lnc-AD : Organoid-based lncRNA discovery platform for Alzheimer's Disease

Objectives:

Our research aims to discover novel long non-coding RNAs (lncRNAs) involved in familial and sporadic forms of Alzheimer’s Disease (AD). Using a patient-derived organoid platform, we previously identified thousands of lncRNAs associated with AD, the majority of which were unknown. Leveraging sequencing data from the NIAGADS database, along with data obtained from the DIAN database (Dominantly Inherited Alzheimer Network), we aim to validate those novel lncRNA and identify which may be involved in the disease process.

Design :

Aim 1 : using bulk and single-cell RNAseq datasets, we will assess the expression of the lncRNAs of interest in patient samples, and identify those which are dysregulated in familial and sporadic AD patients. The single cell sequencing datasets will allow us to achieve a cell-type resolution.

Aim 2 : using whole-genome sequencing (WGS) from patients and controls, we will determine if some of those lncRNAs are associated with known SNPs or rare variants linked to AD.
Altogether, this work will advance our understanding of the genetic bases of AD by shedding light on an underexplored genomic category which may play causative roles in disease development, and provide novel therapeutic targets.

Analysis plan :

Raw files from the bulk (NG00083, previously obtained) and single-cell (NG00108) RNAseq datasets will be aligned to a custom genome containing the novel lncRNA we identified. To undertake differential analyses, we will need to access phenotypic information regarding disease status, as well as risk-modifying variant status. RIN, age of death, post-mortem interval, and sex may be used for correcting expression data. We have previously obtained approval from DIAN to access their datasets. All these datasets were previously analyzed together in two recent publications (PMIDs : 29880032 and 37085492).

To appropriately make use of the WGS data from the AD sequencing project (NG00067), we will need to access information regarding age at disease onset, educational attainment, and available clinical scores.

All data will be processed locally, and results from our analyses will be shared in agreement with the policies.

Our research is focused on finding new long non-coding RNAs (lncRNAs) that play a role in Alzheimer’s Disease (AD). lncRNAs are an understudied type of gene, which are however known to be implicated in many biological functions. We previously found many unknown lncRNAs linked to AD using a patient-derived organoid platform. We now wish to validate these findings using molecular data from the NIAGADS and DIAN databases.

We have two main goals:

1. We will use RNA sequencing data to study the expression of these lncRNAs in patients and identify which ones are abnormal. Single-cell sequencing will help us see how these lncRNAs behave in different cell types.

2. We will use whole-genome sequencing to check if these lncRNAs are connected to common or rare genetic variants known to be associated with AD.

This work will improve our understanding of the genetic causes of AD, of lncRNA biology and may reveal new targets for treatment.