The goal of this project is to identify quantitative trait loci associated with variation in brain structure and function. The ultimate promise of this research is the discovery of genes that predispose to brain disorders and mental illnesses. We believe that the analysis of genetic influences on brain structure and function in randomly sampled extended pedigrees will provide significant clues regarding the genes that are involved in both normal and pathological brain function. The focus of the project is on the genetic dissection of quantitative endophenotypes that more directly index the underlying biological basis of brain function than do discrete disease states themselves. To this end, we will perform neuroimaging and conduct neuropsychological examinations on Mexican American individuals who have been part of our ongoing genetic research studies for the past 15 years. All participants were previously genotyped and our plan is to utilize existing genome scan and genome-wide quantitative transcriptomic data for correlation with neuroanatomic and neurocognitive variables.
Our specific aims are to: 1) perform high quality brain magnetic resonance imaging and neuropsychological examinations on 1,000 Mexican Americans who are members of approximately 30 large extended families, 2) assess the quantitative genetic architecture of brain-related phenotypes by estimating their heritabilities and their genetic correlations, 3) classify specific brain morphological variables and quantitative leukocyte-derived gene expression measures as endophenotypes related to brain function, 4) localize QTLs influencing variation in the quantitative brain-related phenotypes by performing linkage-based genome scanning using the variance component method, 5) refine the position of localized QTLs and identify positional candidate loci using an objective prioritization strategy that jointly utilizes in silico bioinformatics, genetic, and transcriptional data, and 6) identify the most likely functional variations within the two best positional candidate genes. This project involves coordinated R01 applications from Dr. John Blangero, Southwest Foundation for Biomedical Research, and Drs. David Glahn and Peter Fox, University of Texas Health Science Center at San Antonio. If funded, our data and biomaterials will be incorporated into the NIMH Human Genetics Initiative making them available to qualified researchers in the wider scientific community. Relevance to agency mission: Brain-related mental diseases are a major public health burden whose biology is still largely unknown. By identifying genes involved in brain function and structure, we will provide novel biological candidates for the determinants of such diseases and thus improve potential for intervention. ? ? ? ?
| Knowles, Emma E M; Mathias, Samuel R; Mollon, Josephine et al. (2018) A QTL on chromosome 3q23 influences processing speed in humans. Genes Brain Behav :e12530 |
| Adhikari, Bhim M; Jahanshad, Neda; Shukla, Dinesh et al. (2018) Comparison of heritability estimates on resting state fMRI connectivity phenotypes using the ENIGMA analysis pipeline. Hum Brain Mapp 39:4893-4902 |
| Knowles, Emma E M; Curran, Joanne E; Meikle, Peter J et al. (2018) Disentangling the genetic overlap between cholesterol and suicide risk. Neuropsychopharmacology 43:2556-2563 |
| Hodgson, Karen; Poldrack, Russell A; Curran, Joanne E et al. (2017) Shared Genetic Factors Influence Head Motion During MRI and Body Mass Index. Cereb Cortex 27:5539-5546 |
| Knowles, Emma Em; Meikle, Peter J; Huynh, Kevin et al. (2017) Serum phosphatidylinositol as a biomarker for bipolar disorder liability. Bipolar Disord 19:107-115 |
| Hibar, Derrek P (see original citation for additional authors) (2017) Novel genetic loci associated with hippocampal volume. Nat Commun 8:13624 |
| Hodgson, Karen; Almasy, Laura; Knowles, Emma E M et al. (2017) The genetic basis of the comorbidity between cannabis use and major depression. Addiction 112:113-123 |
| Knowles, E E M; Huynh, K; Meikle, P J et al. (2017) The lipidome in major depressive disorder: Shared genetic influence for ether-phosphatidylcholines, a plasma-based phenotype related to inflammation, and disease risk. Eur Psychiatry 43:44-50 |
| Hodgson, Karen; Carless, Melanie A; Kulkarni, Hemant et al. (2017) Epigenetic Age Acceleration Assessed with Human White-Matter Images. J Neurosci 37:4735-4743 |
| Kulkarni, Hemant; Mamtani, Manju; Wong, Gerard et al. (2017) Genetic correlation of the plasma lipidome with type 2 diabetes, prediabetes and insulin resistance in Mexican American families. BMC Genet 18:48 |
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