E ( APOE ), ABCA7 , and RASGEF1C associated with earlier EAOA. APOE ε4/ε4 and ε3/ε4 converted 6.3 and 5 years earlier than ε3/ε3, respectively. ε2 was protective against earlier EAOA. rs4147929, an expression quantitative trait locus for ABCA7 , associated with a 4 year earlier EAOA. This variant was associated with lower brain expression of ABCA7 , which was associated with increased amyloid pathology at autopsy. Multiple immune‐related diseases shared genetic covariance with EAOA. DISCUSSION APOE , ABCA7 , and RASGEF1C associated with earlier EAOA, with supporting evidence from tissue‐specific expression analyses, offering insights into intervenable targets at early stages of AD. Highlights Novel methods estimate how long ago a patient converted to amyloid positivity. Estimating this amyloid clock allows us to determine the onset of the earliest Alzheimer's disease changes. We evaluated what genes influence when someone converts to amyloid positivity. Apolipoprotein E ( APOE ) , ABCA7 , and RASGEF1C associated with earlier age of amyloid positivity. Genetic results were supported by tissue‐specific expression analyses.