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Genetics of CSF Metabolites in Alzheimer Disease and other Brain Disorders

$3,811,778RF1FY2018AGNIH

University Of California Los Angeles, Los Angeles CA

Investigators

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Abstract

Project Summary In humans, cerebrospinal fluid (CSF) reflects the biochemical state of the central nervous system (CNS) under different physiological conditions and therefore is an excellent source for identifying biomarkers for brain disorders. We hypothesize that comprehensive exploration of genetic factors involved in neurometabolite levels in the CNS will give unprecedented insights into how genetic variation controls brain metabolism and links to health and disease. The proposal involves the study of CSF neurometabolites in a discovery and replication sample of 4,000 subjects from a relatively homogenous population to maximize the power for new discoveries. Metabolomic screening of CSF yields roughly thousand analyte levels of primary metabolites and complex lipids and is complemented by the collection of targeted measures of amyloid-? and tau that are currently in use as diagnostic biochemical markers for Alzheimer disease. Genome-wide genetic analysis is performed to identify individual genes and loci contributing to these metabolite levels. For each of the analytes and their ratios, we will establish the effects of age, gender, and other biometric measures. The inclusion of large groups of patients with diagnosis of Alzheimer disease and subjective cognitive decline will make it possible to identify CSF metabolite profiles linked to these disorders. We will employ innovative statistical methods to examine the genetic architecture and heritability of neurometabolites and their genetic correlates with common, complex human brain disorders and related traits with available genome-wide association (GWAS) data. Evidence of genetic correlations between neurometabolites and brain disorders amounts to biomarker discovery linked to disease susceptibility. Moreover, we will apply novel methods to impute the genetic component of CSF metabolite levels into available GWAS cohorts and perform neurometabolomic- wide association studies of brain-related disorders. These approaches will give us a unique opportunity to study the genetic basis of brain function in general and facilitate discovery of genetic links between neurometabolites and human traits involving the CNS. The large genetic atlas of human neurometabolites, which we are generating, will be made publicly available to the scientific community to further advance discovery of brain biology.

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