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Browsing by Author "Natarajan, Pradeep"
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Item A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies(Springer Nature, 2022) Li, Zilin; Li, Xihao; Zhou, Hufeng; Gaynor, Sheila M.; Selvaraj, Margaret Sunitha; Arapoglou, Theodore; Quick, Corbin; Liu, Yaowu; Chen, Han; Sun, Ryan; Dey, Rounak; Arnett, Donna K.; Auer, Paul L.; Bielak, Lawrence F.; Bis, Joshua C.; Blackwell, Thomas W.; Blangero, John; Boerwinkle, Eric; Bowden, Donald W.; Brody, Jennifer A.; Cade, Brian E.; Conomos, Matthew P.; Correa, Adolfo; Cupples, L. Adrienne; Curran, Joanne E.; de Vries, Paul S.; Duggirala, Ravindranath; Franceschini, Nora; Freedman, Barry I.; Göring, Harald H. H.; Guo, Xiuqing; Kalyani, Rita R.; Kooperberg, Charles; Kral, Brian G.; Lange, Leslie A.; Lin, Bridget M.; Manichaikul, Ani; Manning, Alisa K.; Martin, Lisa W.; Mathias, Rasika A.; Meigs, James B.; Mitchell, Braxton D.; Montasser, May E.; Morrison, Alanna C.; Naseri, Take; O'Connell, Jeffrey R.; Palmer, Nicholette D.; Peyser, Patricia A.; Psaty, Bruce M.; Raffield, Laura M.; Redline, Susan; Reiner, Alexander P.; Reupena, Muagututi'a Sefuiva; Rice, Kenneth M.; Rich, Stephen S.; Smith, Jennifer A.; Taylor, Kent D.; Taub, Margaret A.; Vasan, Ramachandran S.; Weeks, Daniel E.; Wilson, James G.; Yanek, Lisa R.; Zhao, Wei; NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium; TOPMed Lipids Working Group; Rotter, Jerome I.; Willer, Cristen J.; Natarajan, Pradeep; Peloso, Gina M.; Lin, Xihong; Biostatistics and Health Data Science, School of MedicineLarge-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 TOPMed samples. We also analyze five non-lipid TOPMed traits.Item Association of premature menopause with incident pulmonary hypertension: A cohort study(PLOS, 2021-03-10) Honigberg, Michael C.; Patel, Aniruddh P.; Lahm, Tim; Wood, Malissa J.; Ho, Jennifer E.; Kohli, Puja; Natarajan, Pradeep; Medicine, School of MedicineBackground: Several forms of pulmonary hypertension (PH) disproportionately affect women. Animal and human studies suggest that estradiol exerts mixed effects on the pulmonary vasculature. Whether premature menopause represents a risk factor for PH is unknown. Methods and findings: In this cohort study, women in the UK Biobank aged 40-69 years who were postmenopausal and had complete data available on reproductive history were included. Premature menopause, defined as menopause occurring before age 40 years. Postmenopausal women without premature menopause served as the reference group. The primary outcome was incident PH, ascertained by appearance of a qualifying ICD code in the participant's UK Biobank study record. Of 136,715 postmenopausal women included, 5,201 (3.8%) had premature menopause. Participants were followed up for a median of 11.1 (interquartile range 10.5-11.8) years. The primary outcome occurred in 38 women (0.73%) with premature menopause and 409 (0.31%) without. After adjustment for age, race, ever-smoking, body-mass index, systolic blood pressure, antihypertensive medication use, non-high-density lipoprotein cholesterol, cholesterol-lowering medication use, C-reactive protein, prevalent type 2 diabetes, obstructive sleep apnea, heart failure, mitral regurgitation, aortic stenosis, venous thromboembolism, forced vital capacity (FVC), the forced expiratory volume in 1 second-to-FVC ratio, use of menopausal hormone therapy, and hysterectomy status, premature menopause was independently associated with PH (hazard ratio 2.13, 95% CI 1.31-3.23, P<0.001). In analyses of alternate menopausal age thresholds, risk of PH appeared to increase progressively with younger age at menopause (Ptrend <0.001), with 4.8-fold risk in women with menopause before age 30 years (95% CI 1.82-12.74, P = 0.002). Use of menopausal hormone therapy did not modify the association of premature menopause with PH. Conclusions: Premature menopause may represent an independent risk factor for PH in women. Further investigation of the role of sex hormones in PH is needed in animal and human studies to elucidate pathobiology and identify novel therapeutic targets.Item Obesity-induced inflammation exacerbates clonal hematopoiesis(The American Society for Clinical Investigation, 2023-06-01) Pasupuleti, Santhosh Kumar; Ramdas, Baskar; Burns, Sarah S.; Palam, Lakshmi