256 results on '"Daniel E. Weeks"'
Search Results
2. dbGaPCheckup: pre-submission checks of dbGaP-formatted subject phenotype files
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Lacey W. Heinsberg and Daniel E. Weeks
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Database architecture ,Data quality control ,Data sharing ,Data distribution ,Repository ,Database of genotypes and phenotypes ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Biology (General) ,QH301-705.5 - Abstract
Abstract Background Data archiving and distribution are essential to scientific rigor and reproducibility of research. The National Center for Biotechnology Information’s Database of Genotypes and Phenotypes (dbGaP) is a public repository for scientific data sharing. To support curation of thousands of complex data sets, dbGaP has detailed submission instructions that investigators must follow when archiving their data. Results We developed dbGaPCheckup, an R package which implements a series of check, awareness, reporting, and utility functions to support data integrity and proper formatting of the subject phenotype data set and data dictionary prior to dbGaP submission. For example, as a tool, dbGaPCheckup ensures that the data dictionary contains all fields required by dbGaP, and additional fields required by dbGaPCheckup; the number and names of variables match between the data set and data dictionary; there are no duplicated variable names or descriptions; observed data values are not more extreme than the logical minimum and maximum values stated in the data dictionary; and more. The package also includes functions that implement a series of minor/scalable fixes when errors are detected (e.g., a function to reorder the variables in the data dictionary to match the order listed in the data set). Finally, we also include reporting functions that produce graphical and textual descriptives of the data to further reduce the likelihood of data integrity issues. The dbGaPCheckup R package is available on CRAN ( https://CRAN.R-project.org/package=dbGaPCheckup ) and developed on GitHub ( https://github.com/lwheinsberg/dbGaPCheckup ). Conclusion dbGaPCheckup is an innovative assistive and timesaving tool that fills an important gap for researchers by making dbGaP submission of large and complex data sets less error prone.
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- 2023
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3. A longitudinal epigenome-wide association study of preeclamptic and normotensive pregnancy
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Shuwei Liu, Haoyi Fu, Mitali Ray, Lacey W. Heinsberg, Yvette P. Conley, Cindy M. Anderson, Carl A. Hubel, James M. Roberts, Arun Jeyabalan, Daniel E. Weeks, and Mandy J. Schmella
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Preeclampsia ,Pre-eclampsia ,DNA methylation ,Epigenetics ,Hypertensive disorder of pregnancy ,Surrogate variable analysis ,Genetics ,QH426-470 - Abstract
Abstract Background While preeclampsia (PE) is a leading cause of pregnancy-related morbidity/mortality, its underlying mechanisms are not fully understood. DNA methylation (DNAm) is a dynamic regulator of gene expression that may offer insight into PE pathophysiology and/or serve as a biomarker (e.g., risk, subtype, a therapeutic response). This study’s purpose was to evaluate for differences in blood-based DNAm across all trimesters between individuals eventually diagnosed with PE (cases) and individuals who remained normotensive throughout pregnancy, did not develop proteinuria, and birthed a normally grown infant (controls). Results In the discovery phase, longitudinal, genome-wide DNAm data were generated across three trimesters of pregnancy in 56 participants (n=28 cases, n=28 controls) individually matched on self-identified race, pre-pregnancy body mass index, smoking, and gestational age at sample collection. An epigenome-wide association study (EWAS) was conducted, using surrogate variable analysis to account for unwanted sources of variation. No CpGs met the genome-wide significance p value threshold of 9×10-8, but 16 CpGs (trimester 1: 5; trimester 2: 1; trimester 3: 10) met the suggestive significance threshold of 1×10-5. DNAm data were also evaluated for differentially methylated regions (DMRs) by PE status. Three DMRs in each trimester were significant after Bonferonni-adjustment. Since only third-trimester samples were available from an independent replication sample (n=64 cases, n=50 controls), the top suggestive hits from trimester 3 (cg16155413 and cg21882990 associated with TRAF3IP2-AS1/TRAF3IP2 genes, which also made up the top DMR) were carried forward for replication. During replication, DNAm data were also generated for validation purposes from discovery phase third trimester samples. While significant associations between DNAm and PE status were observed at both sites in the validation sample, no associations between DNAm and PE status were observed in the independent replication sample. Conclusions The discovery phase findings for cg16155413/cg21882990 (TRAF3IP2-AS1/TRAF3IP2) were validated with a new platform but were not replicated in an independent sample. Given the differences in participant characteristics between the discovery and replication samples, we cannot rule out important signals for these CpGs. Additional research is warranted for cg16155413/cg21882990, as well as top hits in trimesters 1–2 and significant DMRs that were not examined in the replication phase.
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- 2023
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4. Epigenome-wide DNA methylation association study of circulating IgE levels identifies novel targets for asthmaResearch in context
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Kathryn Recto, Priyadarshini Kachroo, Tianxiao Huan, David Van Den Berg, Gha Young Lee, Helena Bui, Dong Heon Lee, Jessica Gereige, Chen Yao, Shih-Jen Hwang, Roby Joehanes, Scott T. Weiss, George T. O’Connor, Daniel Levy, Dawn L. DeMeo, Namiko Abe, Gonçalo Abecasis, Francois Aguet, Christine Albert, Laura Almasy, Alvaro Alonso, Seth Ament, Peter Anderson, Pramod Anugu, Deborah Applebaum-Bowden, Kristin Ardlie, Dan Arking, Donna K. Arnett, Allison Ashley-Koch, Stella Aslibekyan, Tim Assimes, Paul Auer, Dimitrios Avramopoulos, Najib Ayas, Adithya Balasubramanian, John Barnard, Kathleen Barnes, R. Graham Barr, Emily Barron-Casella, Lucas Barwick, Terri Beaty, Gerald Beck, Diane Becker, Lewis Becker, Rebecca Beer, Amber Beitelshees, Emelia Benjamin, Takis Benos, Marcos Bezerra, Larry Bielak, Joshua Bis, Thomas Blackwell, John Blangero, Nathan Blue, Eric Boerwinkle, Donald W. Bowden, Russell Bowler, Jennifer Brody, Ulrich Broeckel, Jai Broome, Deborah Brown, Karen Bunting, Esteban Burchard, Carlos Bustamante, Erin Buth, Brian Cade, Jonathan Cardwell, Vincent Carey, Julie Carrier, April P. Carson, Cara Carty, Richard Casaburi, Juan P. Casas Romero, James Casella, Peter Castaldi, Mark Chaffin, Christy Chang, Yi-Cheng Chang, Daniel Chasman, Sameer Chavan, Bo-Juen Chen, Wei-Min Chen, Yii-Der Ida Chen, Michael Cho, Seung Hoan Choi, Lee-Ming Chuang, Mina Chung, Ren-Hua Chung, Clary Clish, Suzy Comhair, Matthew Conomos, Elaine Cornell, Adolfo Correa, Carolyn Crandall, James Crapo, L. Adrienne Cupples, Joanne Curran, Jeffrey Curtis, Brian Custer, Coleen Damcott, Dawood Darbar, Sean David, Colleen Davis, Michelle Daya, Mariza de Andrade, Lisa de las Fuentes, Paul de Vries, Michael DeBaun, Ranjan Deka, Dawn DeMeo, Scott Devine, Huyen Dinh, Harsha Doddapaneni, Qing Duan, Shannon Dugan-Perez, Ravi Duggirala, Jon Peter Durda, Susan K. Dutcher, Charles Eaton, Lynette Ekunwe, Adel El Boueiz, Patrick Ellinor, Leslie Emery, Serpil Erzurum, Charles Farber, Jesse Farek, Tasha Fingerlin, Matthew Flickinger, Myriam Fornage, Nora Franceschini, Chris Frazar, Mao Fu, Stephanie M. Fullerton, Lucinda Fulton, Stacey Gabriel, Weiniu Gan, Shanshan Gao, Yan Gao, Margery Gass, Heather Geiger, Bruce Gelb, Mark Geraci, Soren Germer, Robert Gerszten, Auyon Ghosh, Richard Gibbs, Chris Gignoux, Mark Gladwin, David Glahn, Stephanie Gogarten, Da-Wei Gong, Harald Goring, Sharon Graw, Kathryn J. Gray, Daniel Grine, Colin Gross, C. Charles Gu, Yue Guan, Xiuqing Guo, Namrata Gupta, Jeff Haessler, Michael Hall, Yi Han, Patrick Hanly, Daniel Harris, Nicola L. Hawley, Jiang He, Ben Heavner, Susan Heckbert, Ryan Hernandez, David Herrington, Craig Hersh, Bertha Hidalgo, James Hixson, Brian Hobbs, John Hokanson, Elliott Hong, Karin Hoth, Chao (Agnes) Hsiung, Jianhong Hu, Yi-Jen Hung, Haley Huston, Chii Min Hwu, Marguerite Ryan Irvin, Rebecca Jackson, Deepti Jain, Cashell Jaquish, Jill Johnsen, Andrew Johnson, Craig Johnson, Rich Johnston, Kimberly Jones, Hyun Min Kang, Robert Kaplan, Sharon Kardia, Shannon Kelly, Eimear Kenny, Michael Kessler, Alyna Khan, Ziad Khan, Wonji Kim, John Kimoff, Greg Kinney, Barbara Konkle, Charles Kooperberg, Holly Kramer, Christoph Lange, Ethan Lange, Leslie Lange, Cathy Laurie, Cecelia Laurie, Meryl LeBoff, Jiwon Lee, Sandra Lee, Wen-Jane Lee, Jonathon LeFaive, David Levine, Joshua Lewis, Xiaohui Li, Yun Li, Henry Lin, Honghuang Lin, Xihong Lin, Simin Liu, Yongmei Liu, Yu Liu, Ruth J.F. Loos, Steven Lubitz, Kathryn Lunetta, James Luo, Ulysses Magalang, Michael Mahaney, Barry Make, Ani Manichaikul, Alisa Manning, JoAnn Manson, Lisa Martin, Melissa Marton, Susan Mathai, Rasika Mathias, Susanne May, Patrick McArdle, Merry-Lynn McDonald, Sean McFarland, Stephen McGarvey, Daniel McGoldrick, Caitlin McHugh, Becky McNeil, Hao Mei, James Meigs, Vipin Menon, Luisa Mestroni, Ginger Metcalf, Deborah A. Meyers, Emmanuel Mignot, Julie Mikulla, Nancy Min, Mollie Minear, Ryan L. Minster, Braxton D. Mitchell, Matt Moll, Zeineen Momin, May E. Montasser, Courtney Montgomery, Donna Muzny, Josyf C. Mychaleckyj, Girish Nadkarni, Rakhi Naik, Take Naseri, Pradeep Natarajan, Sergei Nekhai, Sarah C. Nelson, Bonnie Neltner, Caitlin Nessner, Deborah Nickerson, Osuji Nkechinyere, Kari North, Jeff O'Connell, Tim O'Connor, Heather Ochs-Balcom, Geoffrey Okwuonu, Allan Pack, David T. Paik, Nicholette Palmer, James Pankow, George Papanicolaou, Cora Parker, Gina Peloso, Juan Manuel Peralta, Marco Perez, James Perry, Ulrike Peters, Patricia Peyser, Lawrence S. Phillips, Jacob Pleiness, Toni Pollin, Wendy Post, Julia Powers Becker, Meher Preethi Boorgula, Michael Preuss, Bruce Psaty, Pankaj Qasba, Dandi Qiao, Zhaohui Qin, Nicholas Rafaels, Laura Raffield, Mahitha Rajendran, Vasan S. Ramachandran, D.C. Rao, Laura Rasmussen-Torvik, Aakrosh Ratan, Susan Redline, Robert Reed, Catherine Reeves, Elizabeth Regan, Alex Reiner, Muagututi‘a Sefuiva Reupena, Ken Rice, Stephen Rich, Rebecca Robillard, Nicolas Robine, Dan Roden, Carolina Roselli, Jerome Rotter, Ingo Ruczinski, Alexi Runnels, Pamela Russell, Sarah Ruuska, Kathleen Ryan, Ester Cerdeira Sabino, Danish Saleheen, Shabnam Salimi, Sejal Salvi, Steven Salzberg, Kevin Sandow, Vijay G. Sankaran, Jireh Santibanez, Karen Schwander, David Schwartz, Frank Sciurba, Christine Seidman, Jonathan Seidman, Frédéric Sériès, Vivien Sheehan, Stephanie L. Sherman, Amol Shetty, Aniket Shetty, Wayne Hui-Heng Sheu, M. Benjamin Shoemaker, Brian Silver, Edwin Silverman, Robert Skomro, Albert Vernon Smith, Jennifer Smith, Josh Smith, Nicholas Smith, Tanja Smith, Sylvia Smoller, Beverly Snively, Michael Snyder, Tamar Sofer, Nona Sotoodehnia, Adrienne M. Stilp, Garrett Storm, Elizabeth Streeten, Jessica Lasky Su, Yun Ju Sung, Jody Sylvia, Adam Szpiro, Daniel Taliun, Hua Tang, Margaret Taub, Kent Taylor, Matthew Taylor, Simeon Taylor, Marilyn Telen, Timothy A. Thornton, Machiko Threlkeld, Lesley Tinker, David Tirschwell, Sarah Tishkoff, Hemant Tiwari, Catherine Tong, Russell Tracy, Michael Tsai, Dhananjay Vaidya, Peter VandeHaar, Scott Vrieze, Tarik Walker, Robert Wallace, Avram Walts, Fei Fei Wang, Heming Wang, Jiongming Wang, Karol Watson, Jennifer Watt, Daniel E. Weeks, Joshua Weinstock, Bruce Weir, Lu-Chen Weng, Jennifer Wessel, Cristen Willer, Kayleen Williams, L. Keoki Williams, Scott Williams, Carla Wilson, James Wilson, Lara Winterkorn, Quenna Wong, Baojun Wu, Joseph Wu, Huichun Xu, Lisa Yanek, Ivana Yang, Ketian Yu, Seyedeh Maryam Zekavat, Yingze Zhang, Snow Xueyan Zhao, Wei Zhao, Xiaofeng Zhu, Elad Ziv, Michael Zody, and Sebastian Zoellner
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EWAS ,DNA methylation ,IgE ,Asthma ,RNA-Sequencing ,Mendelian randomization ,Medicine ,Medicine (General) ,R5-920 - Abstract
Summary: Background: Identifying novel epigenetic signatures associated with serum immunoglobulin E (IgE) may improve our understanding of molecular mechanisms underlying asthma and IgE-mediated diseases. Methods: We performed an epigenome-wide association study using whole blood from Framingham Heart Study (FHS; n = 3,471, 46% females) participants and validated results using the Childhood Asthma Management Program (CAMP; n = 674, 39% females) and the Genetic Epidemiology of Asthma in Costa Rica Study (CRA; n = 787, 41% females). Using the closest gene to each IgE-associated CpG, we highlighted biologically plausible pathways underlying IgE regulation and analyzed the transcription patterns linked to IgE-associated CpGs (expression quantitative trait methylation loci; eQTMs). Using prior UK Biobank summary data from genome-wide association studies of asthma and allergy, we performed Mendelian randomization (MR) for causal inference testing using the IgE-associated CpGs from FHS with methylation quantitative trait loci (mQTLs) as instrumental variables. Findings: We identified 490 statistically significant differentially methylated CpGs associated with IgE in FHS, of which 193 (39.3%) replicated in CAMP and CRA (FDR < 0.05). Gene ontology analysis revealed enrichment in pathways related to transcription factor binding, asthma, and other immunological processes. eQTM analysis identified 124 cis-eQTMs for 106 expressed genes (FDR < 0.05). MR in combination with drug-target analysis revealed CTSB and USP20 as putatively causal regulators of IgE levels (Bonferroni adjusted P
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- 2023
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5. A Polynesian-specific missense CETP variant alters the lipid profile
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Jaye Moors, Mohanraj Krishnan, Nick Sumpter, Riku Takei, Matt Bixley, Murray Cadzow, Tanya J. Major, Amanda Phipps-Green, Ruth Topless, Marilyn Merriman, Malcolm Rutledge, Ben Morgan, Jenna C. Carlson, Jerry Z. Zhang, Emily M. Russell, Guangyun Sun, Hong Cheng, Daniel E. Weeks, Take Naseri, Muagututi’a Sefuiva Reupena, Satupa’itea Viali, John Tuitele, Nicola L. Hawley, Ranjan Deka, Stephen T. McGarvey, Janak de Zoysa, Rinki Murphy, Nicola Dalbeth, Lisa Stamp, Mele Taumoepeau, Frances King, Phillip Wilcox, Nuku Rapana, Sally McCormick, Ryan L. Minster, Tony R. Merriman, and Megan Leask
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CETP ,Māori ,Pacific ,Association analyses ,HDL-C ,Lipids ,Genetics ,QH426-470 - Abstract
Summary: Identifying population-specific genetic variants associated with disease and disease-predisposing traits is important to provide insights into the genetic determinants of health and disease between populations, as well as furthering genomic justice. Various common pan-population polymorphisms at CETP associate with serum lipid profiles and cardiovascular disease. Here, sequencing of CETP identified a missense variant rs1597000001 (p.Pro177Leu) specific to Māori and Pacific people that associates with higher HDL-C and lower LDL-C levels. Each copy of the minor allele associated with higher HDL-C by 0.236 mmol/L and lower LDL-C by 0.133 mmol/L. The rs1597000001 effect on HDL-C is comparable with CETP Mendelian loss-of-function mutations that result in CETP deficiency, consistent with our data, which shows that rs1597000001 lowers CETP activity by 27.9%. This study highlights the potential of population-specific genetic analyses for improving equity in genomics and health outcomes for population groups underrepresented in genomic studies.
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- 2023
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6. Whole genome sequence association analysis of fasting glucose and fasting insulin levels in diverse cohorts from the NHLBI TOPMed program
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Daniel DiCorpo, Sheila M. Gaynor, Emily M. Russell, Kenneth E. Westerman, Laura M. Raffield, Timothy D. Majarian, Peitao Wu, Chloé Sarnowski, Heather M. Highland, Anne Jackson, Natalie R. Hasbani, Paul S. de Vries, Jennifer A. Brody, Bertha Hidalgo, Xiuqing Guo, James A. Perry, Jeffrey R. O’Connell, Samantha Lent, May E. Montasser, Brian E. Cade, Deepti Jain, Heming Wang, Ricardo D’Oliveira Albanus, Arushi Varshney, Lisa R. Yanek, Leslie Lange, Nicholette D. Palmer, Marcio Almeida, Juan M. Peralta, Stella Aslibekyan, Abigail S. Baldridge, Alain G. Bertoni, Lawrence F. Bielak, Chung-Shiuan Chen, Yii-Der Ida Chen, Won Jung Choi, Mark O. Goodarzi, James S. Floyd, Marguerite R. Irvin, Rita R. Kalyani, Tanika N. Kelly, Seonwook Lee, Ching-Ti Liu, Douglas Loesch, JoAnn E. Manson, Ryan L. Minster, Take Naseri, James S. Pankow, Laura J. Rasmussen-Torvik, Alexander P. Reiner, Muagututi’a Sefuiva Reupena, Elizabeth Selvin, Jennifer A. Smith, Daniel E. Weeks, Huichun Xu, Jie Yao, Wei Zhao, Stephen Parker, Alvaro Alonso, Donna K. Arnett, John Blangero, Eric Boerwinkle, Adolfo Correa, L. Adrienne Cupples, Joanne E. Curran, Ravindranath Duggirala, Jiang He, Susan R. Heckbert, Sharon L. R. Kardia, Ryan W. Kim, Charles Kooperberg, Simin Liu, Rasika A. Mathias, Stephen T. McGarvey, Braxton D. Mitchell, Alanna C. Morrison, Patricia A. Peyser, Bruce M. Psaty, Susan Redline, Alan R. Shuldiner, Kent D. Taylor, Ramachandran S. Vasan, Karine A. Viaud-Martinez, Jose C. Florez, James G. Wilson, Robert Sladek, Stephen S. Rich, Jerome I. Rotter, Xihong Lin, Josée Dupuis, James B. Meigs, Jennifer Wessel, and Alisa K. Manning
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Biology (General) ,QH301-705.5 - Abstract
This study of 23,000 non-diabetic individuals highlights loci associated with fasting glucose and fasting insulin in diverse cohorts with whole genome sequence data.
