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Full-Text Articles in Other Genetics and Genomics
Unsupervised Deep Representation Learning Enables Phenotype Discovery For Genetic Association Studies Of Brain Imaging, Khush Patel, Ziqian Xie, Hao Yuan, Sheikh Muhammad Saiful Islam, Yaochen Xie, Wei He, Wanheng Zhang, Assaf Gottlieb, Han Chen, Luca Giancardo, Alexander Knaack, Evan Fletcher, Myriam Fornage, Shuiwang Ji, Degui Zhi
Unsupervised Deep Representation Learning Enables Phenotype Discovery For Genetic Association Studies Of Brain Imaging, Khush Patel, Ziqian Xie, Hao Yuan, Sheikh Muhammad Saiful Islam, Yaochen Xie, Wei He, Wanheng Zhang, Assaf Gottlieb, Han Chen, Luca Giancardo, Alexander Knaack, Evan Fletcher, Myriam Fornage, Shuiwang Ji, Degui Zhi
Faculty, Staff and Student Publications
Understanding the genetic architecture of brain structure is challenging, partly due to difficulties in designing robust, non-biased descriptors of brain morphology. Until recently, brain measures for genome-wide association studies (GWAS) consisted of traditionally expert-defined or software-derived image-derived phenotypes (IDPs) that are often based on theoretical preconceptions or computed from limited amounts of data. Here, we present an approach to derive brain imaging phenotypes using unsupervised deep representation learning. We train a 3-D convolutional autoencoder model with reconstruction loss on 6130 UK Biobank (UKBB) participants' T1 or T2-FLAIR (T2) brain MRIs to create a 128-dimensional representation known as Unsupervised Deep learning …
Estimating Heritability Explained By Local Ancestry And Evaluating Stratification Bias In Admixture Mapping From Summary Statistics, Tsz Fung Chan, Xinyue Rui, David V Conti, Myriam Fornage, Mariaelisa Graff, Jeffrey Haessler, Christopher Haiman, Heather M Highland, Su Yon Jung, Eimear E Kenny, Charles Kooperberg, Loic Le Marchand, Kari E North, Ran Tao, Genevieve Wojcik, Christopher R Gignoux, Charleston W K Chiang, Nicholas Mancuso
Estimating Heritability Explained By Local Ancestry And Evaluating Stratification Bias In Admixture Mapping From Summary Statistics, Tsz Fung Chan, Xinyue Rui, David V Conti, Myriam Fornage, Mariaelisa Graff, Jeffrey Haessler, Christopher Haiman, Heather M Highland, Su Yon Jung, Eimear E Kenny, Charles Kooperberg, Loic Le Marchand, Kari E North, Ran Tao, Genevieve Wojcik, Christopher R Gignoux, Charleston W K Chiang, Nicholas Mancuso
Faculty, Staff and Student Publications
The heritability explained by local ancestry markers in an admixed population (h
Leveraging Pleiotropy To Discover And Interpret Gwas Results For Sleep-Associated Traits, Sung Chun, Sebastian Akle, Athanasios Teodosiadis, Brian E Cade, Heming Wang, Tamar Sofer, Daniel S Evans, Katie L Stone, Sina A Gharib, Sutapa Mukherjee, Lyle J Palmer, David Hillman, Jerome I Rotter, Craig L Hanis, John A Stamatoyannopoulos, Susan Redline, Chris Cotsapas, Shamil R Sunyaev
Leveraging Pleiotropy To Discover And Interpret Gwas Results For Sleep-Associated Traits, Sung Chun, Sebastian Akle, Athanasios Teodosiadis, Brian E Cade, Heming Wang, Tamar Sofer, Daniel S Evans, Katie L Stone, Sina A Gharib, Sutapa Mukherjee, Lyle J Palmer, David Hillman, Jerome I Rotter, Craig L Hanis, John A Stamatoyannopoulos, Susan Redline, Chris Cotsapas, Shamil R Sunyaev
Faculty, Staff and Student Publications
Genetic association studies of many heritable traits resulting from physiological testing often have modest sample sizes due to the cost and burden of the required phenotyping. This reduces statistical power and limits discovery of multiple genetic associations. We present a strategy to leverage pleiotropy between traits to both discover new loci and to provide mechanistic hypotheses of the underlying pathophysiology. Specifically, we combine a colocalization test with a locus-level test of pleiotropy. In simulations, we show that this approach is highly selective for identifying true pleiotropy driven by the same causative variant, thereby improves the chance to replicate the associations …