Reddy; Kanumuri, Rahul; Kumar, Ramesh; Pandhiri, Taruni Reddy; Dave, Utpal P.; Yellapu, Nanda Kumar; Zhou, Xinyu; Zhang, Chi; Sandusky, George E.; Yu, Zhi; Honigberg, Michael C.; Bick, Alexander G.; Griffin, Gabriel K.; Niroula, Abhishek; Ebert, Benjamin L.; Paczesny, Sophie; Natarajan, Pradeep; Kapur, Reuben; Medicine, School of MedicineCharacterized by the accumulation of somatic mutations in blood cell lineages, clonal hematopoiesis of indeterminate potential (CHIP) is frequent in aging and involves the expansion of mutated hematopoietic stem and progenitor cells (HSC/Ps) that leads to an increased risk of hematologic malignancy. However, the risk factors that contribute to CHIP-associated clonal hematopoiesis (CH) are poorly understood. Obesity induces a proinflammatory state and fatty bone marrow (FBM), which may influence CHIP-associated pathologies. We analyzed exome sequencing and clinical data for 47,466 individuals with validated CHIP in the UK Biobank. CHIP was present in 5.8% of the study population and was associated with a significant increase in the waist-to-hip ratio (WHR). Mouse models of obesity and CHIP driven by heterozygosity of Tet2, Dnmt3a, Asxl1, and Jak2 resulted in exacerbated expansion of mutant HSC/Ps due in part to excessive inflammation. Our results show that obesity is highly associated with CHIP and that a proinflammatory state could potentiate the progression of CHIP to more significant hematologic neoplasia. The calcium channel blockers nifedipine and SKF-96365, either alone or in combination with metformin, MCC950, or anakinra (IL-1 receptor antagonist), suppressed the growth of mutant CHIP cells and partially restored normal hematopoiesis. Targeting CHIP-mutant cells with these drugs could be a potential therapeutic approach to treat CH and its associated abnormalities in individuals with obesity.Item Polygenic prediction of preeclampsia and gestational hypertension(Springer Nature, 2023) Honigberg, Michael C.; Truong, Buu; Khan, Raiyan R.; Xiao, Brenda; Bhatta, Laxmi; Vy, Ha My T.; Guerrero, Rafael F.; Schuermans, Art; Selvaraj, Margaret Sunitha; Patel, Aniruddh P.; Koyama, Satoshi; Cho, So Mi Jemma; Vellarikkal, Shamsudheen Karuthedath; Trinder, Mark; Urbut, Sarah M.; Gray, Kathryn J.; Brumpton, Ben M.; Patil, Snehal; Zöllner, Sebastian; Antopia, Mariah C.; Saxena, Richa; Nadkarni, Girish N.; Do, Ron; Yan, Qi; Pe’er, Itsik; Verma, Shefali Setia; Gupta, Rajat M.; Haas, David M.; Martin, Hilary C.; van Heel, David A.; Laisk, Triin; Natarajan, Pradeep; Obstetrics and Gynecology, School of MedicinePreeclampsia and gestational hypertension are common pregnancy complications associated with adverse maternal and child outcomes. Current tools for prediction, prevention and treatment are limited. Here we tested the association of maternal DNA sequence variants with preeclampsia in 20,064 cases and 703,117 control individuals and with gestational hypertension in 11,027 cases and 412,788 control individuals across discovery and follow-up cohorts using multi-ancestry meta-analysis. Altogether, we identified 18 independent loci associated with preeclampsia/eclampsia and/or gestational hypertension, 12 of which are new (for example, MTHFR-CLCN6, WNT3A, NPR3, PGR and RGL3), including two loci (PLCE1 and FURIN) identified in the multitrait analysis. Identified loci highlight the role of natriuretic peptide signaling, angiogenesis, renal glomerular function, trophoblast development and immune dysregulation. We derived genome-wide polygenic risk scores that predicted preeclampsia/eclampsia and gestational hypertension in external cohorts, independent of clinical risk factors, and reclassified eligibility for low-dose aspirin to prevent preeclampsia. Collectively, these findings provide mechanistic insights into the hypertensive disorders of pregnancy and have the potential to advance pregnancy risk stratification.Item Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies(Springer Nature, 2023) Li, Xihao; Quick, Corbin; Zhou, Hufeng; Gaynor, Sheila M.; Liu, Yaowu; Chen, Han; Selvaraj, Margaret Sunitha; Sun, Ryan; Dey, Rounak; Arnett, Donna K.; Bielak, Lawrence F.; Bis, Joshua C.; Blangero, John; Boerwinkle, Eric; Bowden, Donald W.; Brody, Jennifer A.; Cade, Brian E.; Correa, Adolfo; Cupples, L. Adrienne; Curran, Joanne E.; de Vries, Paul S.; Duggirala, Ravindranath; Freedman, Barry