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- 2022
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7. A stop-gain variant in BTNL9 is associated with atherogenic lipid profiles
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Jenna C. Carlson, Mohanraj Krishnan, Samantha L. Rosenthal, Emily M. Russell, Jerry Z. Zhang, Nicola L. Hawley, Jaye Moors, Hong Cheng, Nicola Dalbeth, Janak R. de Zoysa, Huti Watson, Muhammad Qasim, Rinki Murphy, Take Naseri, Muagututi’a Sefuiva Reupena, Satupa‘itea Viali, Lisa K. Stamp, John Tuitele, Erin E. Kershaw, Ranjan Deka, Stephen T. McGarvey, Tony R. Merriman, Daniel E. Weeks, and Ryan L. Minster
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identification of disease genes ,Polynesia ,cardiovascular disease risk factors ,genetics of complex traits ,isolated population ,Genetics ,QH426-470 - Abstract
Summary: Current understanding of lipid genetics has come mainly from studies in European-ancestry populations; limited effort has focused on Polynesian populations, whose unique population history and high prevalence of dyslipidemia may provide insight into the biological foundations of variation in lipid levels. Here, we performed an association study to fine map a suggestive association on 5q35 with high-density lipoprotein cholesterol (HDL-C) seen in Micronesian and Polynesian populations. Fine-mapping analyses in a cohort of 2,851 Samoan adults highlighted an association between a stop-gain variant (rs200884524; c.652C>T, p.R218∗; posterior probability = 0.9987) in BTNL9 and both lower HDL-C and greater triglycerides (TGs). Meta-analysis across this and several other cohorts of Polynesian ancestry from Samoa, American Samoa, and Aotearoa New Zealand confirmed the presence of this association (βHDL-C = −1.60 mg/dL, pHDL-C = 7.63 × 10−10; βTG = 12.00 mg/dL, pTG = 3.82 × 10−7). While this variant appears to be Polynesian specific, there is also evidence of association from other multiancestry analyses in this region. This work provides evidence of a previously unexplored contributor to the genetic architecture of lipid levels and underscores the importance of genetic analyses in understudied populations.
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- 2023
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8. An exploratory study of white blood cell proportions across preeclamptic and normotensive pregnancy by self-identified race in individuals with overweight or obesity
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Mitali Ray, Lacey W. Heinsberg, Yvette P. Conley, James M. Roberts, Arun Jeyabalan, Carl A. Hubel, Daniel E. Weeks, and Mandy J. Schmella
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preeclampsia ,white blood cell ,wbc count ,hypertension in pregnancy ,dna methylation ,Gynecology and obstetrics ,RG1-991 - Abstract
Objective: Examine white blood cell (WBC) proportions across preeclamptic (n = 28 cases) and normotensive (n = 28 controls) pregnancy in individuals with overweight/obesity. Methods: WBC proportions were inferred from genome-wide DNA methylation data and compared by case/control status and self-identified race. Results: In Trimester 1, ean B cell proportions were suggestively lower in cases in the overall sample and significantly lower in White participants but not in Black participants. More significant WBC proportion changes were observed across normotensive than preeclamptic pregnancy. Conclusions: These findings in a small sample demonstrate need for additional studies investigating the relationship between self-identified race and WBCs in pregnancy.
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- 2021
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9. Correlates of daytime sleepiness and insomnia among adults in Samoa
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Lacey W. Heinsberg, Jenna C. Carlson, Alysa Pomer, Brian E. Cade, Take Naseri, Muagututia Sefuiva Reupena, Daniel E. Weeks, Stephen T. McGarvey, Susan Redline, and Nicola L. Hawley
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Women's Health Initiative Insomnia Rating Scale (WHIIRS) ,Epworth Sleepiness Scale (ESS) ,sleep health ,Pacific Islander ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
ABSTRACT: Objective: To describe daytime sleepiness and insomnia among adults in Samoa and identify modifiable factors associated with these measures. Design/setting: Cross-sectional analysis of data from the Soifua Manuia (“Good Health”) study (n = 519, 55.1% female); Upolu island, Samoa. Methods: Daytime sleepiness and insomnia were assessed with the Epworth Sleepiness Scale (ESS) and the Women's Health Initiative Insomnia Rating Scale (WHIIRS), respectively. Detailed physical, sociodemographic, and behavioral factors were collected. Sleep measures were characterized using multiple linear regression with backwards elimination and a bootstrap stability investigation. Results: Excessive daytime sleepiness (ESS>10) and insomnia (WHIIRS>10) were reported by 20% and 6.3% of the sample, respectively. ESS scores were higher in individuals reporting more physical activity (Estimate=1.88; 95% CI=1.12 to 2.75), higher material wealth (0.18; 0.09 to 0.28), and asthma (2.85; 1.25 to 4.51). ESS scores were lower in individuals residing in periurban versus urban regions (-1.43; -2.39 to -0.41), reporting no work versus day shift work (-2.26; -3.07 to -1.41), and reporting greater perceived stress (-0.14; -0.23 to -0.06). WHIIRS scores were lower in individuals reporting “other” shift work (split/irregular/on-call/rotating) versus day shift work (-1.96; -2.89 to -1.14) and those who perceived their village's wealth to be poor/average versus wealthy (-0.94; -1.50 to -0.34). Conclusions: Participants had a generally higher prevalence of excessive daytime sleepiness, but lower prevalence of insomnia, compared with individuals from high-income countries. Factors associated with sleep health differed compared with prior studies, emphasizing potential cultural/environmental differences and the need for targeted interventions to improve sleep health in this setting.
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- 2022
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10. Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices
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Pradeep Natarajan, Akhil Pampana, Sarah E. Graham, Sanni E. Ruotsalainen, James A. Perry, Paul S. de Vries, Jai G. Broome, James P. Pirruccello, Michael C. Honigberg, Krishna Aragam, Brooke Wolford, Jennifer A. Brody, Lucinda Antonacci-Fulton, Moscati Arden, Stella Aslibekyan, Themistocles L. Assimes, Christie M. Ballantyne, Lawrence F. Bielak, Joshua C. Bis, Brian E. Cade, Ron Do, Harsha Doddapaneni, Leslie S. Emery, Yi-Jen Hung, Marguerite R. Irvin, Alyna T. Khan, Leslie Lange, Jiwon Lee, Rozenn N. Lemaitre, Lisa W. Martin, Ginger Metcalf, May E. Montasser, Jee-Young Moon, Donna Muzny, Jeffrey R. O’Connell, Nicholette D. Palmer, Juan M. Peralta, Patricia A. Peyser, Adrienne M. Stilp, Michael Tsai, Fei Fei Wang, Daniel E. Weeks, Lisa R. Yanek, James G. Wilson, Goncalo Abecasis, Donna K. Arnett, Lewis C. Becker, John Blangero, Eric Boerwinkle, Donald W. Bowden, Yi-Cheng Chang, Yii-Der I. Chen, Won Jung Choi, Adolfo Correa, Joanne E. Curran, Mark J. Daly, Susan K. Dutcher, Patrick T. Ellinor, Myriam Fornage, Barry I. Freedman, Stacey Gabriel, Soren Germer, Richard A. Gibbs, Jiang He, Kristian Hveem, Gail P. Jarvik, Robert C. Kaplan, Sharon L. R. Kardia, Eimear Kenny, Ryan W. Kim, Charles Kooperberg, Cathy C. Laurie, Seonwook Lee, Don M. Lloyd-Jones, Ruth J. F. Loos, Steven A. Lubitz, Rasika A. Mathias, Karine A. Viaud Martinez, Stephen T. McGarvey, Braxton D. Mitchell, Deborah A. Nickerson, Kari E. North, Aarno Palotie, Cheol Joo Park, Bruce M. Psaty, D. C. Rao, Susan Redline, Alexander P. Reiner, Daekwan Seo, Jeong-Sun Seo, Albert V. Smith, Russell P. Tracy, Ramachandran S. Vasan, Sekar Kathiresan, L. Adrienne Cupples, Jerome I. Rotter, Alanna C. Morrison, Stephen S. Rich, Samuli Ripatti, Cristen Willer, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, FinnGen, and Gina M. Peloso
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Science - Abstract
The influence of X chromosome genetic variation on blood lipids and coronary heart disease (CHD) is not well understood. Here, the authors analyse X chromosome sequencing data across 65,322 multi-ancestry individuals, identifying associations of the Xq23 locus with lipid changes and reduced risk of CHD and diabetes mellitus.
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- 2021
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11. Genetic determinants of telomere length from 109,122 ancestrally diverse whole-genome sequences in TOPMed
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Margaret A. Taub, Matthew P. Conomos, Rebecca Keener, Kruthika R. Iyer, Joshua S. Weinstock, Lisa R. Yanek, John Lane, Tyne W. Miller-Fleming, Jennifer A. Brody, Laura M. Raffield, Caitlin P. McHugh, Deepti Jain, Stephanie M. Gogarten, Cecelia A. Laurie, Ali Keramati, Marios Arvanitis, Albert V. Smith, Benjamin Heavner, Lucas Barwick, Lewis C. Becker, Joshua C. Bis, John Blangero, Eugene R. Bleecker, Esteban G. Burchard, Juan C. Celedón, Yen Pei C. Chang, Brian Custer, Dawood Darbar, Lisa de las Fuentes, Dawn L. DeMeo, Barry I. Freedman, Melanie E. Garrett, Mark T. Gladwin, Susan R. Heckbert, Bertha A. Hidalgo, Marguerite R. Irvin, Talat Islam, W. Craig Johnson, Stefan Kaab, Lenore Launer, Jiwon Lee, Simin Liu, Arden Moscati, Kari E. North, Patricia A. Peyser, Nicholas Rafaels, Christine Seidman, Daniel E. Weeks, Fayun Wen, Marsha M. Wheeler, L. Keoki Williams, Ivana V. Yang, Wei Zhao, Stella Aslibekyan, Paul L. Auer, Donald W. Bowden, Brian E. Cade, Zhanghua Chen, Michael H. Cho, L. Adrienne Cupples, Joanne E. Curran, Michelle Daya, Ranjan Deka, Celeste Eng, Tasha E. Fingerlin, Xiuqing Guo, Lifang Hou, Shih-Jen Hwang, Jill M. Johnsen, Eimear E. Kenny, Albert M. Levin, Chunyu Liu, Ryan L. Minster, Take Naseri, Mehdi Nouraie, Muagututi‘a Sefuiva Reupena, Ester C. Sabino, Jennifer A. Smith, Nicholas L. Smith, Jessica Lasky-Su, James G. Taylor, VI, Marilyn J. Telen, Hemant K. Tiwari, Russell P. Tracy, Marquitta J. White, Yingze Zhang, Kerri L. Wiggins, Scott T. Weiss, Ramachandran S. Vasan, Kent D. Taylor, Moritz F. Sinner, Edwin K. Silverman, M. Benjamin Shoemaker, Wayne H.-H. Sheu, Frank Sciurba, David A. Schwartz, Jerome I. Rotter, Daniel Roden, Susan Redline, Benjamin A. Raby, Bruce M. Psaty, Juan M. Peralta, Nicholette D. Palmer, Sergei Nekhai, Courtney G. Montgomery, Braxton D. Mitchell, Deborah A. Meyers, Stephen T. McGarvey, Angel C.Y. Mak, Ruth J.F. Loos, Rajesh Kumar, Charles Kooperberg, Barbara A. Konkle, Shannon Kelly, Sharon L.R. Kardia, Robert Kaplan, Jiang He, Hongsheng Gui, Frank D. Gilliland, Bruce D. Gelb, Myriam Fornage, Patrick T. Ellinor, Mariza de Andrade, Adolfo Correa, Yii-Der Ida Chen, Eric Boerwinkle, Kathleen C. Barnes, Allison E. Ashley-Koch, Donna K. Arnett, Christine Albert, Cathy C. Laurie, Goncalo Abecasis, Deborah A. Nickerson, James G. Wilson, Stephen S. Rich, Daniel Levy, Ingo Ruczinski, Abraham Aviv, Thomas W. Blackwell, Timothy Thornton, Jeff O’Connell, Nancy J. Cox, James A. Perry, Mary Armanios, Alexis Battle, Nathan Pankratz, Alexander P. Reiner, and Rasika A. Mathias
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telomeres ,telomere length genetics ,trans-population genome-wide association study ,Genetics ,QH426-470 ,Internal medicine ,RC31-1245 - Abstract
Summary: Genetic studies on telomere length are important for understanding age-related diseases. Prior GWASs for leukocyte TL have been limited to European and Asian populations. Here, we report the first sequencing-based association study for TL across ancestrally diverse individuals (European, African, Asian, and Hispanic/Latino) from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. We used whole-genome sequencing (WGS) of whole blood for variant genotype calling and the bioinformatic estimation of telomere length in n = 109,122 individuals. We identified 59 sentinel variants (p < 5 × 10−9) in 36 loci associated with telomere length, including 20 newly associated loci (13 were replicated in external datasets). There was little evidence of effect size heterogeneity across populations. Fine-mapping at OBFC1 indicated that the independent signals colocalized with cell-type-specific eQTLs for OBFC1 (STN1). Using a multi-variant gene-based approach, we identified two genes newly implicated in telomere length, DCLRE1B (SNM1B) and PARN. In PheWAS, we demonstrated that our TL polygenic trait scores (PTSs) were associated with an increased risk of cancer-related phenotypes.
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- 2022
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12. Methylation Data Processing Protocol and Comparison of Blood and Cerebral Spinal Fluid Following Aneurysmal Subarachnoid Hemorrhage
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Annie I. Arockiaraj, Dongjing Liu, John R. Shaffer, Theresa A. Koleck, Elizabeth A. Crago, Daniel E. Weeks, and Yvette P. Conley
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epigenome-wide association study ,methylation ,methylomics ,aneurysmal subarachnoid hemorrhage ,epigenetics ,Genetics ,QH426-470 - Abstract
One challenge in conducting DNA methylation-based epigenome-wide association study (EWAS) is the appropriate cleaning and quality-checking of data to minimize biases and experimental artifacts, while simultaneously retaining potential biological signals. These issues are compounded in studies that include multiple tissue types, and/or tissues for which reference data are unavailable to assist in adjusting for cell-type mixture, for example cerebral spinal fluid (CSF). For our study that evaluated blood and CSF taken from aneurysmal subarachnoid hemorrhage (aSAH) patients, we developed a protocol to clean and quality-check genome-wide methylation levels and compared the methylomic profiles of the two tissues to determine whether blood is a suitable surrogate for CSF. CSF samples were collected from 279 aSAH patients longitudinally during the first 14 days of hospitalization, and a subset of 88 of these patients also provided blood samples within the first 2 days. Quality control (QC) procedures included identification and exclusion of poor performing samples and low-quality probes, functional normalization, and correction for cell-type heterogeneity via surrogate variable analysis (SVA). Significant differences in rates of poor sample performance was observed between blood (1.1% failing QC) and CSF (9.12% failing QC; p = 0.003). Functional normalization increased the concordance of methylation values among technical replicates in both CSF and blood. SVA improved the asymptotic behavior of the test of association in a simulated EWAS under the null hypothesis. To determine the suitability of blood as a surrogate for CSF, we calculated the correlations of adjusted methylation values at each CpG between blood and CSF globally and by genomic regions. Overall, mean within-CpG correlation was low (r < 0.26), suggesting that blood is not a suitable surrogate for global methylation in CSF. However, differences in the magnitude of the correlation were observed by genomic region (CpG island, shore, shelf, open sea; p < 0.001 for all) and orientation with respect to nearby genes (3′ UTR, transcription start site, exon, body, 5′ UTR; p < 0.01 for all). In conclusion, the correlation analysis and QC pipelines indicated that DNA extracted from blood was not, overall, a suitable surrogate for DNA from CSF in aSAH methylomic studies.
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- 2020
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13. Novel caries loci in children and adults implicated by genome-wide analysis of families
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Manika Govil, Nandita Mukhopadhyay, Daniel E. Weeks, Eleanor Feingold, John R. Shaffer, Steven M. Levy, Alexandre R. Vieira, Rebecca L. Slayton, Daniel W. McNeil, Robert J. Weyant, Richard J. Crout, and Mary L. Marazita
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Dental genetics ,Dental public health ,Permanent dentition caries ,Primary dentition caries ,Non-parametric linkage ,Genome-wide linkage study ,Dentistry ,RK1-715 - Abstract
Abstract Background Dental caries is a common chronic disease among children and adults alike, posing a substantial health burden. Caries is affected by multiple genetic and environmental factors, and prior studies have found that a substantial proportion of caries susceptibility is genetically inherited. Methods To identify such genetic factors, we conducted a genome-wide linkage scan in 464 extended families with 2616 individuals from Iowa, Pennsylvania and West Virginia for three dental caries phenotypes: (1) PRIM: dichotomized as zero versus one or more affected primary teeth, (2) QTOT1: age-adjusted quantitative caries measure for both primary and permanent dentitions including pre-cavitated lesions, and (3) QTOT2: age-adjusted quantitative caries excluding pre-cavitated lesions. Genotyping was conducted for approximately 600,000 SNPs on an Illumina platform, pruned to 127,511 uncorrelated SNPs for the analyses reported here. Results Multipoint non-parametric linkage analyses generated peak LOD scores exceeding 2.0 for eight genomic regions, but no LOD scores above 3.0 were observed. The maximum LOD score for each of the three traits was 2.90 at 1q25.3 for PRIM, 2.38 at 6q25.3 for QTOT1, and 2.76 at 5q23.3 for QTOT2. Some overlap in linkage regions was observed among the phenotypes. Genes with a potential role in dental caries in the eight chromosomal regions include CACNA1E, LAMC2, ALMS1, STAMBP, GXYLT2, SLC12A2, MEGF10, TMEM181, ARID1B, and, as well as genes in several immune gene families. Our results are also concordant with previous findings from association analyses on chromosomes 11 and 19. Conclusions These multipoint linkage results provide evidence in favor of novel chromosomal regions, while also supporting earlier association findings for these data. Understanding the genetic etiology of dental caries will allow designing personalized treatment plans based on an individual’s genetic risk of disease.
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- 2018
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14. Genome-wide approach identifies a novel gene-maternal pre-pregnancy BMI interaction on preterm birth
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Xiumei Hong, Ke Hao, Hongkai Ji, Shouneng Peng, Ben Sherwood, Antonio Di Narzo, Hui-Ju Tsai, Xin Liu, Irina Burd, Guoying Wang, Yuelong Ji, Deanna Caruso, Guangyun Mao, Tami R. Bartell, Zhongyang Zhang, Colleen Pearson, Linda Heffner, Sandra Cerda, Terri H. Beaty, M. Daniele Fallin, Aviva Lee-Parritz, Barry Zuckerman, Daniel E. Weeks, and Xiaobin Wang
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Science - Abstract
Preterm birth (PTB) has high prevalence and PTB infants have greater risk for mortality. Here, Hong and colleagues perform a genome-wide gene × environment interaction analysis and find that maternalCOL24A1variants have a significant interaction with maternal pre-pregnancy obesity in increasing PTB risk.
