Introduction:

Proteogenomics is an emerging area of research that may provide novel insights into Alzheimer"s pathophysiology and therapeutic targets. While protein quantitative trait loci (pQTL) analysis has recently been performed with cerebrospinal fluid and brain samples, identification of pQTLs in easily accessible sample types like plasma could enable access to larger scale studies and provide insight to systemic factors influencing disease progression. Here, we identify pQTLs in an Alzheimer"s disease cohort using Proteograph™ XT and mass spectroscopy (MS)-based proteomics from plasma samples. With this study, we aim to examine the impact of genetic variation on protein abundance and reveal the potential functional implications in Alzheimer"s disease.

Methods:

Blood samples were collected from 1,005 participants in the Massachusetts Alzheimer"s Disease Research Center. Participant metadata includes demographics, cognitive scores, and clinical diagnoses. We also collected the plasma biomarker pTau-217 which has been shown to have strong diagnostic accuracy. Proteomics data were obtained by processing plasma samples with early release Proteograph XT (Seer, Inc.) before analysis on an Orbitrap Exploris 480 MS. Participant genotypes were obtained with low pass sequencing by Gencove. MS data was searched by DIA-NN in Library Free mode with scalable match between runs. The low pass sequencing data was mapped and imputed using GLIMPSE. We identified pQTLs and differential protein abundances based on Alzheimer's disease status and rate of progression. We then applied Mendelian randomization methods to identify putative causal protein markers of Alzheimer"s disease and cognitive decline.

Preliminary Data:

To reveal candidate proteins associated with Alzheimer"s disease, we performed differential abundance analysis and identified 138 protein groups that were different between healthy and AD groups. Additionally, eight protein groups were associated with dementia progression using Cox regression analysis. For pQTL identification, we performed a preliminary study with a pilot subset of the samples (N = 161) with array genotypes. We performed pQTL analysis both at peptide abundances for each nanoparticle as well as protein level abundance inferred by MaxLFQ rollup for nanoparticle-peptide abundances due to increased sensitivity of peptide level measurements. With nanoparticle-peptide level quantification, we identified 55 Bonferroni-corrected protein group pQTLs (16 cis and 39 trans) while panel protein quantification revealed 10 Bonferroni-corrected protein group pQTLs (5 cis and 5 trans). We will evaluate the reproducibility of the results from both quantification levels in the full data for defining our final set of pQTLs generated across all 1,005 participants.

Novel Aspect:

Identifying putative causality between protein abundance and AD progression with low pass sequencing, MS pQTLs, and Mendelian randomization.