I.; Göring, Harald H. H.; Guo, Xiuqing; Haessler, Jeffrey; Kalyani, Rita R.; Kooperberg, Charles; Kral, Brian G.; Lange, Leslie A.; Manichaikul, Ani; Martin, Lisa W.; McGarvey, Stephen T.; Mitchell, Braxton D.; Montasser, May E.; Morrison, Alanna C.; Naseri, Take; O'Connell, Jeffrey R.; Palmer, Nicholette D.; Peyser, Patricia A.; Psaty, Bruce M.; Raffield, Laura M.; Redline, Susan; Reiner, Alexander P.; Reupena, Muagututi'a Sefuiva; Rice, Kenneth M.; Rich, Stephen S.; Sitlani, Colleen M.; Smith, Jennifer A.; Taylor, Kent D.; Vasan, Ramachandran S.; Willer, Cristen J.; Wilson, James G.; Yanek, Lisa R.; Zhao, Wei; NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium; TOPMed Lipids Working Group; Rotter, Jerome I.; Natarajan, Pradeep; Peloso, Gina M.; Li, Zilin; Lin, Xihong; Biostatistics and Health Data Science, School of MedicineMeta-analysis of whole genome sequencing/whole exome sequencing (WGS/WES) studies provides an attractive solution to the problem of collecting large sample sizes for discovering rare variants associated with complex phenotypes. Existing rare variant meta-analysis approaches are not scalable to biobank-scale WGS data. Here we present MetaSTAAR, a powerful and resource-efficient rare variant meta-analysis framework for large-scale WGS/WES studies. MetaSTAAR accounts for relatedness and population structure, can analyze both quantitative and dichotomous traits and boosts the power of rare variant tests by incorporating multiple variant functional annotations. Through meta-analysis of four lipid traits in 30,138 ancestrally diverse samples from 14 studies of the Trans Omics for Precision Medicine (TOPMed) Program, we show that MetaSTAAR performs rare variant meta-analysis at scale and produces results comparable to using pooled data. Additionally, we identified several conditionally significant rare variant associations with lipid traits. We further demonstrate that MetaSTAAR is scalable to biobank-scale cohorts through meta-analysis of TOPMed WGS data and UK Biobank WES data of ~200,000 samples.Item Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed Whole Genome Sequencing Study(medRxiv, 2023-06-29) Wang, Yuxuan; Selvaraj, Margaret Sunitha; Li, Xihao; Li, Zilin; Holdcraft, Jacob A.; Arnett, Donna K.; Bis, Joshua C.; Blangero, John; Boerwinkle, Eric; Bowden, Donald W.; Cade, Brian E.; Carlson, Jenna C.; Carson, April P.; Chen, Yii-Der Ida; Curran, Joanne E.; de Vries, Paul S.; Dutcher, Susan K.; Ellinor, Patrick T.; Floyd, James S.; Fornage, Myriam; Freedman, Barry I.; Gabriel, Stacey; Germer, Soren; Gibbs, Richard A.; Guo, Xiuqing; He, Jiang; Heard-Costa, Nancy; Hildalgo, Bertha; Hou, Lifang; Irvin, Marguerite R.; Joehanes, Roby; Kaplan, Robert C.; Kardia, Sharon Lr.; Kelly, Tanika N.; Kim, Ryan; Kooperberg, Charles; Kral, Brian G.; Levy, Daniel; Li, Changwei; Liu, Chunyu; Lloyd-Jone, Don; Loos, Ruth Jf.; Mahaney, Michael C.; Martin, Lisa W.; Mathias, Rasika A.; Minster, Ryan L.; Mitchell, Braxton D.; Montasser, May E.; Morrison, Alanna C.; Murabito, Joanne M.; Naseri, Take; O'Connell, Jeffrey R.; Palmer, Nicholette D.; Preuss, Michael H.; Psaty, Bruce M.; Raffield, Laura M.; Rao, Dabeeru C.; Redline, Susan; Reiner, Alexander P.; Rich, Stephen S.; Ruepena, Muagututi'a Sefuiva; Sheu, Wayne H-H; Smith, Jennifer A.; Smith, Albert; Tiwari, Hemant K.; Tsai, Michael Y.; Viaud-Martinez, Karine A.; Wang, Zhe; Yanek, Lisa R.; Zhao, Wei; NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium; Rotter, Jerome I.; Lin, Xihong; Natarajan, Pradeep; Peloso, Gina M.; Biostatistics and Health Data Science, School of MedicineLong non-coding RNAs (lncRNAs) are known to perform important regulatory functions. Large-scale whole genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess the associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with blood lipid levels (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare variant aggregate association tests using the STAAR (variant-Set Test for Association using Annotation infoRmation) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare coding variants in nearby protein coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500 kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variations and rare protein coding variations at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNA, implicating new therapeutic opportunities.