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- 2017
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15. The Mega2R package: R tools for accessing and processing genetic data in common formats [version 2; referees: 3 approved]
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Robert V. Baron, Justin R. Stickel, and Daniel E. Weeks
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Medicine ,Science - Abstract
The standalone C++ Mega2 program has been facilitating data-reformatting for linkage and association analysis programs since 2000. Support for more analysis programs has been added over time. Currently, Mega2 converts data from several different genetic data formats (including PLINK, VCF, BCF, and IMPUTE2) into the specific data requirements for over 40 commonly-used linkage and association analysis programs (including Mendel, Merlin, Morgan, SHAPEIT, ROADTRIPS, MaCH/minimac3). Recently, Mega2 has been enhanced to use a SQLite database as an intermediate data representation. Additionally, Mega2 now stores bialleleic genotype data in a highly compressed form, like that of the GenABEL R package and the PLINK binary format. Our new Mega2R package now makes it easy to load Mega2 SQLite databases directly into R as data frames. In addition, Mega2R is memory efficient, keeping its genotype data in a compressed format, portions of which are only expanded when needed. Mega2R has functions that ease the process of applying gene-based tests by looping over genes, efficiently pulling out genotypes for variants within the desired boundaries. We have also created several more functions that illustrate how to use the data frames: these permit one to run the pedgene package to carry out gene-based association tests on family data, to run the SKAT package to carry out gene-based association tests, to output the Mega2R data as a VCF file and related files (for phenotype and family data), and to convert the data frames into GenABEL format. The Mega2R package enhances GenABEL since it supports additional input data formats (such as PLINK, VCF, and IMPUTE2) not currently supported by GenABEL. The Mega2 program and the Mega2R R package are both open source and are freely available, along with extensive documentation, from https://watson.hgen.pitt.edu/register for Mega2 and https://CRAN.R-project.org/package=Mega2R for Mega2R.
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- 2019
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16. The Mega2R package: R tools for accessing and processing genetic data in common formats [version 1; referees: 2 approved]
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Robert V. Baron, Justin R. Stickel, and Daniel E. Weeks
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Medicine ,Science - Abstract
The standalone C++ Mega2 program has been facilitating data-reformatting for linkage and association analysis programs since 2000. Support for more analysis programs has been added over time. Currently, Mega2 converts data from several different genetic data formats (including PLINK, VCF, BCF, and IMPUTE2) into the specific data requirements for over 40 commonly-used linkage and association analysis programs (including Mendel, Merlin, Morgan, SHAPEIT, ROADTRIPS, MaCH/minimac3). Recently, Mega2 has been enhanced to use a SQLite database as an intermediate data representation. Additionally, Mega2 now stores bialleleic genotype data in a highly compressed form, like that of the GenABEL R package and the PLINK binary format. Our new Mega2R package now makes it easy to load Mega2 SQLite databases directly into R as data frames. In addition, Mega2R is memory efficient, keeping its genotype data in a compressed format, portions of which are only expanded when needed. Mega2R has functions that ease the process of applying gene-based tests by looping over genes, efficiently pulling out genotypes for variants within the desired boundaries. We have also created several more functions that illustrate how to use the data frames: these permit one to run the pedgene package to carry out gene-based association tests on family data, to run the SKAT package to carry out gene-based association tests, to output the Mega2R data as a VCF file and related files (for phenotype and family data), and to convert the data frames into GenABEL format. The Mega2R package enhances GenABEL since it supports additional input data formats (such as PLINK, VCF, and IMPUTE2) not currently supported by GenABEL. The Mega2 program and the Mega2R R package are both open source and are freely available, along with extensive documentation, from https://watson.hgen.pitt.edu/register for Mega2 and https://CRAN.R-project.org/package=Mega2R for Mega2R.
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- 2018
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17. A genome-wide linkage scan identifies multiple chromosomal regions influencing serum lipid levels in the population on the Samoan islands*s⃞
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Karolina Åberg, Feng Dai, Guangyun Sun, Ember Keighley, Subba Rao Indugula, Linda Bausserman, Satupaitea Viali, John Tuitele, Ranjan Deka, Daniel E. Weeks, and Stephen T. McGarvey
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environmental effects ,genetic linkage analysis ,variance component analysis ,total cholesterol ,low density lipoprotein ,high density lipoprotein ,Biochemistry ,QD415-436 - Abstract
Abnormal lipid levels are important risk factors for cardiovascular diseases. We conducted genome-wide variance component linkage analyses to search for loci influencing total cholesterol (TC), LDL, HDL and triglyceride in families residing in American Samoa and Samoa as well as in a combined sample from the two polities. We adjusted the traits for a number of environmental covariates, such as smoking, alcohol consumption, physical activity, and material lifestyle. We found suggestive univariate linkage with log of the odds (LOD) scores > 3 for LDL on 6p21-p12 (LOD 3.13) in Samoa and on 12q21-q23 (LOD 3.07) in American Samoa. Furthermore, in American Samoa on 12q21, we detected genome-wide linkage (LODeq 3.38) to the bivariate trait TC-LDL. Telomeric of this region, on 12q24, we found suggestive bivariate linkage to TC-HDL (LODeq 3.22) in the combined study sample. In addition, we detected suggestive univariate linkage (LOD 1.9–2.93) on chromosomes 4p-q, 6p, 7q, 9q, 11q, 12q 13q, 15q, 16p, 18q, 19p, 19q and Xq23 and suggestive bivariate linkage (LODeq 2.05–2.62) on chromosomes 6p, 7q, 12p, 12q, and 19p-q. In conclusion, chromosome 6p and 12q may host promising susceptibility loci influencing lipid levels; however, the low degree of overlap between the three study samples strongly encourages further studies of the lipid-related traits.
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- 2008
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18. Stratified randomization controls better for batch effects in 450K methylation analysis: A cautionary tale
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Olive D. Buhule, Ryan L. Minster, Nicola L. Hawley, Mario eMedvedovic, Guangyun eSun, Satupaitea eViali, Ranjan eDeka, Stephen T. McGarvey, and Daniel E. Weeks
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DNA Methylation ,Obesity ,epigenetics ,Study Design ,Array data ,Batch effects ,Genetics ,QH426-470 - Abstract
Background: Batch effects in DNA methylation microarray experiments can lead to spurious results if not properly handled during the plating of samples. Methods: Two pilot studies examining the association of DNA methylation patterns across the genome with obesity in Samoan men were investigated for chip- and row-specific batch effects. For each study, the DNA of 46 obese men and 46 lean men were assayed using Illumina's Infinium HumanMethylation450 BeadChip. In the first study (Sample One), samples from obese and lean subjects were examined on separate chips. In the second study (Sample Two), the samples were balanced on the chips by lean/obese status, age group, and census region. We used methylumi, watermelon, and limma R packages, as well as ComBat, to analyze the data. Principal component analysis and linear regression were respectively employed to identify the top principal components and to test for their association with the batches and lean/obese status. To identify differentially methylated positions (DMPs) between obese and lean males at each locus, we used a moderated t-test.Results: Chip effects were effectively removed from Sample Two but not Sample One. In addition, dramatic differences were observed between the two sets of DMP results. After removing'' batch effects with ComBat, Sample One had 94,191 probes differentially methylated at a q-value threshold of 0.05 while Sample Two had zero differentially methylated probes. The disparate results from Sample One and Sample Two likely arise due to the confounding of lean/obese status with chip and row batch effects.Conclusion: Even the best possible statistical adjustments for batch effects may not completely remove them. Proper study design is vital for guarding against spurious findings due to such effects.
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- 2014
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19. Rare Variants in Genes Encoding Subunits of the Epithelial Na
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Brandon M, Blobner, Annet, Kirabo, Ossama B, Kashlan, Shaohu, Sheng, Donna K, Arnett, Lewis C, Becker, Eric, Boerwinkle, Jenna C, Carlson, Yan, Gao, Richard A, Gibbs, Jiang, He, Marguerite R, Irvin, Sharon L R, Kardia, Tanika N, Kelly, Charles, Kooperberg, Stephen T, McGarvey, Vipin K, Menon, May E, Montasser, Take, Naseri, Susan, Redline, Alexander P, Reiner, Muagututi'a S, Reupena, Jennifer A, Smith, Xiao, Sun, Dhananjay, Vaidya, Karine A, Viaud-Martinez, Daniel E, Weeks, Lisa R, Yanek, Xiaofeng, Zhu, Ryan L, Minster, and Thomas R, Kleyman
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Phenotype ,Sodium ,Humans ,Blood Pressure ,Epithelial Sodium Channels ,Kidney - Abstract
The epithelial NaWe explored the association of low frequency and rare variants in the genes encoding ENaC subunits, with systolic blood pressure, diastolic blood pressure, mean arterial pressure, and pulse pressure. Using whole-genome sequencing data from 14 studies participating in the Trans-Omics in Precision Medicine Whole-Genome Sequencing Program, and sequence kernel association tests.We found that variants inOur results suggest that variants in extrarenal ENaCs, in addition to ENaCs expressed in kidneys, influence blood pressure and kidney function.
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- 2023
20. Multi-ancestry transcriptome-wide association analyses yield insights into tobacco use biology and drug repurposing
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Fang Chen, Xingyan Wang, Seon-Kyeong Jang, Bryan C. Quach, J. Dylan Weissenkampen, Chachrit Khunsriraksakul, Lina Yang, Renan Sauteraud, Christine M. Albert, Nicholette D. D. Allred, Donna K. Arnett, Allison E. Ashley-Koch, Kathleen C. Barnes, R. Graham Barr, Diane M. Becker, Lawrence F. Bielak, Joshua C. Bis, John Blangero, Meher Preethi Boorgula, Daniel I. Chasman, Sameer Chavan, Yii-Der I. Chen, Lee-Ming Chuang, Adolfo Correa, Joanne E. Curran, Sean P. David, Lisa de las Fuentes, Ranjan Deka, Ravindranath Duggirala, Jessica D. Faul, Melanie E. Garrett, Sina A. Gharib, Xiuqing Guo, Michael E. Hall, Nicola L. Hawley, Jiang He, Brian D. Hobbs, John E. Hokanson, Chao A. Hsiung, Shih-Jen Hwang, Thomas M. Hyde, Marguerite R. Irvin, Andrew E. Jaffe, Eric O. Johnson, Robert Kaplan, Sharon L. R. Kardia, Joel D. Kaufman, Tanika N. Kelly, Joel E. Kleinman, Charles Kooperberg, I-Te Lee, Daniel Levy, Sharon M. Lutz, Ani W. Manichaikul, Lisa W. Martin, Olivia Marx, Stephen T. McGarvey, Ryan L. Minster, Matthew Moll, Karine A. Moussa, Take Naseri, Kari E. North, Elizabeth C. Oelsner, Juan M. Peralta, Patricia A. Peyser, Bruce M. Psaty, Nicholas Rafaels, Laura M. Raffield, Muagututi’a Sefuiva Reupena, Stephen S. Rich, Jerome I. Rotter, David A. Schwartz, Aladdin H. Shadyab, Wayne H-H. Sheu, Mario Sims, Jennifer A. Smith, Xiao Sun, Kent D. Taylor, Marilyn J. Telen, Harold Watson, Daniel E. Weeks, David R. Weir, Lisa R. Yanek, Kendra A. Young, Kristin L. Young, Wei Zhao, Dana B. Hancock, Bibo Jiang, Scott Vrieze, and Dajiang J. Liu
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Tobacco Smoke and Health ,Human Genome ,Drug Repositioning ,Single Nucleotide ,Biological Sciences ,Medical and Health Sciences ,Brain Disorders ,Tobacco Use ,Substance Misuse ,Good Health and Well Being ,Tobacco ,Genetics ,Humans ,Genetic Predisposition to Disease ,Polymorphism ,Transcriptome ,Drug Abuse (NIDA only) ,Biology ,Genome-Wide Association Study ,Developmental Biology - Abstract
Most transcriptome-wide association studies (TWASs) so far focus on European ancestry and lack diversity. To overcome this limitation, we aggregated genome-wide association study (GWAS) summary statistics, whole-genome sequences and expression quantitative trait locus (eQTL) data from diverse ancestries. We developed a new approach, TESLA (multi-ancestry integrative study using an optimal linear combination of association statistics), to integrate an eQTL dataset with a multi-ancestry GWAS. By exploiting shared phenotypic effects between ancestries and accommodating potential effect heterogeneities, TESLA improves power over other TWAS methods. When applied to tobacco use phenotypes, TESLA identified 273 new genes, up to 55% more compared with alternative TWAS methods. These hits and subsequent fine mapping using TESLA point to target genes with biological relevance. In silico drug-repurposing analyses highlight several drugs with known efficacy, including dextromethorphan and galantamine, and new drugs such as muscle relaxants that may be repurposed for treating nicotine addiction.
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- 2023
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21. The protective effect of rs373863828 on type 2 diabetes does not operate through a body composition pathway in adult Samoans
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Nicola L. Hawley, Rachel L. Duckham, Jenna C. Carlson, Take Naseri, Muagututia Sefuiva Reupena, Viali Lameko, Alysa Pomer, Abigail Wetzel, Melania Selu, Vaimoana Lupematisila, Folla Unasa, Lupesina Vesi, Tracy Fatu, Seipepa Unasa, Kima Faasalele‐Savusa, Anna C. Rivara, Emily Russell, James P. Delany, Satupaitea Viali, Erin E. Kershaw, Ryan L. Minster, Daniel E. Weeks, and Stephen T. McGarvey
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Adult ,Male ,Native Hawaiian or Other Pacific Islander ,Nutrition and Dietetics ,Endocrinology, Diabetes and Metabolism ,Medicine (miscellaneous) ,Body Mass Index ,Absorptiometry, Photon ,Glucose ,Endocrinology ,Diabetes Mellitus, Type 2 ,Body Composition ,Humans ,Female ,Obesity - Abstract
The aim of this study was to understand whether the paradoxical association of missense variant rs373863828 in CREB3 regulatory factor (CREBRF) with higher BMI but lower odds of diabetes is explained by either metabolically favorable body fat distribution or greater fat-free mass.This study explored the association of the minor allele with dual-energy x-ray absorptiometry-derived body composition in n = 421 Samoans and used path analysis to examine the mediating role of fat and fat-free mass on the relationship between rs373863828 and fasting glucose.Among females, the rs373863828 minor A allele was associated with greater BMI. There was no association of genotype with percent body fat, visceral adiposity, or fat distribution in either sex. In both females and males, lean mass was greater with each A allele: 2.16 kg/copy (p = 0.0001) and 1.73 kg/copy (p = 0.02), respectively. Path analysis showed a direct negative effect of rs373863828 genotype on fasting glucose (p = 0.004) consistent with previous findings, but also an indirect positive effect on fasting glucose operating through fat-free mass (p = 0.027).The protective effect of rs373863828 in CREBRF, common among Pacific Islanders, on type 2 diabetes does not operate through body composition. Rather, the variant's effects on body size/composition and fasting glucose likely operate via different, tissue-specific mechanisms.
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- 2022
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22. Insights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension
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Tanika N, Kelly, Xiao, Sun, Karen Y, He, Michael R, Brown, Sarah A Gagliano, Taliun, Jacklyn N, Hellwege, Marguerite R, Irvin, Xuenan, Mi, Jennifer A, Brody, Nora, Franceschini, Xiuqing, Guo, Shih-Jen, Hwang, Paul S, de Vries, Yan, Gao, Arden, Moscati, Girish N, Nadkarni, Lisa R, Yanek, Tali, Elfassy, Jennifer A, Smith, Ren-Hua, Chung, Amber L, Beitelshees, Amit, Patki, Stella, Aslibekyan, Brandon M, Blobner, Juan M, Peralta, Themistocles L, Assimes, Walter R, Palmas, Chunyu, Liu, Adam P, Bress, Zhijie, Huang, Lewis C, Becker, Chii-Min, Hwa, Jeffrey R, O'Connell, Jenna C, Carlson, Helen R, Warren, Sayantan, Das, Ayush, Giri, Lisa W, Martin, W, Craig Johnson, Ervin R, Fox, Erwin P, Bottinger, Alexander C, Razavi, Dhananjay, Vaidya, Lee-Ming, Chuang, Yen-Pei C, Chang, Take, Naseri, Deepti, Jain, Hyun Min, Kang, Adriana M, Hung, Vinodh, Srinivasasainagendra, Beverly M, Snively, Dongfeng, Gu, May E, Montasser, Muagututi'a Sefuiva, Reupena, Benjamin D, Heavner, Jonathon, LeFaive, James E, Hixson, Kenneth M, Rice, Fei Fei, Wang, Jonas B, Nielsen, Jianfeng, Huang, Alyna T, Khan, Wei, Zhou, Jovia L, Nierenberg, Cathy C, Laurie, Nicole D, Armstrong, Mengyao, Shi, Yang, Pan, Adrienne M, Stilp, Leslie, Emery, Quenna, Wong, Nicola L, Hawley, Ryan L, Minster, Joanne E, Curran, Patricia B, Munroe, Daniel E, Weeks, Kari E, North, Russell P, Tracy, Eimear E, Kenny, Daichi, Shimbo, Aravinda, Chakravarti, Stephen S, Rich, Alex P, Reiner, John, Blangero, Susan, Redline, Braxton D, Mitchell, Dabeeru C, Rao, Yii-Der, Ida Chen, Sharon L R, Kardia, Robert C, Kaplan, Rasika A, Mathias, Jiang, He, Bruce M, Psaty, Myriam, Fornage, Ruth J F, Loos, Adolfo, Correa, Eric, Boerwinkle, Jerome I, Rotter, Charles, Kooperberg, Todd L, Edwards, Gonçalo R, Abecasis, Xiaofeng, Zhu, Daniel, Levy, Donna K, Arnett, and Alanna C, Morrison
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Hypertension ,Internal Medicine ,Humans ,Blood Pressure ,Genomics ,Precision Medicine ,Polymorphism, Single Nucleotide ,Genome-Wide Association Study - Abstract
Background: The availability of whole-genome sequencing data in large studies has enabled the assessment of coding and noncoding variants across the allele frequency spectrum for their associations with blood pressure. Methods: We conducted a multiancestry whole-genome sequencing analysis of blood pressure among 51 456 Trans-Omics for Precision Medicine and Centers for Common Disease Genomics program participants (stage-1). Stage-2 analyses leveraged array data from UK Biobank (N=383 145), Million Veteran Program (N=318 891), and Reasons for Geographic and Racial Differences in Stroke (N=10 643) participants, along with whole-exome sequencing data from UK Biobank (N=199 631) participants. Results: Two blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings ( P -8 ). Among them, a rare intergenic variant at novel locus, LOC100506274 , was associated with lower systolic blood pressure in stage-1 (beta [SE]=−32.6 [6.0]; P =4.99×10 -8 ) but not stage-2 analysis ( P =0.11). Furthermore, a novel common variant at the known INSR locus was suggestively associated with diastolic blood pressure in stage-1 (beta [SE]=−0.36 [0.07]; P =4.18×10 -7 ) and attained genome-wide significance in stage-2 (beta [SE]=−0.29 [0.03]; P =7.28×10 -23 ). Nineteen additional signals suggestively associated with blood pressure in meta-analysis of single and aggregate rare variant findings ( P -6 and P -4 , respectively). Discussion: We report one promising but unconfirmed rare variant for blood pressure and, more importantly, contribute insights for future blood pressure sequencing studies. Our findings suggest promise of aggregate analyses to complement single variant analysis strategies and the need for larger, diverse samples, and family studies to enable robust rare variant identification.
