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School of Medicine Publications and Presentations

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2020

Genetic correlation

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Neurocognitive Impairment In Type 2 Diabetes: Evidence For Shared Genetic Aetiology, Josephine Mollon, Joanne E. Curran, Samuel R. Mathias, Emma E. M. Knowles, Phoeve Carlisle, Peter T. Fox, Rene L. Olvera, Harald Hh Goring, Amanda Rodrigue, Laura Almasy, Ravindranath Duggirala, John Blangero, David C. Glahn May 2020

Neurocognitive Impairment In Type 2 Diabetes: Evidence For Shared Genetic Aetiology, Josephine Mollon, Joanne E. Curran, Samuel R. Mathias, Emma E. M. Knowles, Phoeve Carlisle, Peter T. Fox, Rene L. Olvera, Harald Hh Goring, Amanda Rodrigue, Laura Almasy, Ravindranath Duggirala, John Blangero, David C. Glahn

School of Medicine Publications and Presentations

Aims/hypothesis: Type 2 diabetes is associated with cognitive impairments, but it is unclear whether common genetic factors influence both type 2 diabetes risk and cognition.

Methods: Using data from 1892 Mexican-American individuals from extended pedigrees, including 402 with type 2 diabetes, we examined possible pleiotropy between type 2 diabetes and cognitive functioning, as measured by a comprehensive neuropsychological test battery.

Results: Negative phenotypic correlations (ρp) were observed between type 2 diabetes and measures of attention (Continuous Performance Test [CPT d']: ρp = -0.143, p = 0.001), verbal memory (California Verbal Learning Test [CVLT] recall: ρp = -0.111, p = 0.004) …


Imaging Local Genetic Influences On Cortical Folding, Aaron F. Alexander-Bloch, Armin Raznahan, Simon N. Vandeker, Jakob Seidlitz, Zhixin Lu, Samuel R. Matthias, Emma Knowles, Josephine Mollon, Amanda Rodrigue, Joanne E. Curran, Harald H. H. Goring, Peter T. Fox, John Blangero Mar 2020

Imaging Local Genetic Influences On Cortical Folding, Aaron F. Alexander-Bloch, Armin Raznahan, Simon N. Vandeker, Jakob Seidlitz, Zhixin Lu, Samuel R. Matthias, Emma Knowles, Josephine Mollon, Amanda Rodrigue, Joanne E. Curran, Harald H. H. Goring, Peter T. Fox, John Blangero

School of Medicine Publications and Presentations

Recent progress in deciphering mechanisms of human brain cortical folding leave unexplained whether spatially patterned genetic influences contribute to this folding. High-resolution in vivo brain MRI can be used to estimate genetic correlations (covariability due to shared genetic factors) in interregional cortical thickness, and biomechanical studies predict an influence of cortical thickness on folding patterns. However, progress has been hampered because shared genetic influences related to folding patterns likely operate at a scale that is much more local (cm) than that addressed in prior imaging studies. Here, we develop methodological approaches to examine local genetic influences on cortical thickness and …


Heritability Of 596 Lipid Species And Genetic Correlation With Cardiovascular Traits In The Busselton Family Heart Study, Gemma Cadby, Phillip E. Melton, Nina S. Mccarthy, Corey Giles, Natalie A. Mellett, Kevin Huynh, Joseph Hung, John Beilby, Marie-Pierre Dube, Gerald F. Watts, John Blangero, Peter J. Meikle, Eric K. Moses Feb 2020

Heritability Of 596 Lipid Species And Genetic Correlation With Cardiovascular Traits In The Busselton Family Heart Study, Gemma Cadby, Phillip E. Melton, Nina S. Mccarthy, Corey Giles, Natalie A. Mellett, Kevin Huynh, Joseph Hung, John Beilby, Marie-Pierre Dube, Gerald F. Watts, John Blangero, Peter J. Meikle, Eric K. Moses

School of Medicine Publications and Presentations

Introduction: Cardiovascular disease (CVD) is the leading cause of death worldwide, and genetic investigations into the human lipidome may provide insight into CVD risk. The aim of this study was to estimate the heritability of circulating lipid species and their genetic correlation with CVD traits.

Methods: Targeted lipidomic profiling was performed on 4492 participants from the Busselton Family Heart Study to quantify the major fatty acids of 596 lipid species from 33 classes. We estimated narrow-sense heritabilities of lipid species/classes, and their genetic correlations with eight CVD traits – body mass index, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol, triglycerides, …