Identifying Key Molecular Differences Between Lewy Body and Alzheimer's Disease via Multi-Omics Analysis - PROJECT SUMMARY: Dementia affects nearly 7 million Americans and includes multiple underlying pathologies that are frequently misdiagnosed due to overlapping clinical symptoms.1,2 While Alzheimer’s disease (AD) is the most common form of neurodegenerative dementia, dementia with Lewy bodies (DLB) and Parkinson’s disease dementia (PDD) are also prevalent in individuals over the age of 65.3,4 Lewy body disease (LBD) encompasses both DLB and PDD and is characterized by abnormal α-synuclein aggregates, often co-occurring with AD pathology - amyloid-β (Aβ) plaques and neurofibrillary tangles (NFTs).5 AD and LBD can affect overlapping cortical regions and present with similar symptoms, complicating diagnosis and treatment.5 A key knowledge gap lies in understanding the molecular alterations that differentiate LBD and AD. Additionally, genetic sex strongly influences disease risk, progression, and therapeutic response in neurodegenerative disorders.6,7 Addressing this requires incorporating sex as a biological variable to inform targeted treatment strategies. This project aims to close these gaps by characterizing transcriptomic and genomic alterations in postmortem anterior cingulate cortex tissue from 607 neuropathologically defined cases, including LBD, AD, amyloid-only pathology, and controls.8 The proposed research will pursue four aims: Aim 1 (K99 Y1): Investigate isoform dysregulation across pathologies using bulk short-read and long-read RNA sequencing, identifying alternative splicing and cryptic exon inclusion. Aim 2 (K99 Y2): Characterize cell-type-specific transcriptional changes using single-nucleus RNA sequencing, revealing cell-type heterogeneity and molecular complexity in mixed pathologies. Aim 3 (R00 Y3): Identify eQTLs and sQTLs by integrating SNP array and bulk RNAseq data to link genomic variants with dysregulated gene and isoform expression. Aim 4 (R00 Y4–Y5): Develop and evaluate predictive deep learning models that integrate multi-omics data from Aims 1–3 and external datasets to identify early molecular markers of pathology. Collectively, this research proposal leverages a large, unique dataset and advanced ‘omics technologies to investigate isoform dysregulation, cell-type-specific transcriptional changes, and QTLs unique to or shared by LBD and AD. It also evaluates sex differences by measuring the effect size of sex in molecular analyses, offering insights into sex-biased disease mechanisms. Career development: This award will significantly enhance my career development, enabling me to expand my expertise in transcriptomic and genomic analysis through multi-omics approaches. During the K99 phase at TGen, I will receive mentored training in long-read and single-nucleus RNA sequencing, as well as wet lab techniques for validating findings. I will also engage in collaboration workshops, seminars on emerging ‘omic technologies, and the Columbia University Career MODE program to support my transition to independence. In the R00 phase, I will establish my own lab to investigate molecular alterations in neurodegeneration by integrating ‘omics data generated in this research proposal with public datasets. Guided by a multidisciplinary team of mentors, this structured training plan will support my goal of launching an independent research program focused on the molecular mechanisms of neurodegeneration, particularly the significant role of pathology and sex differences.