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- 2023
23. The Mega2R package: R tools for accessing and processing genetic data in common formats [version 1; referees: 3 approved]
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Robert V. Baron, Justin R. Stickel, and Daniel E. Weeks
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Software Tool Article ,Articles ,database ,genotypes ,genome-wide association studies ,linkage ,Mega2 ,phenotypes ,R ,SQLite ,gene-based association tests - Abstract
The standalone C++ Mega2 program has been facilitating data-reformatting for linkage and association analysis programs since 2000. Support for more analysis programs has been added over time. Currently, Mega2 converts data from several different genetic data formats (including PLINK, VCF, BCF, and IMPUTE2) into the specific data requirements for over 40 commonly-used linkage and association analysis programs (including Mendel, Merlin, Morgan, SHAPEIT, ROADTRIPS, MaCH/minimac3). Recently, Mega2 has been enhanced to use a SQLite database as an intermediate data representation. Additionally, Mega2 now stores bialleleic genotype data in a highly compressed form, like that of the GenABEL R package and the PLINK binary format. Our new Mega2R package now makes it easy to load Mega2 SQLite databases directly into R as data frames. In addition, Mega2R is memory efficient, keeping its genotype data in a compressed format, portions of which are only expanded when needed. Mega2R has functions that ease the process of applying gene-based tests by looping over genes, efficiently pulling out genotypes for variants within the desired boundaries. We have also created several more functions that illustrate how to use the data frames: these permit one to run the pedgene package to carry out gene-based association tests on family data, to run the SKAT package to carry out gene-based association tests, to output the Mega2R data as a VCF file and related files (for phenotype and family data), and to convert the data frames into GenABEL format. The Mega2R package enhances GenABEL since it supports additional input data formats (such as PLINK, VCF, and IMPUTE2) not currently supported by GenABEL. The Mega2 program and the Mega2R R package are both open source and are freely available, along with extensive documentation, from https://watson.hgen.pitt.edu/register for Mega2 and https://CRAN.R-project.org/package=Mega2R for Mega2R.
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- 2018
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24. Whole Genome Sequence Analysis of the Plasma Proteome in Black Adults Provides Novel Insights Into Cardiovascular Disease
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Daniel H. Katz, Usman A. Tahir, Alexander G. Bick, Akhil Pampana, Debby Ngo, Mark D. Benson, Zhi Yu, Jeremy M. Robbins, Zsu-Zsu Chen, Daniel E. Cruz, Shuliang Deng, Laurie Farrell, Sumita Sinha, Alec A. Schmaier, Dongxiao Shen, Yan Gao, Michael E. Hall, Adolfo Correa, Russell P. Tracy, Peter Durda, Kent D. Taylor, Yongmei Liu, W. Craig Johnson, Xiuqing Guo, Jie Yao, Yii-Der Ida Chen, Ani W. Manichaikul, Deepti Jain, Claude Bouchard, Mark A. Sarzynski, Stephen S. Rich, Jerome I. Rotter, Thomas J. Wang, James G. Wilson, Pradeep Natarajan, Robert E. Gerszten, Namiko Abe, Gonçalo Abecasis, Francois Aguet, Christine Albert, Laura Almasy, Alvaro Alonso, Seth Ament, Peter Anderson, Pramod Anugu, Deborah Applebaum-Bowden, Kristin Ardlie, Dan Arking, Donna K. Arnett, Allison Ashley-Koch, Stella Aslibekyan, Tim Assimes, Paul Auer, Dimitrios Avramopoulos, Najib Ayas, Adithya Balasubramanian, John Barnard, Kathleen Barnes, R. Graham Barr, Emily Barron-Casella, Lucas Barwick, Terri Beaty, Gerald Beck, Diane Becker, Lewis Becker, Rebecca Beer, Amber Beitelshees, Emelia Benjamin, Takis Benos, Marcos Bezerra, Larry Bielak, Joshua Bis, Thomas Blackwell, John Blangero, Eric Boerwinkle, Donald W. Bowden, Russell Bowler, Jennifer Brody, Ulrich Broeckel, Jai Broome, Deborah Brown, Karen Bunting, Esteban Burchard, Carlos Bustamante, Erin Buth, Brian Cade, Jonathan Cardwell, Vincent Carey, Julie Carrier, April Carson, Cara Carty, Richard Casaburi, Juan P. Casas Romero, James Casella, Peter Castaldi, Mark Chaffin, Christy Chang, Yi-Cheng Chang, Daniel Chasman, Sameer Chavan, Bo-Juen Chen, Wei-Min Chen, Michael Cho, Seung Hoan Choi, Lee-Ming Chuang, Mina Chung, Ren-Hua Chung, Clary Clish, Suzy Comhair, Matthew Conomos, Elaine Cornell, Carolyn Crandall, James Crapo, L. Adrienne Cupples, Joanne Curran, Jeffrey Curtis, Brian Custer, Coleen Damcott, Dawood Darbar, Sean David, Colleen Davis, Michelle Daya, Mariza de Andrade, Lisa de las Fuentes, Paul de Vries, Michael DeBaun, Ranjan Deka, Dawn DeMeo, Scott Devine, Huyen Dinh, Harsha Doddapaneni, Qing Duan, Shannon Dugan-Perez, Ravi Duggirala, Jon Peter Durda, Susan K. Dutcher, Charles Eaton, Lynette Ekunwe, Adel El Boueiz, Patrick Ellinor, Leslie Emery, Serpil Erzurum, Charles Farber, Jesse Farek, Tasha Fingerlin, Matthew Flickinger, Myriam Fornage, Nora Franceschini, Chris Frazar, Mao Fu, Stephanie M. Fullerton, Lucinda Fulton, Stacey Gabriel, Weiniu Gan, Shanshan Gao, Margery Gass, Heather Geiger, Bruce Gelb, Mark Geraci, Soren Germer, Robert Gerszten, Auyon Ghosh, Richard Gibbs, Chris Gignoux, Mark Gladwin, David Glahn, Stephanie Gogarten, Da-Wei Gong, Harald Goring, Sharon Graw, Kathryn J. Gray, Daniel Grine, Colin Gross, C. Charles Gu, Yue Guan, Namrata Gupta, David M. Haas, Jeff Haessler, Michael Hall, Yi Han, Patrick Hanly, Daniel Harris, Nicola L. Hawley, Jiang He, Ben Heavner, Susan Heckbert, Ryan Hernandez, David Herrington, Craig Hersh, Bertha Hidalgo, James Hixson, Brian Hobbs, John Hokanson, Elliott Hong, Karin Hoth, Chao (Agnes) Hsiung, Jianhong Hu, Yi-Jen Hung, Haley Huston, Chii Min Hwu, Marguerite Ryan Irvin, Rebecca Jackson, Cashell Jaquish, Jill Johnsen, Andrew Johnson, Craig Johnson, Rich Johnston, Kimberly Jones, Hyun Min Kang, Robert Kaplan, Sharon Kardia, Shannon Kelly, Eimear Kenny, Michael Kessler, Alyna Khan, Ziad Khan, Wonji Kim, John Kimoff, Greg Kinney, Barbara Konkle, Charles Kooperberg, Holly Kramer, Christoph Lange, Ethan Lange, Leslie Lange, Cathy Laurie, Cecelia Laurie, Meryl LeBoff, Jiwon Lee, Sandra Lee, Wen-Jane Lee, Jonathon LeFaive, David Levine, Dan Levy, Joshua Lewis, Xiaohui Li, Yun Li, Henry Lin, Honghuang Lin, Xihong Lin, Simin Liu, Yu Liu, Ruth J.F. Loos, Steven Lubitz, Kathryn Lunetta, James Luo, Ulysses Magalang, Michael Mahaney, Barry Make, Ani Manichaikul, Alisa Manning, JoAnn Manson, Lisa Martin, Melissa Marton, Susan Mathai, Rasika Mathias, Susanne May, Patrick McArdle, Merry-Lynn McDonald, Sean McFarland, Stephen McGarvey, Daniel McGoldrick, Caitlin McHugh, Becky McNeil, Hao Mei, James Meigs, Vipin Menon, Luisa Mestroni, Ginger Metcalf, Deborah A. Meyers, Emmanuel Mignot, Julie Mikulla, Nancy Min, Mollie Minear, Ryan L. Minster, Braxton D. Mitchell, Matt Moll, Zeineen Momin, May E. Montasser, Courtney Montgomery, Donna Muzny, Josyf C. Mychaleckyj, Girish Nadkarni, Rakhi Naik, Take Naseri, Sergei Nekhai, Sarah C. Nelson, Bonnie Neltner, Caitlin Nessner, Deborah Nickerson, Osuji Nkechinyere, Kari North, Jeff O’Connell, Tim O’Connor, Heather Ochs-Balcom, Geoffrey Okwuonu, Allan Pack, David T. Paik, Nicholette Palmer, James Pankow, George Papanicolaou, Cora Parker, Gina Peloso, Juan Manuel Peralta, Marco Perez, James Perry, Ulrike Peters, Patricia Peyser, Lawrence S. Phillips, Jacob Pleiness, Toni Pollin, Wendy Post, Julia Powers Becker, Meher Preethi Boorgula, Michael Preuss, Bruce Psaty, Pankaj Qasba, Dandi Qiao, Zhaohui Qin, Nicholas Rafaels, Laura Raffield, Mahitha Rajendran, Vasan S. Ramachandran, D.C. Rao, Laura Rasmussen-Torvik, Aakrosh Ratan, Susan Redline, Robert Reed, Catherine Reeves, Elizabeth Regan, Alex Reiner, Muagututi’a Sefuiva Reupena, Ken Rice, Stephen Rich, Rebecca Robillard, Nicolas Robine, Dan Roden, Carolina Roselli, Jerome Rotter, Ingo Ruczinski, Alexi Runnels, Pamela Russell, Sarah Ruuska, Kathleen Ryan, Ester Cerdeira Sabino, Danish Saleheen, Shabnam Salimi, Sejal Salvi, Steven Salzberg, Kevin Sandow, Vijay G. Sankaran, Jireh Santibanez, Karen Schwander, David Schwartz, Frank Sciurba, Christine Seidman, Jonathan Seidman, Frédéric Sériès, Vivien Sheehan, Stephanie L. Sherman, Amol Shetty, Aniket Shetty, Wayne Hui-Heng Sheu, M. Benjamin Shoemaker, Brian Silver, Edwin Silverman, Robert Skomro, Albert Vernon Smith, Jennifer Smith, Josh Smith, Nicholas Smith, Tanja Smith, Sylvia Smoller, Beverly Snively, Michael Snyder, Tamar Sofer, Nona Sotoodehnia, Adrienne M. Stilp, Garrett Storm, Elizabeth Streeten, Jessica Lasky Su, Yun Ju Sung, Jody Sylvia, Adam Szpiro, Daniel Taliun, Hua Tang, Margaret Taub, Matthew Taylor, Simeon Taylor, Marilyn Telen, Timothy A. Thornton, Machiko Threlkeld, Lesley Tinker, David Tirschwell, Sarah Tishkoff, Hemant Tiwari, Catherine Tong, Russell Tracy, Michael Tsai, Dhananjay Vaidya, David Van Den Berg, Peter VandeHaar, Scott Vrieze, Tarik Walker, Robert Wallace, Avram Walts, Fei Fei Wang, Heming Wang, Jiongming Wang, Karol Watson, Jennifer Watt, Daniel E. Weeks, Joshua Weinstock, Bruce Weir, Scott T. Weiss, Lu-Chen Weng, Jennifer Wessel, Cristen Willer, Kayleen Williams, L. Keoki Williams, Carla Wilson, James Wilson, Lara Winterkorn, Quenna Wong, Joseph Wu, Huichun Xu, Lisa Yanek, Ivana Yang, Ketian Yu, Seyedeh Maryam Zekavat, Yingze Zhang, Snow Xueyan Zhao, Wei Zhao, Xiaofeng Zhu, Michael Zody, and Sebastian Zoellner
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Adult ,Male ,Proteomics ,Aging ,Whole genome sequence analysis ,Proteome ,Clinical Sciences ,Black People ,Disease ,Computational biology ,race and ethnicity ,Cardiorespiratory Medicine and Haematology ,Cardiovascular ,Article ,proteomics ,cardiovascular disease ,Physiology (medical) ,Genetics ,2.1 Biological and endogenous factors ,Humans ,Medicine ,Aetiology ,Lung ,Heart Disease - Coronary Heart Disease ,and Blood Institute TOPMed (Trans-Omics for Precision Medicine) Consortium† ,business.industry ,Prevention ,Human Genome ,National Heart ,Genomics ,Blood proteins ,Genetic architecture ,Heart Disease ,Good Health and Well Being ,Cardiovascular System & Hematology ,Cardiovascular Diseases ,Public Health and Health Services ,Female ,Cardiology and Cardiovascular Medicine ,business ,Biotechnology ,Genome-Wide Association Study - Abstract
Background: Plasma proteins are critical mediators of cardiovascular processes and are the targets of many drugs. Previous efforts to characterize the genetic architecture of the plasma proteome have been limited by a focus on individuals of European descent and leveraged genotyping arrays and imputation. Here we describe whole genome sequence analysis of the plasma proteome in individuals with greater African ancestry, increasing our power to identify novel genetic determinants. Methods: Proteomic profiling of 1301 proteins was performed in 1852 Black adults from the Jackson Heart Study using aptamer-based proteomics (SomaScan). Whole genome sequencing association analysis was ascertained for all variants with minor allele count ≥5. Results were validated using an alternative, antibody-based, proteomic platform (Olink) as well as replicated in the Multi-Ethnic Study of Atherosclerosis and the HERITAGE Family Study (Health, Risk Factors, Exercise Training and Genetics). Results: We identify 569 genetic associations between 479 proteins and 438 unique genetic regions at a Bonferroni-adjusted significance level of 3.8×10 -11 . These associations include 114 novel locus-protein relationships and an additional 217 novel sentinel variant-protein relationships. Novel cardiovascular findings include new protein associations at the APOE gene locus including ZAP70 (sentinel single nucleotide polymorphism [SNP] rs7412-T, β=0.61±0.05, P =3.27×10 -30 ) and MMP-3 (β=-0.60±0.05, P =1.67×10 -32 ), as well as a completely novel pleiotropic locus at the HPX gene, associated with 9 proteins. Further, the associations suggest new mechanisms of genetically mediated cardiovascular disease linked to African ancestry; we identify a novel association between variants linked to APOL1-associated chronic kidney and heart disease and the protein CKAP2 (rs73885319-G, β=0.34±0.04, P =1.34×10 -17 ) as well as an association between ATTR amyloidosis and RBP4 levels in community-dwelling individuals without heart failure. Conclusions: Taken together, these results provide evidence for the functional importance of variants in non-European populations, and suggest new biological mechanisms for ancestry-specific determinants of lipids, coagulation, and myocardial function.
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- 2022
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25. Association of rs9939609 in FTO with BMI among Polynesian peoples living in Aotearoa New Zealand and other Pacific nations
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Mohanraj Krishnan, Amanda Phipps-Green, Emily M. Russell, Tanya J. Major, Murray Cadzow, Lisa K. Stamp, Nicola Dalbeth, Jennie Harré Hindmarsh, Muhammad Qasim, Huti Watson, Shuwei Liu, Jenna C. Carlson, Ryan L. Minster, Nicola L. Hawley, Take Naseri, Muagututi’a Sefuiva Reupena, Ranjan Deka, Stephen T. McGarvey, Tony R. Merriman, Rinki Murphy, and Daniel E. Weeks
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Genetics ,Genetics (clinical) - Published
- 2023
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26. CHIT: an allele-specific method for testing the association between molecular quantitative traits and phenotype–genotype interaction
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Daniel E. Weeks, Juan C. Celedón, Qi Yan, Erick Forno, and Wei Chen
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Statistics and Probability ,Haplotype ,Single-nucleotide polymorphism ,Computational biology ,Quantitative trait locus ,Biology ,Original Papers ,Biochemistry ,Computer Science Applications ,Computational Mathematics ,Genotype-phenotype distinction ,Computational Theory and Mathematics ,Expression quantitative trait loci ,Linear regression ,Molecular Biology ,Type I and type II errors ,Genetic association - Abstract
Motivation Allele-specific differences in molecular traits can be obtained from next-generation sequencing data and could potentially improve testing power, but such information is usually overlooked in association studies. Furthermore, the variation of molecular quantitative traits (e.g. gene expression) could result from the interaction effect of genotypes and phenotypes, but it is challenging to identify such interaction signals in complex disease studies in humans due to small genetic effect sizes and/or small sample sizes. Results We develop a novel statistical method, the combined haplotype interaction test (CHIT), which tests for association between molecular quantitative traits and phenotype–genotype interactions by modeling the total read counts and allele-specific reads in a target region. CHIT can be used as a supplementary analysis to the regular linear interaction regression. In our simulations, CHIT obtains non-inflated type I error rates, and it has higher power than a standard interaction quantitative trait locus approach based on linear regression models. Finally, we illustrate CHIT by testing associations between gene expression obtained by RNA-seq and the interaction of SNPs and atopy status from a study of childhood asthma in Puerto Ricans, and results demonstrate that CHIT could be more powerful than a standard linear interaction expression quantitative trait loci approach. Availability and implementation The CHIT algorithm has been implemented in Python. The source code and documentation are available and can be downloaded from https://github.com/QiYanPitt/CHIT. Supplementary information Supplementary data are available at Bioinformatics online.
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- 2021
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27. Acute Brain-Derived Neurotrophic Factor DNA Methylation Trajectories in Cerebrospinal Fluid and Associations With Outcomes Following Severe Traumatic Brain Injury in Adults
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Sue R. Beers, Amery Treble-Barna, John R. Shaffer, Lacey W. Heinsberg, David O. Okonkwo, Yvette P. Conley, Daniel E. Weeks, and Ava M. Puccio
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Brain-derived neurotrophic factor ,Epigenetic biomarkers ,0303 health sciences ,Traumatic brain injury ,business.industry ,General Medicine ,medicine.disease ,Bioinformatics ,03 medical and health sciences ,0302 clinical medicine ,Cerebrospinal fluid ,DNA methylation ,medicine ,Epigenetics ,business ,030217 neurology & neurosurgery ,030304 developmental biology - Abstract
Background. Epigenetic biomarkers have the potential to explain outcome heterogeneity following traumatic brain injury (TBI) but are largely unexplored. Objective. This exploratory pilot study characterized brain-derived neurotrophic factor ( BDNF) DNA methylation trajectories following severe TBI. Methods. Brain-derived neurotrophic factor DNA methylation trajectories in cerebrospinal fluid (CSF) over the first 5 days following severe TBI in 112 adults were examined in association with 3- and 12-month outcomes. Results. Group-based trajectory analysis revealed low and high DNA methylation groups at two BDNF cytosine-phosphate-guanine (CpG) targets that showed suggestive associations ( P < .05) with outcomes. Membership in the high DNA methylation groups was associated with better outcomes after controlling for age, sex, and injury severity. Associations of age × trajectory group interactions with outcomes at a third CpG site revealed a pattern of the same or better outcomes with higher ages in the high DNA methylation group and worse outcomes with higher ages in the low DNA methylation group. Conclusions. Although no observed associations met the empirical significance threshold after correcting for multiple comparisons, suggestive associations of the main effect models were consistent in their direction of effect and were observed across two CpG sites and two outcome time points. Results suggest that higher acute CSF BDNF DNA methylation may promote recovery following severe TBI in adults, and this effect may be more robust with higher age. While the results require replication in larger and racially diverse independent samples, BDNF DNA methylation may serve as an early postinjury biomarker helping to explain outcome heterogeneity following TBI.
