tRNA modifications regulating mitochondrial function and the mitochondrial proteome in AD/ADRD

Abstract Mitochondrial (MT) function decreases with age, and its dysfunction contributes to the pathogenesis of Alzheimer’s disease and related disorders (AD/ADRD). The 22 mitochondrial tRNAs (mt-tRNAs), with help from nuclear-tRNAs, translate the 13 MT-encoded proteins, which are essential subunits of the respiratory chain complexes responsible for ATP production. mt-tRNAs also contain post-transcriptional modifications catalyzed by nuclear-encoded mt-tRNA-modifying enzymes. After transcription the many of the ~500 nuclear-encoded tRNAs (nuclear-tRNA) with cytoplasmic modifications should impact MT function by influencing the translation efficiency of nuclear-encoded MT proteins synthesized in the cytoplasm and then imported into the MT, which is defined as the MT proteome and includes ~1,150 proteins encoded by both nuclear DNA (nDNA) and mitochondrial DNA (mtDNA). In humans ~50 types of tRNA modifications occur on cytoplasmic and mt-tRNAs. We found that mt-tRNA-modifying enzymes (e.g., TRMU, NSUN3, GTPBP3, PUS1) are upregulated in human AD brains. An emerging area of interest is to investigate tRNA-based MT-nuclear crosstalk. Rigorous scientific evidence also supports the idea that abnormal MT function linked to susceptible loci in mtDNA and nDNA increases the likelihood of AD by changing the expression of tRNAs or modifications to perturb MT-nuclear interactions in AD brain. We hypothesize that genetic mutation and aberrant modification of mt-tRNA and nuclear-tRNA impair the bidirectional MT-nuclear crosstalk, to disrupt the translational efficiency of the MT proteome. In this proposal, we will identify genetic mutations in mtDNA, tRNA genes, and genes encoding the MT proteome associated with AD status using >100k multi-ancestry WGS data in the AD Sequencing Project (ADSP), and AD-related multi-ancestry endophenotypes harmonized by the ADSP-PHC, and molecular pathways in multi-ancestry multi-omics data in the AMP-AD and the ADSP-Functional Genomics Consortium (ADSP-FGC) (Aim 1). Then we will identify AD-related tRNAs and modifications using our unique platforms of AQRNA-seq that can profile tRNA abundance, and LC-MS that can profile 50 tRNA modifications from two human AD brain regions to examine relatively region-specific and AD-related tRNA profiles, providing an exceptional resource for studying tRNAs in ADRD (Aim 2). Finally, we will select the top tRNAs (~5) and tRNA- modifying enzymes (2-5) for further functional evaluation with our 3D human assembloid model of ADRD, to identify those tRNAs or tRNA modifications with the strongest effects on pathology or neurodegeneration and thus uncover disease mechanisms or therapeutic targets for AD (Aim 3).