P4‐237: WHOLE GENE‐BASED ASSOCIATION OF BASELINE PLASMA HOMOCYSTEINE IN THE ADNI‐1 COHORT

Homocysteine (HCY) is one of the key metabolites in one-carbon metabolism pathway and plasma HCY was shown to be elevated in AD and associated with brain atrophy 1,2. Identification of genetic influence on HCY level can inform which genes will subsequently affect the levels of other metabolites in the one-carbon pathway and can reveal new genetic risk factors for AD through the one-carbon pathway. Quality-controlled baseline plasma HCY and GWAS data were from 742 non-Hispanic Caucasian participants (Table 1) in the Alzheimer's Disease Neuroimaging Initiative. G ene-based analysis was conducted using an additive genetic model with and without APOE e 4 status in addition to sex and age as covariates to investigate the overall effect of all genetic variants within each gene using HYST 3. Genes with p<2.13 x10 - 6 (0.05/23,505 genes) were considered to be genome-wide significant. One gene (KLF15, p = 4.02 x10 - 7) w as genome-wide significant, even after adjusting for APOE genotype. Th is gene ha s not been previously studied in AD nor has it been associated with plasma HCY level, to date.KLF15 and SP1 are known to synergistically activate acetyl-CoA synthetase 2 (AceCS2) which produces acetyl-CoA for oxidation 4.Acetyl-CoA is a co-enzyme in the synthesis of acetylcholine, an important neurotransmitter involved in learning and memory. SP1 was recently identified in a transcriptional regulation network involving many genes associated with memory impairment using the ADNI cohort 5. Two more genes (VAV3, COX10) show suggestive association (p<6.98 x10 -6).VAV3 is known to interact with phospholipase C, gamma 1 (PLCG1), which through diacylglycerol (DAG) is involved in the degradation of phosphocholine, a phosphomonoester elevated in hippocampus in early stages of AD. COX activity was shown to be significantly decreased in the hippocampus of AD patients 6. Our results demonstrate the promise of integrating genetics with quantitative metabolomic endophenotypes to better understand metabolomic changes using genetics and to discover novel mechanistic targets related to AD pathophysiology.[1] Seshadri et al., N Engl J Med, 2002. [2] Rajagopalan et al., Neuroreport, 2011. [3] Li et al., Am J Hum Genet, 2012. [4] Yamamoto et al., J Biol Chem, 2004. [5] Ramanan et al., Brain Imaging Behav, 2012. [6] Bosetti et al., Neurobiol Aging, 2002.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.