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- 2021
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28. An Exploratory Study of Epigenetic Age in Preeclamptic and Normotensive Pregnancy Reveals Differences by Self-Reported Race but Not Pregnancy Outcome
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James M. Roberts, Carl A. Hubel, Yvette P. Conley, Lacey W. Heinsberg, Daniel E. Weeks, Arun Jeyabalan, Mandy J. Schmella, and Mitali Ray
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Adult ,0301 basic medicine ,medicine.medical_specialty ,Adolescent ,Reproductive medicine ,Physiology ,Article ,Epigenesis, Genetic ,Preeclampsia ,Correlation ,Young Adult ,03 medical and health sciences ,Race (biology) ,0302 clinical medicine ,Pre-Eclampsia ,Pregnancy ,medicine ,Humans ,Longitudinal Studies ,Prospective Studies ,Epigenetics ,030219 obstetrics & reproductive medicine ,business.industry ,Racial Groups ,Age Factors ,Pregnancy Outcome ,Obstetrics and Gynecology ,DNA Methylation ,medicine.disease ,030104 developmental biology ,Case-Control Studies ,DNA methylation ,Female ,Self Report ,business ,Body mass index - Abstract
Preeclampsia is a leading cause of maternal and neonatal morbidity and mortality. Chronological age and race are associated with preeclampsia, but the role of these factors is not entirely understood. We hypothesized that DNA methylation age, a measure of biological age, would be higher in individuals with preeclampsia than in individuals with normotensive pregnancy and that DNA methylation age would differ by race across pregnancy. This was a longitudinal, exploratory study of 56 pregnant individuals (n = 28 preeclampsia cases and n = 28 normotensive controls). Genome-wide DNA methylation data were generated from trimester-specific peripheral blood samples. DNA methylation age was estimated using the "Improved Precision" clock, and ∆age, the difference between DNA methylation age and chronological age, was computed. DNA methylation age was compared with chronological age using Pearson correlations. The relationships between ∆age and preeclampsia status, self-reported race, and covariates were tested using multiple linear regression and performed both with and without consideration of cell-type heterogeneity. We observed strong correlation between chronological age and DNA methylation age across pregnancy, with significantly stronger correlation observed in White participants than in Black participants. We observed no association between ∆age and preeclampsia status. However, ∆age was higher in participants with higher pre-pregnancy body mass index in trimester 1 and lower in Black participants than in White participants in trimesters 2 and 3. Observations were largely consistent when controlling for cell-type heterogeneity. Our findings in a small sample support the need for additional studies to investigate the relationship between race and biological age, which could provide further insight into racial disparities across pregnancy. However, this study does not support an association between ∆age and preeclampsia status.
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- 2021
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29. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program
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Nancy L. Heard-Costa, Lucas Barwick, Clary B. Clish, Celeste Eng, Joanne M. Murabito, Esteban G. Burchard, Yii-Der Ida Chen, Daniel I. Chasman, Robert C. Kaplan, James B. Meigs, Deborah A. Nickerson, Cashell E. Jaquish, Eric Boerwinkle, Jennifer A. Brody, Charles Kooperberg, Mark T. Gladwin, Sebastian Schoenherr, Keng-Han Lin, John Barnard, Ryan D. Hernandez, Andrew D. Johnson, Edwin K. Silverman, Mollie A. Minear, Michelle Daya, Barbara A. Konkle, Sharon R. Browning, Daniel E. Weeks, Wendy S. Post, Alexander P. Reiner, Kathryn L. Lunetta, Gina M. Peloso, David Van Den Berg, Dan E. Arking, Seung-been Lee, Leslie A. Lange, Cristen J. Willer, Zachary A. Szpiech, Tasha E. Fingerlin, Wayne E. Clarke, Xutong Zhao, Stephen S. Rich, Nora Franceschini, Sudha Seshadri, Chloé Sarnowski, Hyun Min Kang, Sayantan Das, Michael C. Zody, Stephanie M. Fullerton, Dean Bobo, Alanna C. Morrison, Brian Custer, Nona Sotoodehnia, Shannon Kelly, Thomas W. Blackwell, Bruce M. Psaty, Yingze Zhang, Susan R. Heckbert, Robert E. Gerszten, M. Benjamin Shoemaker, Daniel Taliun, Leslie S. Emery, André Corvelo, Michael H. Cho, Braxton D. Mitchell, Xiaoming Liu, Stella Aslibekyan, Paul L. Auer, Brandon Chalazan, Sarah C. Nelson, Seung Hoan Choi, Jeong-Sun Seo, Matthew P. Conomos, Anne-Katrin Emde, Lawrence F. Bielak, Alisa K. Manning, Allison E. Ashley-Koch, Diane Fatkin, Xiaowen Tian, Emelia J. Benjamin, D. C. Rao, Mina K. Chung, Myriam Fornage, Daniel Levy, Michael D. Kessler, Weihong Tang, Daniel J. Gottlieb, Pradeep Natarajan, Jessica Lasky-Su, Amol C. Shetty, Cathy C. Laurie, Dan M. Roden, Timothy D. O’Connor, Jedidiah Carlson, Lewis C. Becker, Achilleas N. Pitsillides, Karine A. Viaud-Martinez, Raul Torres, Adolfo Correa, Christian Fuchsberger, Deborah A. Meyers, Alvaro Alonso, Sanghamitra Mohanty, Jonathon LeFaive, Soren Germer, Julie L. Mikulla, François Aguet, Susan K. Dutcher, Sarah A Gagliano Taliun, Ani Manichaikul, Lori Garman, Xiuqing Guo, Timothy A. Thornton, David D. McManus, Albert V. Smith, Kristin G. Ardlie, Anna Köttgen, Sharon L.R. Kardia, Quenna Wong, Jill M. Johnsen, Andrea Natale, Richard A. Gibbs, Douglas P. Kiel, Ingo Ruczinski, Susan Redline, Lukas Forer, Scott I. Vrieze, May E. Montasser, Rasika A. Mathias, Jerome I. Rotter, Jacob Pleiness, Chunyu Liu, Brian L. Browning, James G. Wilson, Weiniu Gan, Christine M. Albert, Marilyn J. Telen, Courtney G. Montgomery, Steven A. Lubitz, Robert Klemmer, Ramachandran S. Vasan, Nathan Pankratz, Mariza de Andrade, Vivien A. Sheehan, Kenneth Rice, Xihong Lin, Eimear E. Kenny, Stephanie M. Gogarten, John Blangero, Donna K. Arnett, Jiang He, Pankaj Qasba, James F. Casella, Patrick T. Ellinor, Nicholette D. Palmer, R. Graham Barr, Scott T. Weiss, Joanne E. Curran, Bruce S. Weir, Kari E. North, L. Adrienne Cupples, Dawn L. DeMeo, Tanika N. Kelly, Angel C.Y. Mak, Russell P. Tracy, David A. Schwartz, Kent D. Taylor, Rebecca L. Beer, Daniel N. Harris, George J. Papanicolaou, Marguerite R. Irvin, Stephen T. McGarvey, Sebastian Zöllner, Patricia A. Peyser, Brian E. Cade, Ruth J. F. Loos, Douglas Loesch, Nicholas L. Smith, Gonçalo R. Abecasis, Jennifer A. Smith, Michael E. Hall, Lu-Chen Weng, Jeffrey R. O'Connell, Adrienne M. Stilp, Donald W. Bowden, Kathleen C. Barnes, Stacey Gabriel, Michael Boehnke, Wayne Huey-Herng Sheu, and Dawood Darbar
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Quality Control ,Heterozygote ,Genomics ,Computational biology ,Biology ,Polymorphism, Single Nucleotide ,Genome ,Article ,DNA sequencing ,INDEL Mutation ,Loss of Function Mutation ,Genetics research ,Genetic variation ,Humans ,Precision Medicine ,Genetic association ,Population Density ,Multidisciplinary ,Whole Genome Sequencing ,Genome, Human ,Genetic Variation ,Rare variants ,United States ,Genetic architecture ,Phenotype ,Cytochrome P-450 CYP2D6 ,Haplotypes ,Mutagenesis ,Sample Size ,Next-generation sequencing ,National Heart, Lung, and Blood Institute (U.S.) ,Imputation (genetics) ,Reference genome - Abstract
The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%., The goals, resources and design of the NHLBI Trans-Omics for Precision Medicine (TOPMed) programme are described, and analyses of rare variants detected in the first 53,831 samples provide insights into mutational processes and recent human evolutionary history.
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- 2021
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30. ECHS1 disease in two unrelated families of Samoan descent: Common variant - rare disorder
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Stephen T. McGarvey, Daniel D. Nguyen, Shaya S. Eftekharian, Daniel E. Weeks, Sha Tang, Mariella Simon, Sacha Ferdinandusse, Muagututia Sefuiva Reupena, David Dimmock, Take Naseri, Jose E. Abdenur, Frédéric M. Vaz, James Pitt, Ryan L. Minster, Sansan Lee, Katarzyna A. Ellsworth, Laboratory Genetic Metabolic Diseases, Amsterdam Gastroenterology Endocrinology Metabolism, APH - Personalized Medicine, and APH - Methodology
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0301 basic medicine ,Male ,Heterozygote ,Adolescent ,Mitochondrial disease ,media_common.quotation_subject ,Samoa ,Population ,030105 genetics & heredity ,Biology ,medicine.disease_cause ,Compound heterozygosity ,03 medical and health sciences ,Rare Diseases ,ECHS1 ,Genetics ,medicine ,Humans ,Genetic Predisposition to Disease ,education ,Child ,Gene ,Enoyl-CoA Hydratase ,Genetics (clinical) ,media_common ,Dystonia ,education.field_of_study ,Mutation ,Daughter ,Infant ,Original Articles ,medicine.disease ,Leigh syndrome ,mitochondrial disease ,030104 developmental biology ,silent variant ,Child, Preschool ,Samoan population ,Original Article ,Female - Abstract
Mutations in the short‐chain enoyl‐CoA hydratase (SCEH) gene, ECHS1, cause a rare autosomal recessive disorder of valine catabolism. Patients usually present with developmental delay, regression, dystonia, feeding difficulties, and abnormal MRI with bilateral basal ganglia involvement. We present clinical, biochemical, molecular, and functional data for four affected patients from two unrelated families of Samoan descent with identical novel compound heterozygous mutations. Family 1 has three affected boys while Family 2 has an affected daughter, all with clinical and MRI findings of Leigh syndrome and intermittent episodes of acidosis and ketosis. WES identified a single heterozygous variant in ECHS1 at position c.832G > A (p.Ala278Thr). However, western blot revealed significantly reduced ECHS1 protein for all affected family members. Decreased SCEH activity in fibroblasts and a mild increase in marker metabolites in urine further supported ECHS1 as the underlying gene defect. Additional investigations at the DNA (aCGH, WGS) and RNA (qPCR, RT‐PCR, RNA‐Seq, RNA‐Array) level identified a silent, common variant at position c.489G > A (p.Pro163=) as the second mutation. This substitution, present at high frequency in the Samoan population, is associated with decreased levels of normally spliced mRNA. To our understanding, this is the first report of a novel, hypomorphic allele c.489G > A (p.Pro163=), associated with SCEH deficiency.
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- 2021
31. A stop-gain variant in
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Jenna C, Carlson, Mohanraj, Krishnan, Samantha L, Rosenthal, Emily M, Russell, Jerry Z, Zhang, Nicola L, Hawley, Jaye, Moors, Hong, Cheng, Nicola, Dalbeth, Janak R, de Zoysa, Huti, Watson, Muhammad, Qasim, Rinki, Murphy, Take, Naseri, Muagututi'a Sefuiva, Reupena, Satupa'itea, Viali, Lisa K, Stamp, John, Tuitele, Erin E, Kershaw, Ranjan, Deka, Stephen T, McGarvey, Tony R, Merriman, Daniel E, Weeks, and Ryan L, Minster
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Current understanding of lipid genetics has come mainly from studies in European-ancestry populations; limited effort has focused on Polynesian populations, whose unique population history and high prevalence of dyslipidemia may provide insight into the biological foundations of variation in lipid levels. Here, we performed an association study to fine map a suggestive association on 5q35 with high-density lipoprotein cholesterol (HDL-C) seen in Micronesian and Polynesian populations. Fine-mapping analyses in a cohort of 2,851 Samoan adults highlighted an association between a stop-gain variant (rs200884524; c.652CT, p.R218∗; posterior probability = 0.9987) in
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- 2022
32. A loss-of-function IFNAR1 allele in Polynesia underlies severe viral diseases in homozygotes
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Paul Bastard, Kuang-Chih Hsiao, Qian Zhang, Jeremy Choin, Emma Best, Jie Chen, Adrian Gervais, Lucy Bizien, Marie Materna, Christine Harmant, Maguelonne Roux, Nicola L. Hawley, Daniel E. Weeks, Stephen T. McGarvey, Karla Sandoval, Carmina Barberena-Jonas, Consuelo D. Quinto-Cortés, Erika Hagelberg, Alexander J. Mentzer, Kathryn Robson, Boubacar Coulibaly, Yoann Seeleuthner, Benedetta Bigio, Zhi Li, Gilles Uzé, Sandra Pellegrini, Lazaro Lorenzo, Zineb Sbihi, Sylvain Latour, Marianne Besnard, Tiphaine Adam de Beaumais, Evelyne Jacqz Aigrain, Vivien Béziat, Ranjan Deka, Litara Esera Tulifau, Satupa‘itea Viali, Muagututi‘a Sefuiva Reupena, Take Naseri, Peter McNaughton, Vanessa Sarkozy, Jane Peake, Annaliesse Blincoe, Sarah Primhak, Simon Stables, Kate Gibson, See-Tarn Woon, Kylie Marie Drake, Adrian V.S. Hill, Cheng-Yee Chan, Richard King, Rohan Ameratunga, Iotefa Teiti, Maite Aubry, Van-Mai Cao-Lormeau, Stuart G. Tangye, Shen-Ying Zhang, Emmanuelle Jouanguy, Paul Gray, Laurent Abel, Andrés Moreno-Estrada, Ryan L. Minster, Lluis Quintana-Murci, Andrew C. Wood, Jean-Laurent Casanova, Imagine - Institut des maladies génétiques (IHU) (Imagine - U1163), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Rockefeller University [New York], Human genetics of infectious diseases: Complex predisposition (Equipe Inserm U1163), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Département de Pédiatrie et maladies infectieuses [CHU Necker], CHU Necker - Enfants Malades [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Howard Hughes Medical Institute (HHMI), University of Auckland [Auckland], Génétique Evolutive Humaine - Human Evolutionary Genetics, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Collège de France - Chaire Génomique humaine et évolution, Collège de France (CdF (institution)), University of Pittsburgh (PITT), Pennsylvania Commonwealth System of Higher Education (PCSHE), Langebio (CINVESTAV), University of New South Wales [Sydney] (UNSW), Sydney Children's hospital, Garvan Institute of medical research, UNSW Faculty of Medicine [Sydney], Institut Louis Malardé [Papeete] (ILM), Institut de Recherche pour le Développement (IRD), Auckland City Hospital, Canterbury Health Laboratories, University of Oxford, University of Queensland [Brisbane], Brown University, Ministry of Health [Samoa], Tupua Tamasese Meaole Hospital (TTM), University of Cincinnati (UC), Hopital Saint-Louis [AP-HP] (AP-HP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Université Paris Cité (UPCité), Institut Gustave Roussy (IGR), Centre Hospitalier de Polynésie Française, Signalisation des Cytokines - Cytokine Signaling, Institut Pasteur [Paris] (IP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Cellules Souches, Plasticité Cellulaire, Médecine Régénératrice et Immunothérapies (IRMB), Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), University of Oslo (UiO), National Laboratory of Genomics for Biodiversity (LANGEBIO), Centro de Investigacion y de Estudios Avanzados del Instituto Politécnico Nacional (CINVESTAV), Yale University [New Haven], Hub Bioinformatique et Biostatistique - Bioinformatics and Biostatistics HUB, Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité), Human genetics of infectious diseases : Mendelian predisposition (Equipe Inserm U1163), Shanghai Jiaotong University, Murdoch Children's Research Institute (MCRI), The laboratory of V.-M. Cao-Lormeau is supported by MATAEA grant no. 03557/MED/REC_29/05/2019 (Délégation à la recherche de la Polynésie française). The Laboratory of Human Evolutionary Genetics is supported by Institut Pasteur, Collège de France, the Centre national de la recherche scientifique, Fondation Allianz-Institut de France, the French Government’s Investissement d’Avenir program, Laboratoires d’Excellence 'Integrative Biology of Emerging Infectious Diseases' (ANR-10-LABX-62-IBEID) and 'Milieu Intérieur' (ANR-10-LABX-69-01), Fondation de France (grant no. 00106080), and Fondation pour la Recherche Médicale (Equipe FRM DEQ20180339214). The Laboratory of Human Genetics of Infectious Diseases is supported by the Howard Hughes Medical Institute, the Rockefeller University, the St. Giles Foundation, the National Institutes of Health (NIH, R01AI088364 and R01AI163029), the National Center for Advancing Translational Sciences, the NIH Clinical and Translational Science Award program (UL1 TR001866), a Fast Grant from Emergent Ventures, Mercatus Center at George Mason University, the Yale Center for Mendelian Genomics, and the Genome Sequencing Program Coordinating Center funded by the National Human Genome Research Institute (UM1HG006504 and U24HG008956), the Yale High-Performance Computing Center (S10OD018521), the Fisher Center for Alzheimer’s Research Foundation, the Meyer Foundation, the French National Research Agency (ANR) under the 'Investments for the Future' program (ANR-10-IAHU-01), the Integrative Biology of Emerging Infectious Diseases Laboratory of Excellence (ANR-10-LABX-62-IBEID), the French Foundation for Medical Research (FRM, EQU201903007798), the FRM and ANR GENCOVID project, the ANRS-COV05, ANR GENVIR (ANR-20-CE93-003), and ANR AABIFNCOV (ANR-20-CO11-0001) projects, the European Union’s Horizon 2020 research and innovation program under grant agreement 824110 (EASI-genomics), the Square Foundation, Grandir - Fonds de solidarité pour l’enfance, the Fondation du Souffle, the SCOR Corporate Foundation for Science, INSERM, the French Ministry of Higher Education, Research, and Innovation (MESRI-COVID-19), and the University of Paris. P. Bastard was supported by the FRM (EA20170638020) and by the MD-PhD program of the Imagine Institute (with the support of Fondation Bettencourt-Schueller). The National Laboratory of Genomics for Biodiversity (LANGEBIO-CINVESTAV) in Mexico is supported by Consejo Nacional de Ciencia y Technologia (grant number FONCICYT/50/2016), The Newton Fund through the Medical Research Council (grant number MR/N028937/1), and the International Center for Genetic Engineering and Biotechnology grant number CRP/MEX20-01, awarded to A. Moreno-Estrada. S.G. Tangye is supported by a Leadership 3 Investigator Grant awarded by the National Health and Medical Research Council of Australia (1176665) and the Jeffrey Modell Foundation. Clinical Immunogenomics Research Consortium Australasia investigators (K.-C. Hsiao, P. McNaughton, A. Blincoe, J. Peake, S.G. Tangye, and P. Gray) are supported by the John Brown Cook Foundation. This work was supported by the National Institutes of Health grants R01-HL093093 (S.T. McGarvey) and R01-HL133040 (R.L. Minster). Molecular data for the Trans-Omics in Precision Medicine (TOPMed) program were provided by the National Heart, Lung, and Blood Institute (NHLBI). Genome sequencing for the Soifua Manuia study, labeled 'NHLBI TOPMed: Genome-wide Association Study of Adiposity in Samoans' (phs000972.v4.p1) in the dbGaP, was performed at the Northwest Genomics Center (HHSN268201100037C) and the New York Genome Center (HHSN268201500016C). Core support, including centralized genomic read mapping and genotype calling, along with variant quality metrics and filtering, was provided by the TOPMed Informatics Research Center (3R01-HL117626-02S1, contract HHSN268201800002I). Core support, including phenotype harmonization, data management, sample-identity QC, and general program coordination, was also provided by the TOPMed Data Coordinating Center (R01-HL120393, U01-HL120393, contract HHSN268201800001I). We gratefully acknowledge the studies and participants who provided biological samples and data for TOPMed. This research was funded in whole or in part by the French National Research Agency (ANR)., ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), ANR-10-LABX-0069,MILIEU INTERIEUR,GENETIC & ENVIRONMENTAL CONTROL OF IMMUNE PHENOTYPE VARIANCE: ESTABLISHING A PATH TOWARDS PERSONALIZED MEDICINE(2010), ANR-10-IAHU-0001,Imagine,Institut Hospitalo-Universitaire Imagine(2010), ANR-20-COVI-0003,GENCOVID,Identification des défauts monogéniques de l'immunité responsables des formes sévères de COVID-19 chez les patients précédemment en bonne santé(2020), ANR-20-CE93-0003,GENVIR,Analyse multi-omique de l'immunité anti-virale: de l'identification des circuits biologiques pertinents à la découverte de défauts monogéniques héréditaires de l'immunité chez les patients avec infections virales sévères(2020), ANR-20-CO11-0001,AABIFNCOV,Bases génétiques et immunologiques des auto-anticorps contre les interférons de type I prédisposant aux formes sévères de COVID-19.(2020), European Project: 824110,H2020-INFRAIA-2018-1,EASI-Genomics(2019), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPC), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPC), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPC), Institut Pasteur [Paris]-Université Paris Cité (UPC), University of Oxford [Oxford], Institut Pasteur [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPC), Institute for Regenerative Medicine and Biotherapy [Montpellier], Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre Hospitalier Universitaire de Montpellier (CHU Montpellier ), Université Paris Cité (UPC), Garvan Institute of Medical Research [Sydney, Australia], and Chaire Génomique humaine et évolution
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[SDV.GEN]Life Sciences [q-bio]/Genetics ,Infectious disease and host defense ,Homozygote ,Immunology ,Innate immunity and inflammation ,Receptor, Interferon alpha-beta ,Polynesia ,Virus Diseases ,[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases ,Humans ,Immunology and Allergy ,Immunodeficiency ,Child ,Alleles ,Human disease genetics - Abstract
International audience; Globally, autosomal recessive IFNAR1 deficiency is a rare inborn error of immunity underlying susceptibility to live attenuated vaccine and wild-type viruses. We report seven children from five unrelated kindreds of western Polynesian ancestry who suffered from severe viral diseases. All the patients are homozygous for the same nonsense IFNAR1 variant (p.Glu386*). This allele encodes a truncated protein that is absent from the cell surface and is loss-of-function. The fibroblasts of the patients do not respond to type I IFNs (IFN-α2, IFN-ω, or IFN-β). Remarkably, this IFNAR1 variant has a minor allele frequency >1% in Samoa and is also observed in the Cook, Society, Marquesas, and Austral islands, as well as Fiji, whereas it is extremely rare or absent in the other populations tested, including those of the Pacific region. Inherited IFNAR1 deficiency should be considered in individuals of Polynesian ancestry with severe viral illnesses.