A Framework For Detecting Noncoding Rare-Variant Associations Of Large-Scale Whole-Genome Sequencing Studies, Zilin Li, Xihao Li, Hufeng Zhou, Sheila M Gaynor, Margaret Sunitha Selvaraj, Theodore Arapoglou, Corbin Quick, Yaowu Liu, Han Chen, Ryan Sun, Rounak Dey, Donna K Arnett, Paul L Auer, Lawrence F Bielak, Joshua C Bis, Thomas W Blackwell, John Blangero, Eric Boerwinkle, Donald W Bowden, Jennifer A Brody, Brian E Cade, Matthew P Conomos, Adolfo Correa, L Adrienne Cupples, Joanne E Curran, Paul S De Vries, Ravindranath Duggirala, Nora Franceschini, Barry I Freedman, Harald H H Göring, Xiuqing Guo, Rita R Kalyani, Charles Kooperberg, Brian G Kral, Leslie A Lange, Bridget M Lin, Ani Manichaikul, Alisa K Manning, Lisa W Martin, Rasika A Mathias, James B Meigs, Braxton D Mitchell, May E Montasser, Alanna C Morrison, Take Naseri, Jeffrey R O'Connell, Nicholette D Palmer, Patricia A Peyser, Bruce M Psaty, Laura M Raffield, Susan Redline, Alexander P Reiner, Muagututi'a Sefuiva Reupena, Kenneth M Rice, Stephen S Rich, Jennifer A Smith, Kent D Taylor, Margaret A Taub, Ramachandran S Vasan, Daniel E Weeks, James G Wilson, Lisa R Yanek, Wei Zhao, Jerome I Rotter, Cristen J Willer, Pradeep Natarajan, Gina M Peloso, Xihong Lin
A Framework For Detecting Noncoding Rare-Variant Associations Of Large-Scale Whole-Genome Sequencing Studies, Zilin Li, Xihao Li, Hufeng Zhou, Sheila M Gaynor, Margaret Sunitha Selvaraj, Theodore Arapoglou, Corbin Quick, Yaowu Liu, Han Chen, Ryan Sun, Rounak Dey, Donna K Arnett, Paul L Auer, Lawrence F Bielak, Joshua C Bis, Thomas W Blackwell, John Blangero, Eric Boerwinkle, Donald W Bowden, Jennifer A Brody, Brian E Cade, Matthew P Conomos, Adolfo Correa, L Adrienne Cupples, Joanne E Curran, Paul S De Vries, Ravindranath Duggirala, Nora Franceschini, Barry I Freedman, Harald H H Göring, Xiuqing Guo, Rita R Kalyani, Charles Kooperberg, Brian G Kral, Leslie A Lange, Bridget M Lin, Ani Manichaikul, Alisa K Manning, Lisa W Martin, Rasika A Mathias, James B Meigs, Braxton D Mitchell, May E Montasser, Alanna C Morrison, Take Naseri, Jeffrey R O'Connell, Nicholette D Palmer, Patricia A Peyser, Bruce M Psaty, Laura M Raffield, Susan Redline, Alexander P Reiner, Muagututi'a Sefuiva Reupena, Kenneth M Rice, Stephen S Rich, Jennifer A Smith, Kent D Taylor, Margaret A Taub, Ramachandran S Vasan, Daniel E Weeks, James G Wilson, Lisa R Yanek, Wei Zhao, Jerome I Rotter, Cristen J Willer, Pradeep Natarajan, Gina M Peloso, Xihong Lin
Faculty, Staff and Student Publications
Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate …
A Genome-Wide Association Study Discovers 46 Loci Of The Human Metabolome In The Hispanic Community Health Study/Study Of Latinos, Elena V Feofanova, Han Chen, Yulin Dai, Peilin Jia, Megan L Grove, Alanna C Morrison, Qibin Qi, Martha Daviglus, Jianwen Cai, Kari E North, Cathy C Laurie, Robert C Kaplan, Eric Boerwinkle, Bing Yu
A Genome-Wide Association Study Discovers 46 Loci Of The Human Metabolome In The Hispanic Community Health Study/Study Of Latinos, Elena V Feofanova, Han Chen, Yulin Dai, Peilin Jia, Megan L Grove, Alanna C Morrison, Qibin Qi, Martha Daviglus, Jianwen Cai, Kari E North, Cathy C Laurie, Robert C Kaplan, Eric Boerwinkle, Bing Yu
Faculty, Staff and Student Publications
Variation in levels of the human metabolome reflect changes in homeostasis, providing a window into health and disease. The genetic impact on circulating metabolites in Hispanics, a population with high cardiometabolic disease burden, is largely unknown. We conducted genome-wide association analyses on 640 circulating metabolites in 3,926 Hispanic Community Health Study/Study of Latinos participants. The estimated heritability for 640 metabolites ranged between 0%-54% with a median at 2.5%. We discovered 46 variant-metabolite pairs (p value < 1.2 × 10