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- 2022
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33. Mendelian randomization supports bidirectional causality between telomere length and clonal hematopoiesis of indeterminate potential
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Tetsushi, Nakao, Alexander G, Bick, Margaret A, Taub, Seyedeh M, Zekavat, Md M, Uddin, Abhishek, Niroula, Cara L, Carty, John, Lane, Michael C, Honigberg, Joshua S, Weinstock, Akhil, Pampana, Christopher J, Gibson, Gabriel K, Griffin, Shoa L, Clarke, Romit, Bhattacharya, Themistocles L, Assimes, Leslie S, Emery, Adrienne M, Stilp, Quenna, Wong, Jai, Broome, Cecelia A, Laurie, Alyna T, Khan, Albert V, Smith, Thomas W, Blackwell, Veryan, Codd, Christopher P, Nelson, Zachary T, Yoneda, Juan M, Peralta, Donald W, Bowden, Marguerite R, Irvin, Meher, Boorgula, Wei, Zhao, Lisa R, Yanek, Kerri L, Wiggins, James E, Hixson, C Charles, Gu, Gina M, Peloso, Dan M, Roden, Muagututi'a S, Reupena, Chii-Min, Hwu, Dawn L, DeMeo, Kari E, North, Shannon, Kelly, Solomon K, Musani, Joshua C, Bis, Donald M, Lloyd-Jones, Jill M, Johnsen, Michael, Preuss, Russell P, Tracy, Patricia A, Peyser, Dandi, Qiao, Pinkal, Desai, Joanne E, Curran, Barry I, Freedman, Hemant K, Tiwari, Sameer, Chavan, Jennifer A, Smith, Nicholas L, Smith, Tanika N, Kelly, Bertha, Hidalgo, L Adrienne, Cupples, Daniel E, Weeks, Nicola L, Hawley, Ryan L, Minster, Ranjan, Deka, Take T, Naseri, Lisa, de Las Fuentes, Laura M, Raffield, Alanna C, Morrison, Paul S, Vries, Christie M, Ballantyne, Eimear E, Kenny, Stephen S, Rich, Eric A, Whitsel, Michael H, Cho, M Benjamin, Shoemaker, Betty S, Pace, John, Blangero, Nicholette D, Palmer, Braxton D, Mitchell, Alan R, Shuldiner, Kathleen C, Barnes, Susan, Redline, Sharon L R, Kardia, Gonçalo R, Abecasis, Lewis C, Becker, Susan R, Heckbert, Jiang, He, Wendy, Post, Donna K, Arnett, Ramachandran S, Vasan, Dawood, Darbar, Scott T, Weiss, Stephen T, McGarvey, Mariza, de Andrade, Yii-Der Ida, Chen, Robert C, Kaplan, Deborah A, Meyers, Brian S, Custer, Adolfo, Correa, Bruce M, Psaty, Myriam, Fornage, JoAnn E, Manson, Eric, Boerwinkle, Barbara A, Konkle, Ruth J F, Loos, Jerome I, Rotter, Edwin K, Silverman, Charles, Kooperberg, John, Danesh, Nilesh J, Samani, Siddhartha, Jaiswal, Peter, Libby, Patrick T, Ellinor, Nathan, Pankratz, Benjamin L, Ebert, Alexander P, Reiner, Rasika A, Mathias, Ron, Do, and Pradeep, Natarajan
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Multidisciplinary - Abstract
Human genetic studies support an inverse causal relationship between leukocyte telomere length (LTL) and coronary artery disease (CAD), but directionally mixed effects for LTL and diverse malignancies. Clonal hematopoiesis of indeterminate potential (CHIP), characterized by expansion of hematopoietic cells bearing leukemogenic mutations, predisposes both hematologic malignancy and CAD. TERT (which encodes telomerase reverse transcriptase) is the most significantly associated germline locus for CHIP in genome-wide association studies. Here, we investigated the relationship between CHIP, LTL, and CAD in the Trans-Omics for Precision Medicine (TOPMed) program ( n = 63,302) and UK Biobank ( n = 47,080). Bidirectional Mendelian randomization studies were consistent with longer genetically imputed LTL increasing propensity to develop CHIP, but CHIP then, in turn, hastens to shorten measured LTL (mLTL). We also demonstrated evidence of modest mediation between CHIP and CAD by mLTL. Our data promote an understanding of potential causal relationships across CHIP and LTL toward prevention of CAD.
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- 2022
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34. A missense variant in CREBRF, rs373863828, is associated with fat-free mass, not fat mass in Samoan infants
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Joshua A Strayer, F. Unasa-Apelu, Abigail I. Wetzel, Rachel L. Duckham, Ulai T Fidow, Stephen T. McGarvey, Kendall Arslanian, Daniel E. Weeks, Theresa Atanoa, Take Naseri, Nicola L. Hawley, Erin E. Kershaw, and Alysa Pomer
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Adult ,Male ,Native Hawaiian or Other Pacific Islander ,Genotype ,Samoa ,Endocrinology, Diabetes and Metabolism ,Mutation, Missense ,Medicine (miscellaneous) ,Physiology ,030209 endocrinology & metabolism ,Locus (genetics) ,Polymorphism, Single Nucleotide ,Article ,Young Adult ,03 medical and health sciences ,0302 clinical medicine ,Diabetes mellitus ,Humans ,Medicine ,Prospective Studies ,030212 general & internal medicine ,Allele ,Prospective cohort study ,Nutrition and Dietetics ,business.industry ,Tumor Suppressor Proteins ,Infant, Newborn ,Infant ,Anthropometry ,medicine.disease ,Obesity ,Minor allele frequency ,Cross-Sectional Studies ,Body Composition ,Lean body mass ,Female ,business - Abstract
BACKGROUND/OBJECTIVES: In Samoa, where 80% of the adult population is living with obesity, understanding the determinants of adiposity and growth during infancy may inform prevention efforts. We examined the association of a missense variant, rs373863828, in the CREBRF gene with body composition in Samoan infants. Adults with one or more copies of the rs373863828 minor allele (A) have higher odds of obesity, based on body-mass index (BMI), but paradoxically decreased odds of diabetes compared to those without the allele. Our study may offer novel insight into the natural history and pathogenesis of this unexpected relationship. SUBJECTS/METHODS: In a prospective study, we measured body composition in early infancy, and at 2- and 4-months of age using anthropometry and Dual-Energy X-Ray Absorptiometry (DXA). We genotyped subjects at the CREBRF rs373863828 locus and compared infants with (AA/AG) and without (GG) the variant. In longitudinal analyses, we calculated the absolute change in each outcome from the early infant to the 4-month assessment, adjusting for baseline and other covariates. RESULTS: In cross-sectional analyses, there was no significant difference in infant BMI or fat mass by genotype. After adjusting for covariates, infants with the variant had 4.0 ± 1.8g more bone mass (p=0.026) and 210.9 ±79.6g more lean mass (p=0.009) at 4-months and accumulated 176.9 ± 73.0g more lean mass between the early infant and 4-month assessment (p=0.017). CONCLUSIONS: The CREBRF rs373863828 minor allele (A) was not associated with increased BMI or adiposity in Samoan infants, but instead with increased lean and bone mass. Our findings suggest that lean (i.e. muscle) and bone mass accretion should be explored as pathways to explain the ‘protective’ effect of the CREBRF variant against diabetes.
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- 2020
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35. Transcriptome-wide and differential expression network analyses of childhood asthma in nasal epithelium
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Daniel E. Weeks, Glorisa Canino, Nadia Boutaoui, Edna Acosta-Pérez, Zhao Ren, Wei Chen, Yueh-Ying Han, Soyeon Kim, Juan C. Celedón, Yale Jiang, Rong Zhang, Franziska Rosser, Qi Yan, Angel Colón-Semidey, María Alvarez, and Erick Forno
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Adult ,Male ,Adolescent ,Immunology ,Article ,Transcriptome ,Young Adult ,immune system diseases ,Humans ,Immunology and Allergy ,Medicine ,Differential expression ,Child ,Childhood asthma ,business.industry ,Gene Expression Profiling ,Immunoglobulin E ,Nasal epithelium ,Asthma ,respiratory tract diseases ,body regions ,Nasal Mucosa ,Case-Control Studies ,Female ,business - Abstract
In a transcription-wide association study of nasal epithelium, we identify novel and previously reported susceptibility genes for atopic asthma in children and show that gene co-expression networks differ markedly between children with and without atopic asthma.
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- 2020
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36. Genome-wide association studies in Samoans give insight into the genetic architecture of fasting serum lipid levels
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Nicola L. Hawley, Muagututi‘a Sefuiva Reupena, John Tuitele, Hong Cheng, Jenna C. Carlson, Guangyun Sun, Ranjan Deka, Ryan L. Minster, Take Naseri, Stephen T. McGarvey, and Daniel E. Weeks
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Adult ,Genetic Markers ,Male ,0301 basic medicine ,Apolipoprotein E ,Samoa ,Quantitative Trait Loci ,Population ,Genome-wide association study ,030105 genetics & heredity ,Biology ,Polymorphism, Single Nucleotide ,Article ,Cohort Studies ,03 medical and health sciences ,Apolipoproteins E ,Genetics ,Humans ,education ,Genotyping ,Triglycerides ,Genetics (clinical) ,Genetic association ,education.field_of_study ,Apolipoprotein A-I ,Cholesterol, HDL ,Cholesterol, LDL ,Fasting ,Middle Aged ,Lipid Metabolism ,Lipids ,Genetic architecture ,Cholesterol Ester Transfer Proteins ,030104 developmental biology ,Population bottleneck ,Female ,lipids (amino acids, peptides, and proteins) ,Genome-Wide Association Study ,Lipoprotein - Abstract
The current understanding of the genetic architecture of lipids has largely come from genome-wide association studies (GWAS). To date, few GWAS have examined the genetic architecture of lipids in Polynesians, and none have in Samoans, whose unique population history, including many population bottlenecks, may provide insight into the biological foundations of variation in lipid levels. Here we performed a GWAS of four fasting serum lipid levels: total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and triglycerides (TG) in a sample of 2849 Samoans, with validation genotyping for associations in a replication cohort comprising 1798 Samoans and American Samoans. We identified multiple genome-wide significant associations (P < 5 × 10(−8)) previously seen in other populations—APOA1 with TG, CETP with HDL, and APOE with TC and LDL—and several suggestive associations (P < 1 × 10(−5)), including an association of variants downstream of MGAT1 and RAB21 with HDL. However, we observed different association signals for variants near APOE than what has been previously reported in non-Polynesian populations. The association with several known lipid loci combined with the newly identified associations with variants near MGAT1 and RAB21 suggest that while some of the genetic architecture of lipids is shared between Samoans and other populations, part of the genetic architecture may be Polynesian-specific.
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- 2020
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37. Evolutionary history of modern Samoans
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Stephen T. McGarvey, Take Naseri, Daniel E. Weeks, Nicola L. Hawley, Muagututi‘a Sefuiva Reupena, Amol C. Shetty, Daniel N. Harris, Michael D. Kessler, Timothy D. O’Connor, Ethan E. Cochrane, Ranjan Deka, Ryan L. Minster, and Sharon R. Browning
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010506 paleontology ,Native Hawaiian or Other Pacific Islander ,Time Factors ,Samoa ,Oceania ,Population ,Population structure ,genetically understudied populations ,01 natural sciences ,03 medical and health sciences ,European colonialism ,Genetics ,Humans ,education ,Demography ,030304 developmental biology ,0105 earth and related environmental sciences ,0303 health sciences ,education.field_of_study ,Multidisciplinary ,fine-scale population structure ,rare variants ,Biological Sciences ,Biological Evolution ,Genealogy ,language.human_language ,Austronesian ,Geography ,Archaeology ,Capital city ,language ,Samoan ,Settlement (litigation) ,Chronology - Abstract
Significance There are multiple archaeological debates regarding early Samoan population history. Here, we add genetic data to this discussion, which supports an initial small population size at the founding of the Samoan islands. We also indicate a major demographic change approximately 1,000 y ago that mirrors the archaeological record. In addition, we demonstrate the utility of rare genetic variants in identifying sparse population structure. These genetic results help establish a detailed demographic model for the Samoan population, which will aid in future studies of Oceanic populations for both history and disease., Archaeological studies estimate the initial settlement of Samoa at 2,750 to 2,880 y ago and identify only limited settlement and human modification to the landscape until about 1,000 to 1,500 y ago. At this point, a complex history of migration is thought to have begun with the arrival of people sharing ancestry with Near Oceanic groups (i.e., Austronesian-speaking and Papuan-speaking groups), and was then followed by the arrival of non-Oceanic groups during European colonialism. However, the specifics of this peopling are not entirely clear from the archaeological and anthropological records, and is therefore a focus of continued debate. To shed additional light on the Samoan population history that this peopling reflects, we employ a population genetic approach to analyze 1,197 Samoan high-coverage whole genomes. We identify population splits between the major Samoan islands and detect asymmetrical gene flow to the capital city. We also find an extreme bottleneck until about 1,000 y ago, which is followed by distinct expansions across the islands and subsequent bottlenecks consistent with European colonization. These results provide for an increased understanding of Samoan population history and the dynamics that inform it, and also demonstrate how rapid demographic processes can shape modern genomes.
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- 2020
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38. Genetic Variability in the Iron Homeostasis Pathway and Patient Outcomes After Aneurysmal Subarachnoid Hemorrhage
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Daniel E. Weeks, Elizabeth Crago, Sheila Alexander, Samuel M. Poloyac, Lacey W. Heinsberg, Yvette P. Conley, and Ryan L. Minster
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Oncology ,medicine.medical_specialty ,Candidate gene ,Subarachnoid hemorrhage ,Iron ,Receptors, Cell Surface ,Single-nucleotide polymorphism ,Critical Care and Intensive Care Medicine ,Article ,Brain Ischemia ,03 medical and health sciences ,0302 clinical medicine ,Cerebral vasospasm ,Internal medicine ,Homeostasis ,Humans ,Vasospasm, Intracranial ,Medicine ,Genetic association ,business.industry ,Glasgow Outcome Scale ,Ceruloplasmin ,Bayes Theorem ,030208 emergency & critical care medicine ,Odds ratio ,Subarachnoid Hemorrhage ,medicine.disease ,Female ,Neurology (clinical) ,Outcomes research ,business ,030217 neurology & neurosurgery ,Genome-Wide Association Study - Abstract
BACKGROUND/OBJECTIVE: Iron can be detrimental to most tissues both in excess and in deficiency. The brain in particular is highly susceptible to the consequences of excessive iron, especially during blood brain barrier disruption after injury. Preliminary evidence suggests that iron homeostasis is important during recovery after neurologic injury, therefore, the exploration of genetic variability in genes involved in iron homeostasis is an important area of patient outcomes research. The purpose of this study was to examine the relationship between tagging SNPs in candidate genes related to iron homeostasis and acute and long-term patient outcomes after aneurysmal subarachnoid hemorrhage (aSAH). METHODS: This study was a longitudinal, observational, candidate gene association study of participants with aSAH that used a two tier design including tier 1 (discovery, n=197) and tier 2 (replication, n=277). Participants were followed during the acute outcome phase for development of cerebral vasospasm (CV) and delayed cerebral ischemia (DCI) and during the long-term outcome phase for death and gross functional outcome using the Glasgow Outcome Scale (GOS; poor = 1–3). Genetic association analyses were performed using a logistic regression model adjusted for age, sex, and Fisher grade. Approximate Bayes Factors (ABF) and Bayesian False Discovery Probabilities (BFDP) were used to prioritize and interpret results. RESULTS: In tier 1, 235 tagging SNPs in 28 candidate genes were available for analysis and 26 associations (20 unique SNPs in 12 genes) were nominated for replication in tier 2. In tier 2, we observed an increase in evidence of association for three associations in the ceruloplasmin (CP) and cubilin (CUBN) genes. We observed an association between rs17838831 (CP) with GOS at 3 months (tier 2 results, Odds Ratio [OR] = 2.10, 95% Confidence Interval [CI] = 1.14 – 3.86, p = 0.018, ABF = 0.52, and BFDP = 70.8%) and GOS at 12 months (tier 2 results, OR = 1.86, 95% CI = 0.98 – 3.52, p = 0.058, ABF = 0.72, and BFDP = 77.3%) as well as between rs10904850 (CUBN) with DCI (tier 2 results, OR = 0.70, 95% CI = 0.48 – 1.02, p = 0.064, ABF = 0.59, and BFDP = 71.8%). CONCLUSIONS: Among the genes examined, our findings support a role for CP and CUBN in patient outcomes after aSAH. In an effort to translate these findings into clinical utility and improve outcomes after aSAH, additional research is needed to examine the functional roles of these genes after aSAH.
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- 2020
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39. BayesRB: a markov chain Monte Carlo-based polygenic genetic risk score algorithm for dichotomous traits
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Ying Shan and Daniel E. Weeks
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Identifying high-risk individuals with diseases through reliable prediction models guides screening and preventive treatment. Most complex diseases have a genetic basis influenced by multiple genes and so disease risk can be estimated using polygenic risk score (PRS) algorithms. Many PRS algorithms have been developed so far. Among them, BayesR shows good characteristics of unbiasedness, accuracy, sparseness, and robustness. It detects the associated SNPs, estimates the SNP effects, and makes prediction of disease risks based on all SNPs simultaneously. However, this method assumes that the phenotypes follow a Gaussian distribution, which cannot be met in case-control studies. Here, we made an extension of the BayesR method, called BayesRB, by adding auxiliary variables to the BayesR model. We explored the characteristics, efficacy, and accuracy of BayesRB when estimating SNP effects and predicting disease risks compared with three traditional algorithms under different conditions using both simulated data and real data from the Welcome Trust Case Control Consortium (WTCCC). For SNP effect estimation, BayesRB shows unbiasedness and sparseness for big and small effect SNPs, respectively. For disease risk prediction, BayesRB had the best performance among the methods. This study provides a theoretical basis for complex disease risk prediction and disease prevention
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- 2022
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40. Iron homeostasis pathway DNA methylation trajectories reveal a role for STEAP3 metalloreductase in patient outcomes after aneurysmal subarachnoid hemorrhage
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Lacey W. Heinsberg, Daniel E. Weeks, Sheila A. Alexander, Ryan L. Minster, Paula R. Sherwood, Samuel M. Poloyac, Sandra Deslouches, Elizabeth A. Crago, and Yvette P. Conley
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Stroke ,Epigenetics ,Biomarker ,Six-transmembrane epithelial antigen of prostate 3 ,Group-based trajectory analysis ,Article - Abstract
Background Following aneurysmal subarachnoid hemorrhage (aSAH), the brain is susceptible to ferroptosis, a type of iron-dependent cell death. Therapeutic intervention targeting the iron homeostasis pathway shows promise for mitigating ferroptosis and improving recovery in animal models, but little work has been conducted in humans. DNA methylation (DNAm) plays a key role in gene expression and brain function, plasticity, and injury recovery, making it a potentially useful biomarker of outcomes or therapeutic target for intervention. Therefore, in this longitudinal, observational study, we examined the relationships between trajectories of DNAm in candidate genes related to iron homeostasis and acute (cerebral vasospasm and delayed cerebral ischemia) and long-term (Glasgow Outcome Scale [GOS, unfavorable = 1–3] and death) patient outcomes after aSAH. Results Longitudinal, genome-wide DNAm data were generated from DNA extracted from post-aSAH cerebrospinal fluid (n = 260 participants). DNAm trajectories of 637 CpG sites in 36 candidate genes related to iron homeostasis were characterized over 13 days post-aSAH using group-based trajectory analysis, an unsupervised clustering method. Significant associations were identified between inferred DNAm trajectory groups at several CpG sites and acute and long-term outcomes. Among our results, cg25713625 in the STEAP3 metalloreductase gene (STEAP3) stood out. Specifically, in comparing the highest cg25713625 DNAm trajectory group with the lowest, we observed significant associations (i.e., based on p-values less than an empirical significance threshold) with unfavorable GOS at 3 and 12 months (OR = 11.7, p = 0.0006 and OR = 15.6, p = 0.0018, respectively) and death at 3 and 12 months (OR = 19.1, p = 0.0093 and OR = 12.8, p = 0.0041, respectively). These results were replicated in an independent sample (n = 100 participants) observing significant associations with GOS at 3 and 12 months (OR = 8.2, p = 0.001 and OR = 6.3, p = 0.0.0047, respectively) and death at 3 months (OR = 2.3, p = 0.008) and a suggestive association (i.e., p-value OR = 2.0, p = 0.0272). In both samples, an additive effect of the DNAm trajectory group was observed as the percentage of participants with unfavorable long-term outcomes increased substantially with higher DNAm trajectory groups. Conclusion Our results support a role for DNAm of cg25713625/STEAP3 in recovery following aSAH. Additional research is needed to further explore the role of DNAm of cg25713625/STEAP3 as a biomarker of unfavorable outcomes, or therapeutic target to improve outcomes, to translate these findings clinically.
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- 2022
41. Rare coding variants in 35 genes associate with circulating lipid levels-A multi-ancestry analysis of 170,000 exomes
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George Hindy, Peter Dornbos, Mark D. Chaffin, Dajiang J. Liu, Minxian Wang, Margaret Sunitha Selvaraj, David Zhang, Joseph Park, Carlos A. Aguilar-Salinas, Lucinda Antonacci-Fulton, Diego Ardissino, Donna K. Arnett, Stella Aslibekyan, Gil Atzmon, Christie M. Ballantyne, Francisco Barajas-Olmos, Nir Barzilai, Lewis C. Becker, Lawrence F. Bielak, Joshua C. Bis, John Blangero, Eric Boerwinkle, Lori L. Bonnycastle, Erwin Bottinger, Donald W. Bowden, Matthew J. Bown, Jennifer A. Brody, Jai G. Broome, Noël P. Burtt, Brian E. Cade, Federico Centeno-Cruz, Edmund Chan, Yi-Cheng Chang, Yii-Der I. Chen, Ching-Yu Cheng, Won Jung Choi, Rajiv Chowdhury, Cecilia Contreras-Cubas, Emilio J. Córdova, Adolfo Correa, L. Adrienne Cupples, Joanne E. Curran, John Danesh, Paul S. de Vries, Ralph A. DeFronzo, Harsha Doddapaneni, Ravindranath Duggirala, Susan K. Dutcher, Patrick T. Ellinor, Leslie S. Emery, Jose C. Florez, Myriam Fornage, Barry I. Freedman, Valentin Fuster, Ma. Eugenia Garay-Sevilla, Humberto García-Ortiz, Soren Germer, Richard A. Gibbs, Christian Gieger, Benjamin Glaser, Clicerio Gonzalez, Maria Elena Gonzalez-Villalpando, Mariaelisa Graff, Sarah E. Graham, Niels Grarup, Leif C. Groop, Xiuqing Guo, Namrata Gupta, Sohee Han, Craig L. Hanis, Torben Hansen, Jiang He, Nancy L. Heard-Costa, Yi-Jen Hung, Mi Yeong Hwang, Marguerite R. Irvin, Sergio Islas-Andrade, Gail P. Jarvik, Hyun Min Kang, Sharon L.R. Kardia, Tanika Kelly, Eimear E. Kenny, Alyna T. Khan, Bong-Jo Kim, Ryan W. Kim, Young Jin Kim, Heikki A. Koistinen, Charles Kooperberg, Johanna Kuusisto, Soo Heon Kwak, Markku Laakso, Leslie A. Lange, Jiwon Lee, Juyoung Lee, Seonwook Lee, Donna M. Lehman, Rozenn N. Lemaitre, Allan Linneberg, Jianjun Liu, Ruth J.F. Loos, Steven A. Lubitz, Valeriya Lyssenko, Ronald C.W. Ma, Lisa Warsinger Martin, Angélica Martínez-Hernández, Rasika A. Mathias, Stephen T. McGarvey, Ruth McPherson, James B. Meigs, Thomas Meitinger, Olle Melander, Elvia Mendoza-Caamal, Ginger A. Metcalf, Xuenan Mi, Karen L. Mohlke, May E. Montasser, Jee-Young Moon, Hortensia Moreno-Macías, Alanna C. Morrison, Donna M. Muzny, Sarah C. Nelson, Peter M. Nilsson, Jeffrey R. O’Connell, Marju Orho-Melander, Lorena Orozco, Colin N.A. Palmer, Nicholette D. Palmer, Cheol Joo Park, Kyong Soo Park, Oluf Pedersen, Juan M. Peralta, Patricia A. Peyser, Wendy S. Post, Michael Preuss, Bruce M. Psaty, Qibin Qi, D.C. Rao, Susan Redline, Alexander P. Reiner, Cristina Revilla-Monsalve, Stephen S. Rich, Nilesh Samani, Heribert Schunkert, Claudia Schurmann, Daekwan Seo, Jeong-Sun Seo, Xueling Sim, Rob Sladek, Kerrin S. Small, Wing Yee So, Adrienne M. Stilp, E. Shyong Tai, Claudia H.T. Tam, Kent D. Taylor, Yik Ying Teo, Farook Thameem, Brian Tomlinson, Michael Y. Tsai, Tiinamaija Tuomi, Jaakko Tuomilehto, Teresa Tusié-Luna, Miriam S. Udler, Rob M. van Dam, Ramachandran S. Vasan, Karine A. Viaud Martinez, Fei Fei Wang, Xuzhi Wang, Hugh Watkins, Daniel E. Weeks, James G. Wilson, Daniel R. Witte, Tien-Yin Wong, Lisa R. Yanek, Sekar Kathiresan, Daniel J. Rader, Jerome I. Rotter, Michael Boehnke, Mark I. McCarthy, Cristen J. Willer, Pradeep Natarajan, Jason A. Flannick, Amit V. Khera, Gina M. Peloso, NIH - National Heart, Lung, and Blood Institute (NHLBI) (Estados Unidos), Centre of Excellence in Complex Disease Genetics, HUS Abdominal Center, Institute for Molecular Medicine Finland, Leif Groop Research Group, Clinicum, Department of Medicine, HUS Internal Medicine and Rehabilitation, University of Helsinki, and Department of Public Health
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APOC3 ,Blood Glucose ,Multifactorial Inheritance ,gene-based association ,Polymorphism, Single Nucleotide ,Article ,Open Reading Frames ,ANGPTL3 ,lipid ,OF-FUNCTION MUTATIONS ,BINDING ,Databases, Genetic ,SEQUENCE VARIANTS ,Genetics ,Humans ,Exome ,Genetic Predisposition to Disease ,SINUSOIDAL ENDOTHELIAL-CELLS ,Genetics (clinical) ,Alleles ,RISK ,IDENTIFICATION ,1184 Genetics, developmental biology, physiology ,association ,cholesterol ,Genetic Variation ,Computational Biology ,Molecular Sequence Annotation ,PERILIPIN ,Lipid Metabolism ,Lipids ,Genetics, Population ,Phenotype ,Diabetes Mellitus, Type 2 ,Liver ,Case-Control Studies ,exome sequencing ,TRIGLYCERIDES ,Genome-Wide Association Study - Abstract
Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels. This work was supported by a grant from the Swedish Research Council (2016-06830) and grants from the National Heart, Lung, and Blood Institute (NHLBI): R01HL142711 and R01HL127564. Please refer to the supplemental information for the full acknowledgements. Sí
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- 2022
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42. ANGPT1 methylation and delayed cerebral ischemia in aneurysmal subarachnoid hemorrhage patients
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Dongjing Liu, Annie I. Arockiaraj, John R. Shaffer, Samuel M. Poloyac, Paula R. Sherwood, Sheila A. Alexander, Elizabeth A. Crago, Daniel E. Weeks, and Yvette P. Conley
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Background Delayed cerebral ischemia (DCI) is a common secondary complication and an important cause of disability and mortality among patients who survive aneurysmal subarachnoid hemorrhage (aSAH). Knowledge on DCI pathogenesis, risk factors, and biomarkers are essential for early detection and improved prognosis. To investigate the role of DNA methylation in DCI risk, we conducted an epigenome-wide association study (EWAS) in 68 patients followed up to 1 year after the initial aneurysm rupture. Blood samples were collected within 48 h post hemorrhage and used for DNA methylation profiling at ~ 450k CpG sites. A separate cohort of 175 patients was sequenced for the top CpG sites from the discovery analysis for a replication of the EWAS findings. Results EWAS did not identify any epigenome-wide significant CpGs. The top signal, cg18031596, was annotated to ANGPT1, a gene with critical functions in angiogenesis after vascular injury. Post hoc power calculations indicated a well-powered discovery analysis for cg18031596. Analysis of the replication cohort showed that four out of the five CpG sites sequenced at the ANGPT1 locus passed a Bonferroni-adjusted significance threshold. In a pooled analysis of the entire sample, three out of five yielded a significant p-value, and the top association signal (p-value = 0.004) was seen for a CpG that was not originally measured in the discovery EWAS. However, four ANGPT1 CpG sites had an opposite effect direction in the replication analysis compared to the discovery EWAS, marking a failure of replication. We carefully examined this observed flip in directions and propose several possible explanations in addition to that it was a random chance that ANGPT1 ranked at the top in the discovery EWAS. Conclusions We failed to demonstrate a significant and consistent effect of ANGPT1 methylation in DCI risk in two cohorts. Though the replication attempt to weaken the overall support of this gene, given its relevant function and top rank of significance in the EWAS, our results call for future studies of larger aSAH cohorts to determine its relevance for the occurrence of DCI.
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- 2021
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43. Characterization of cerebrospinal fluid DNA methylation age during the acute recovery period following aneurysmal subarachnoid hemorrhage
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Lacey W. Heinsberg, Dongjing Liu, John R. Shaffer, Daniel E. Weeks, and Yvette P. Conley
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Stroke ,Epigenomics ,Age acceleration ,Epigenetics ,Group-based trajectory analysis ,Article - Abstract
Background Biological aging may occur at different rates than chronological aging due to genetic, social, and environmental factors. DNA methylation (DNAm) age is thought to be a reliable measure of accelerated biological aging which has been linked to an array of poor health outcomes. Given the importance of chronological age in recovery following aneurysmal subarachnoid hemorrhage (aSAH), a type of stroke, DNAm age may also be an important biomarker of outcomes, further improving predictive models. Cerebrospinal fluid (CSF) is a unique tissue representing the local central nervous system environment post-aSAH. However, the validity of CSF DNAm age is unknown, and it is unclear which epigenetic clock is ideal to compute CSF DNAm age, particularly given changes in cell type heterogeneity (CTH) during the acute recovery period. Further, the stability of DNAm age post-aSAH, specifically, has not been examined and may improve our understanding of patient recovery post-aSAH. Therefore, the purpose of this study was to characterize CSF DNAm age over 14 days post-aSAH using four epigenetic clocks. Results Genome-wide DNAm data were available for two tissues: (1) CSF for N = 273 participants with serial sampling over 14 days post-aSAH (N = 850 samples) and (2) blood for a subset of n = 72 participants at one time point post-aSAH. DNAm age was calculated using the Horvath, Hannum, Levine, and “Improved Precision” (Zhang) epigenetic clocks. “Age acceleration” was computed as the residuals of DNAm age regressed on chronological age both with and without correcting for CTH. Using scatterplots, Pearson correlations, and group-based trajectory analysis, we examined the relationships between CSF DNAm age and chronological age, the concordance between DNAm ages calculated from CSF versus blood, and the stability (i.e., trajectories) of CSF DNAm age acceleration over time during recovery from aSAH. We observed moderate to strong correlations between CSF DNAm age and chronological age (R = 0.66 [Levine] to R = 0.97 [Zhang]), moderate to strong correlations between DNAm age in CSF versus blood (R = 0.69 [Levine] to R = 0.98 [Zhang]), and stable CSF age acceleration trajectories over 14 days post-aSAH in the Horvath and Zhang clocks (unadjusted for CTH), as well as the Hannum clock (adjusted for CTH). Conclusions CSF DNAm age was generally stable post-aSAH. Although correlated, CSF DNAm age differs from blood DNAm age in the Horvath, Hannum, and Levine clocks, but not in the Zhang clock. Taken together, our results suggest that, of the clocks examined here, the Zhang clock is the most robust to CTH and is recommended for use in complex tissues such as CSF.
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- 2021
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44. A framework for detecting noncoding rare variant associations of large-scale whole-genome sequencing studies
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Adolfo Correa, Corbin Quick, Jennifer A. Brody, Daniel E. Weeks, Rounak Dey, Joanne E. Curran, Charles Kooperberg, Wei Zhao, Brian G. Kral, Lisa W. Martin, Christen J. Willer, Donald W. Bowden, Eric Boerwinkle, Theodore Arapoglou, Joshua C. Bis, Barry I. Freedman, Leslie A. Lange, Ryan Sun, James G. Wilson, Lawrence F. Bielak, May E. Montasser, Kent D. Taylor, Jerome I. Rotter, Ramachandran S. Vasan, L. Adrienne Cupples, Rita R. Kalyani, Hufeng Zhou, Ani Manichaikul, John Blangero, Han Chen, Patricia A. Peyser, Stephen S. Rich, Brian E. Cade, Sheila M. Gaynor, Paul S. de Vries, Xihong Lin, Susan Redline, Thomas W. Blackwell, Margaret Sunitha Selvaraj, Jeffrey R. O'Connell, Xihao Li, Bruce M. Psaty, Ravindranath Duggirala, Matthew P. Conomos, Kenneth Rice, Donna K. Arnett, Muagututi‘a Sefuiva Reupena, Alanna C. Morrison, Nicholette D. Palmer, Jennifer A. Smith, Harald H H Göring, Alexander P. Reiner, Lisa R. Yanek, Braxton D. Mitchell, Laura M. Raffield, Yaowu Liu, Xiuqing Guo, Gina M. Peloso, Zilin Li, Pradeep Natarajan, and Take Naseri
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Whole genome sequencing ,Technology ,Genome ,Whole Genome Sequencing ,Human Genome ,Genetic Variation ,Scale (descriptive set theory) ,Computational biology ,Replicate ,TOPMed Lipids Working Group ,Biological Sciences ,Biology ,Medical and Health Sciences ,Annotation ,NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium ,Phenotype ,Good Health and Well Being ,Genetics ,Humans ,Generic health relevance ,Genome-Wide Association Study ,Biotechnology ,Developmental Biology ,Genetic association - Abstract
Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare variants’ (RVs) associations with complex human traits. Variant set analysis is a powerful approach to study RV association, and a key component of it is constructing RV sets for analysis. However, existing methods have limited ability to define analysis units in the noncoding genome. Furthermore, there is a lack of robust pipelines for comprehensive and scalable noncoding RV association analysis. Here we propose a computationally-efficient noncoding RV association-detection framework that uses STAAR (variant-set test for association using annotation information) to group noncoding variants in gene-centric analysis based on functional categories. We also propose SCANG (scan the genome)-STAAR, which uses dynamic window sizes and incorporates multiple functional annotations, in a non-gene-centric analysis. We furthermore develop STAARpipeline to perform flexible noncoding RV association analysis, including gene-centric analysis as well as fixed-window-based and dynamic-window-based non-gene-centric analysis. We apply STAARpipeline to identify noncoding RV sets associated with four quantitative lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several noncoding RV associations in an additional 9,123 TOPMed samples.
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- 2021
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45. A population-specific missense variant rs1597000001 inCETPpromotes a favorable lipid profile and reduces CETP activity
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Nicola L. Hawley, J. A. Moors, Murray Cadzow, J. de Zoysa, Sally P.A. McCormick, Daniel E. Weeks, Tony R. Merriman, B. Morgan, Nicholas A Sumpter, J. Z. Zhang, Ruth Topless, M. Taumoepeau, Guangyun Sun, Lisa K. Stamp, R. Dekar, F. King, M. Krishnan, Ryan L. Minster, Stephen T. McGarvey, Megan Leask, Rinki Murphy, Satupaitea Viali, Jenna C. Carlson, Phillip Wilcox, Emily M. Russell, Marilyn E. Merriman, John Tuitele, Take Naseri, Matthew J. Bixley, Nicola Dalbeth, Riku Takei, Hong Cheng, Tanya J Major, Amanda Phipps-Green, M. Rutledge, and Muagututi’a S. Reupena
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medicine.medical_specialty ,symbols.namesake ,Endocrinology ,medicine.diagnostic_test ,Internal medicine ,Population specific ,medicine ,Mendelian inheritance ,symbols ,Missense mutation ,Biology ,Lipid profile - Abstract
Sequencing ofCETPin Māori and Pacific peoples identified a common (MAF ∼2.4%-5.4%) population-specific missense variant (rs1597000001,CETP:c.530C>T p.Pro177Leu) that associates with higher HDL-C levels ([95% CI 0.211; 0.260]) and lower LDL-C ([95% CI -0.209; -0.058]). In a subsample of the study cohort (n = 11), heterozygous carriers of the population-specific variant had lower plasma CETP activity (P= 0.028). Our study identifies a population-specific missense variant inCETPwhich lowers CETP activity with an effect on HDL-C that is comparable to MendelianCETPloss-of-function mutations.
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- 2021
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46. A murine model of the human CREBRFR457Q obesity-risk variant does not influence energy or glucose homeostasis in response to nutritional stress
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Nicola L. Hawley, Ray Lu, Stephen T. McGarvey, Anna C. Meyer, Polly E. Mattila, Gabriele Schoiswohl, Michael Ewing, Sebastien Gingras, Erin E. Kershaw, Daniel E. Weeks, Ashlee N Wood, Aneta Kowalski, Brett A. Kaufman, Ryan L. Minster, Samantha L. Rosenthal, and Jitendra S. Kanshana
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Male ,Bioenergetics ,Physiology ,Adipose tissue ,Disease ,Biochemistry ,Body Mass Index ,Mice ,Glucose Metabolism ,Medicine and Health Sciences ,Glucose homeostasis ,Homeostasis ,Gene Knock-In Techniques ,Multidisciplinary ,Organic Compounds ,Monosaccharides ,Animal Models ,DNA-Binding Proteins ,Chemistry ,Experimental Organism Systems ,Physiological Parameters ,Adipose Tissue ,Connective Tissue ,Physical Sciences ,Medicine ,Carbohydrate Metabolism ,Female ,Anatomy ,Research Article ,medicine.medical_specialty ,Science ,Carbohydrates ,Mutation, Missense ,Mouse Models ,Carbohydrate metabolism ,Biology ,Research and Analysis Methods ,Polymorphism, Single Nucleotide ,Model Organisms ,Diabetes mellitus ,Internal medicine ,medicine ,Animals ,Genetic Predisposition to Disease ,Obesity ,Nutrition ,Body Weight ,Organic Chemistry ,Chemical Compounds ,Biology and Life Sciences ,medicine.disease ,Diet ,Disease Models, Animal ,Endocrinology ,Biological Tissue ,Metabolism ,Glucose ,Animal Studies ,Physiological Processes ,Energy Metabolism - Abstract
Obesity and diabetes have strong heritable components, yet the genetic contributions to these diseases remain largely unexplained. In humans, a missense variant in Creb3 regulatory factor (CREBRF) [rs373863828 (p.Arg457Gln); CREBRFR457Q] is strongly associated with increased odds of obesity but decreased odds of diabetes. Although virtually nothing is known about CREBRF’s mechanism of action, emerging evidence implicates it in the adaptive transcriptional response to nutritional stress downstream of TORC1. The objectives of this study were to generate a murine model with knockin of the orthologous variant in mice (CREBRFR458Q) and to test the hypothesis that this CREBRF variant promotes obesity and protects against diabetes by regulating energy and glucose homeostasis downstream of TORC1. To test this hypothesis, we performed extensive phenotypic analysis of CREBRFR458Q knockin mice at baseline and in response to acute (fasting/refeeding), chronic (low- and high-fat diet feeding), and extreme (prolonged fasting) nutritional stress as well as with pharmacological TORC1 inhibition, and aging to 52 weeks. The results demonstrate that the murine CREBRFR458Q model of the human CREBRFR457Q variant does not influence energy/glucose homeostasis in response to these interventions, with the exception of possible greater loss of fat relative to lean mass with age. Alternative preclinical models and/or studies in humans will be required to decipher the mechanisms linking this variant to human health and disease.
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- 2021
47. Gene-Based Association Testing of Dichotomous Traits With Generalized Functional Linear Mixed Models Using Extended Pedigrees: Applications to Age-Related Macular Degeneration
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Yvette P. Conley, Christopher I. Amos, Daniel E. Weeks, Ao Yuan, Alexander F. Wilson, Ana I. Vazquez, Chi-Yang Chiu, Yingda Jiang, Ruzong Fan, Qi Yan, Francis J. McMahon, M'Hamed Lajmi Lakhal-Chaieb, Joan E. Bailey-Wilson, Xiaogang Zhong, Michael B. Gorin, Momiao Xiong, Wei Chen, and Richard J. Cook
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Statistics and Probability ,Genetics ,Association test ,genetic structures ,Blindness ,business.industry ,Association (object-oriented programming) ,05 social sciences ,Pedigree chart ,Macular degeneration ,medicine.disease ,01 natural sciences ,Generalized linear mixed model ,eye diseases ,Article ,010104 statistics & probability ,Age related ,0502 economics and business ,medicine ,sense organs ,0101 mathematics ,Statistics, Probability and Uncertainty ,business ,Gene ,050205 econometrics - Abstract
Genetics plays a role in age-related macular degeneration (AMD), a common cause of blindness in the elderly. There is a need for powerful methods for carrying out region-based association tests between a dichotomous trait like AMD and genetic variants on family data. Here, we apply our new generalized functional linear mixed models (GFLMM) developed to test for gene-based association in a set of AMD families. Using common and rare variants, we observe significant association with two known AMD genes: CFH and ARMS2. Using rare variants, we find suggestive signals in four genes: ASAH1, CLEC6A, TMEM63C, and SGSM1. Intriguingly, ASAH1 is down-regulated in AMD aqueous humor, and ASAH1 deficiency leads to retinal inflammation and increased vulnerability to oxidative stress. These findings were made possible by our GFLMM which model the effect of a major gene as a fixed mean, the polygenic contributions as a random variation, and the correlation of pedigree members by kinship coefficients. Simulations indicate that the GFLMM likelihood ratio tests (LRTs) accurately control the Type I error rates. The LRTs have similar or higher power than existing retrospective kernel and burden statistics. Our GFLMM-based statistics provide a new tool for conducting family-based genetic studies of complex diseases. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.
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- 2021
48. MicroRNA-associated DNA Methylation in a Longitudinal, Exploratory Study of Preeclamptic and Normotensive Pregnancy
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Mitali Ray, Lacey W. Heinsberg, Ningxi Chen, Yvette P. Conley, Daniel E. Weeks, and Mandy J. Schmella
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Obstetrics and Gynecology - Published
- 2022
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49. Whole Genome Sequencing Identifies CRISPLD2 as a Lung Function Gene in Children With Asthma
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Priyadarshini Kachroo, Julian Hecker, Bo L. Chawes, Tarunveer S. Ahluwalia, Michael H. Cho, Dandi Qiao, Rachel S. Kelly, Su H. Chu, Yamini V. Virkud, Mengna Huang, Kathleen C. Barnes, Esteban G. Burchard, Celeste Eng, Donglei Hu, Juan C. Celedón, Michelle Daya, Albert M. Levin, Hongsheng Gui, L. Keoki Williams, Erick Forno, Angel C.Y. Mak, Lydiana Avila, Manuel E. Soto-Quiros, Michelle M. Cloutier, Edna Acosta-Pérez, Glorisa Canino, Klaus Bønnelykke, Hans Bisgaard, Benjamin A. Raby, Christoph Lange, Scott T. Weiss, Jessica A. Lasky-Su, Namiko Abe, Goncalo Abecasis, Christine Albert, Nicholette (Nichole) Palmer Allred, Laura Almasy, Alvaro Alonso, Seth Ament, Peter Anderson, Pramod Anugu, Deborah Applebaum-Bowden, Dan Arking, Donna K. Arnett, Allison Ashley-Koch, Stella Aslibekyan, Tim Assimes, Paul Auer, Dimitrios Avramopoulos, John Barnard, Kathleen Barnes, R. Graham Barr, Emily Barron-Casella, Terri Beaty, Diane Becker, Lewis Becker, Rebecca Beer, Ferdouse Begum, Amber Beitelshees, Emelia Benjamin, Marcos Bezerra, Larry Bielak, Joshua Bis, Thomas Blackwell, John Blangero, Eric Boerwinkle, Ingrid Borecki, Russell Bowler, Jennifer Brody, Ulrich Broeckel, Jai Broome, Karen Bunting, Esteban Burchard, Jonathan Cardwell, Cara Carty, Richard Casaburi, James Casella, Mark Chaffin, Christy Chang, Daniel Chasman, Sameer Chavan, Bo-Juen Chen, Wei-Min Chen, Yii-Der Ida Chen, Seung Hoan Choi, Lee-Ming Chuang, Mina Chung, Elaine Cornell, Adolfo Correa, Carolyn Crandall, James Crapo, L. Adrienne Cupples, Joanne Curran, Jeffrey Curtis, Brian Custer, Coleen Damcott, Dawood Darbar, Sayantan Das, Sean David, Colleen Davis, Mariza de Andrade, Michael DeBaun, Ranjan Deka, Dawn DeMeo, Scott Devine, Ron Do, Qing Duan, Ravi Duggirala, Peter Durda, Susan Dutcher, Charles Eaton, Lynette Ekunwe, Patrick Ellinor, Leslie Emery, Charles Farber, Leanna Farnam, Tasha Fingerlin, Matthew Flickinger, Myriam Fornage, Nora Franceschini, Mao Fu, Stephanie M. Fullerton, Lucinda Fulton, Stacey Gabriel, Weiniu Gan, Yan Gao, Margery Gass, Bruce Gelb, Xiaoqi (Priscilla) Geng, Soren Germer, Chris Gignoux, Mark Gladwin, David Glahn, Stephanie Gogarten, Da-Wei Gong, Harald Goring, C. Charles Gu, Yue Guan, Xiuqing Guo, Jeff Haessler, Michael Hall, Daniel Harris, Nicola Hawley, Jiang He, Ben Heavner, Susan Heckbert, Ryan Hernandez, David Herrington, Craig Hersh, Bertha Hidalgo, James Hixson, John Hokanson, Kramer Holly, Elliott Hong, Karin Hoth, Chao (Agnes) Hsiung, Haley Huston, Chii Min Hwu, Marguerite Ryan Irvin, Rebecca Jackson, Deepti Jain, Cashell Jaquish, Min A. Jhun, Jill Johnsen, Andrew Johnson, Craig Johnson, Rich Johnston, Kimberly Jones, Hyun Min Kang, Robert Kaplan, Sharon Kardia, Sekar Kathiresan, Laura Kaufman, Shannon Kelly, Eimear Kenny, Michael Kessler, Alyna Khan, Greg Kinney, Barbara Konkle, Charles Kooperberg, Stephanie Krauter, Ethan Lange, Leslie Lange, Cathy Laurie, Cecelia Laurie, Meryl LeBoff, Seunggeun Shawn Lee, Wen-Jane Lee, Jonathon LeFaive, David Levine, Dan Levy, Joshua Lewis, Yun Li, Honghuang Lin, Keng Han Lin, Simin Liu, Yongmei Liu, Ruth Loos, Steven Lubitz, Kathryn Lunetta, James Luo, Michael Mahaney, Barry Make, Ani Manichaikul, JoAnn Manson, Lauren Margolin, Lisa Martin, Susan Mathai, Rasika Mathias, Patrick McArdle, Merry-Lynn McDonald, Sean McFarland, Stephen McGarvey, Hao Mei, Deborah A. Meyers, Julie Mikulla, Nancy Min, Mollie Minear, Ryan L. Minster, Braxton Mitchell, May E. Montasser, Solomon Musani, Stanford Mwasongwe, Josyf C. Mychaleckyj, Girish Nadkarni, Rakhi Naik, Pradeep Natarajan, Sergei Nekhai, Deborah Nickerson, Kari North, Jeff O'Connell, Tim O'Connor, Heather Ochs-Balcom, James Pankow, George Papanicolaou, Margaret Parker, Afshin Parsa, Sara Penchev, Juan Manuel Peralta, Marco Perez, James Perry, Ulrike Peters, Patricia Peyser, Lawrence S. Phillips, Sam Phillips, Toni Pollin, Wendy Post, Julia Powers Becker, Meher Preethi Boorgula, Michael Preuss, Dmitry Prokopenko, Bruce Psaty, Pankaj Qasba, Zhaohui Qin, Nicholas Rafaels, Laura Raffield, Vasan Ramachandran, D.C. Rao, Laura Rasmussen-Torvik, Aakrosh Ratan, Susan Redline, Robert Reed, Elizabeth Regan, Alex Reiner, Ken Rice, Stephen Rich, Dan Roden, Carolina Roselli, Jerome Rotter, Ingo Ruczinski, Pamela Russell, Sarah Ruuska, Kathleen Ryan, Phuwanat Sakornsakolpat, Shabnam Salimi, Steven Salzberg, Kevin Sandow, Vijay Sankaran, Christopher Scheller, Ellen Schmidt, Karen Schwander, David Schwartz, Frank Sciurba, Christine Seidman, Jonathan Seidman, Vivien Sheehan, Amol Shetty, Aniket Shetty, Wayne Hui-Heng Sheu, M. Benjamin Shoemaker, Brian Silver, Edwin Silverman, Jennifer Smith, Josh Smith, Nicholas Smith, Tanja Smith, Sylvia Smoller, Beverly Snively, Tamar Sofer, Nona Sotoodehnia, Adrienne Stilp, Elizabeth Streeten, Yun Ju Sung, Jessica Su-Lasky, Jody Sylvia, Adam Szpiro, Carole Sztalryd, Daniel Taliun, Hua Tang, Margaret Taub, Kent Taylor, Simeon Taylor, Marilyn Telen, Timothy A. Thornton, Lesley Tinker, David Tirschwell, Hemant Tiwari, Russell Tracy, Michael Tsai, Dhananjay Vaidya, Peter VandeHaar, Scott Vrieze, Tarik Walker, Robert Wallace, Avram Walts, Emily Wan, Fei Fei Wang, Karol Watson, Daniel E. Weeks, Bruce Weir, Scott Weiss, Lu-Chen Weng, Cristen Willer, Kayleen Williams, Carla Wilson, James Wilson, Quenna Wong, Huichun Xu, Lisa Yanek, Ivana Yang, Rongze Yang, Norann Zaghloul, Maryam Zekavat, Yingze Zhang, Snow Xueyan Zhao, Wei Zhao, Xiuwen Zheng, Degui Zhi, Xiang Zhou, Michael Zody, and Sebastian Zoellner
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Adult ,Costa Rica ,Male ,Pulmonary and Respiratory Medicine ,Adolescent ,Vital Capacity ,Single-nucleotide polymorphism ,Pedigree chart ,Critical Care and Intensive Care Medicine ,Young Adult ,03 medical and health sciences ,FEV1/FVC ratio ,0302 clinical medicine ,Polymorphism (computer science) ,Forced Expiratory Volume ,Humans ,Medicine ,SNP ,030212 general & internal medicine ,Child ,Asthma ,Whole Genome Sequencing ,business.industry ,Middle Aged ,respiratory system ,medicine.disease ,respiratory tract diseases ,Minor allele frequency ,030228 respiratory system ,Genetic epidemiology ,Child, Preschool ,Interferon Regulatory Factors ,Immunology ,Respiratory Physiological Phenomena ,Female ,Cardiology and Cardiovascular Medicine ,business ,Cell Adhesion Molecules - Abstract
BACKGROUND: Asthma is a common respiratory disorder with a highly heterogeneous nature that remains poorly understood. The objective was to use whole genome sequencing (WGS) data to identify regions of common genetic variation contributing to lung function in individuals with a diagnosis of asthma. METHODS: WGS data were generated for 1,053 individuals from trios and extended pedigrees participating in the family-based Genetic Epidemiology of Asthma in Costa Rica study. Asthma affection status was defined through a physician’s diagnosis of asthma, and most participants with asthma also had airway hyperresponsiveness (AHR) to methacholine. Family-based association tests for single variants were performed to assess the associations with lung function phenotypes. RESULTS: A genome-wide significant association was identified between baseline FEV(1)/FVC ratio and a single-nucleotide polymorphism in the top hit cysteine-rich secretory protein LCCL domain-containing 2 (CRISPLD2) (rs12051168; P = 3.6 × 10(−8) in the unadjusted model) that retained suggestive significance in the covariate-adjusted model (P = 5.6 × 10(−6)). Rs12051168 was also nominally associated with other related phenotypes: baseline FEV(1) (P = 3.3 × 10(−3)), postbronchodilator (PB) FEV(1) (7.3 × 10(−3)), and PB FEV(1)/FVC ratio (P = 2.7 × 10(−3)). The identified baseline FEV(1)/FVC ratio and rs12051168 association was meta-analyzed and replicated in three independent cohorts in which most participants with asthma also had confirmed AHR (combined weighted z-score P = .015) but not in cohorts without information about AHR. CONCLUSIONS: These findings suggest that using specific asthma characteristics, such as AHR, can help identify more genetically homogeneous asthma subgroups with genotype-phenotype associations that may not be observed in all children with asthma. CRISPLD2 also may be important for baseline lung function in individuals with asthma who also may have AHR.
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- 2019
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50. Genetic Variability and Trajectories of DNA Methylation May Support a Role for HAMP in Patient Outcomes After Aneurysmal Subarachnoid Hemorrhage
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Susan M. Sereika, John R. Shaffer, Paula R. Sherwood, Annie I. Arockiaraj, Yvette P. Conley, Lacey W. Heinsberg, Daniel E. Weeks, Dianxu Ren, and Elizabeth Crago
- Subjects
Adult ,Male ,Oncology ,medicine.medical_specialty ,Subarachnoid hemorrhage ,Glasgow Outcome Scale ,Pilot Projects ,Critical Care and Intensive Care Medicine ,Polymorphism, Single Nucleotide ,Article ,Brain Ischemia ,03 medical and health sciences ,0302 clinical medicine ,Cerebral vasospasm ,Hepcidins ,Modified Rankin Scale ,Internal medicine ,Genotype ,Humans ,Vasospasm, Intracranial ,Medicine ,Longitudinal Studies ,Aged ,business.industry ,030208 emergency & critical care medicine ,Methylation ,DNA Methylation ,Middle Aged ,Subarachnoid Hemorrhage ,Prognosis ,medicine.disease ,Functional Status ,DNA methylation ,Disease Progression ,Female ,Neurology (clinical) ,HAMP ,business ,030217 neurology & neurosurgery - Abstract
BACKGROUND/OBJECTIVE: Preclinical evidence suggests iron homeostasis is an important biological mechanism following aneurysmal subarachnoid hemorrhage (aSAH), however, this concept is underexplored in humans. This study examined the relationship between patient outcomes following aSAH and genetic variants and DNA methylation in the hepcidin gene (HAMP), a key regulator of iron homeostasis. METHODS: In this exploratory, longitudinal observational study, participants with verified aSAH were monitored for acute outcomes including cerebral vasospasm (CV) and delayed cerebral ischemia (DCI) and evaluated post-discharge at 3 and 12 months for long-term outcomes of death and functional status using the Modified Rankin Scale (mRS; poor = 3-6) and Glasgow Outcome Scale (GOS; poor = 1-3). Participants were genotyped for two genetic variants and DNA methylation data was collected from serial cerebrospinal fluid over 14 days post-aSAH at 8 methylation sites within HAMP. Participants were grouped based on their site-specific DNA methylation trajectory, with and without correcting for cell type heterogeneity (CTH), and the associations between genetic variants and inferred DNA methylation trajectory groups and patient outcomes were tested. To correct for multiple testing, an empirical significance threshold was computed using permutation testing. RESULTS: Genotype data for rs10421768 and rs7251432 were available for 241 and 371 participants respectively and serial DNA methylation data were available for 260 participants. Acute outcome prevalence included CV in 45% and DCI in 37.1% of the overall sample. Long-term outcome prevalence at 3 and 12 months included poor GOS in 23% and 21%, poor mRS in 31.6% and 27.3%, and mortality in 15.1% and 18.2%, respectively in the overall sample. Being homozygous for the rs7251432 variant allele was significantly associated with death at 3 months (p=0.003) and was the only association identified that passed adjustments for multiple testing mentioned above. Suggestive associations (defined as trending toward significance, p-value
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- 2019
- Full Text
- View/download PDF
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