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2,764 results on '"North, Kari"'

1. Methylation patterns associated with C-reactive protein in racially and ethnically diverse populations

Author: Lundin, Jessica I, Peters, Ulrike, Hu, Yao, Ammous, Farah, Avery, Christy L, Benjamin, Emelia J, Bis, Joshua C, Brody, Jennifer A, Carlson, Chris, Cushman, Mary, Gignoux, Chris, Guo, Xiuqing, Haessler, Jeff, Haiman, Chris, Joehanes, Roby, Kasela, Silva, Kenny, Eimear, Lapalainien, Tuuli, Levy, Daniel, Liu, Chunyu, Liu, Yongmei, Loos, Ruth JF, Lu, Ake, Matise, Tara, North, Kari E, Park, Sungshim L, Ratliff, Scott M, Reiner, Alex, Rich, Stephen S, Rotter, Jerome I, Smith, Jennifer A, Sotoodehnia, Nona, Tracy, Russell, Van den Berg, David, Xu, Huichun, Ye, Ting, Zhao, Wei, Raffield, Laura M, Kooperberg, Charles, and Study, On Behalf of the PAGE
Subjects: Biological Sciences, Genetics, Minority Health, American Indian or Alaska Native, Human Genome, Health Disparities, Aetiology, 2.1 Biological and endogenous factors, Inflammatory and immune system, Humans, DNA Methylation, C-Reactive Protein, Epigenesis, Genetic, DNA, Inflammation, Genome-Wide Association Study, CpG Islands, Intracellular Signaling Peptides and Proteins, C-reactive protein, methylation, epigenetics, EWAS, racial and ethnic diversity, Mendelian randomization, causal pathway, PAGE Study, Biochemistry and Cell Biology, Medical Biochemistry and Metabolomics, Developmental Biology, Biochemistry and cell biology
Abstract: Systemic low-grade inflammation is a feature of chronic disease. C-reactive protein (CRP) is a common biomarker of inflammation and used as an indicator of disease risk; however, the role of inflammation in disease is not completely understood. Methylation is an epigenetic modification in the DNA which plays a pivotal role in gene expression. In this study we evaluated differential DNA methylation patterns associated with blood CRP level to elucidate biological pathways and genetic regulatory mechanisms to improve the understanding of chronic inflammation. The racially and ethnically diverse participants in this study were included as 50% White, 41% Black or African American, 7% Hispanic or Latino/a, and 2% Native Hawaiian, Asian American, American Indian, or Alaska Native (total n = 13,433) individuals. We replicated 113 CpG sites from 87 unique loci, of which five were novel (CADM3, NALCN, NLRC5, ZNF792, and cg03282312), across a discovery set of 1,150 CpG sites associated with CRP level (p
Published: 2024

2. Determinants of mosaic chromosomal alteration fitness.

Author: Pershad, Yash, Mack, Taralynn, Poisner, Hannah, Jakubek, Yasminka, Stilp, Adrienne, Mitchell, Braxton, Lewis, Joshua, Boerwinkle, Eric, Loos, Ruth, Chami, Nathalie, Wang, Zhe, Barnes, Kathleen, Pankratz, Nathan, Fornage, Myriam, Redline, Susan, Psaty, Bruce, Bis, Joshua, Shojaie, Ali, Silverman, Edwin, Cho, Michael, Yun, Jeong, DeMeo, Dawn, Levy, Daniel, Johnson, Andrew, Mathias, Rasika, Taub, Margaret, Arnett, Donna, North, Kari, Raffield, Laura, Carson, April, Doyle, Margaret, Rich, Stephen, Guo, Xiuqing, Cox, Nancy, Roden, Dan, Franceschini, Nora, Desai, Pinkal, Reiner, Alex, Auer, Paul, Scheet, Paul, Jaiswal, Siddhartha, Weinstock, Joshua, Bick, Alexander, and Rotter, Jerome
Subjects: Humans, Mosaicism, Chromosome Aberrations, Clonal Hematopoiesis, Male, Female, Genome-Wide Association Study, Janus Kinase 2, Telomerase, Loss of Heterozygosity, Cross-Sectional Studies, Mutation, Middle Aged, Hematopoietic Stem Cells, Polymorphism, Single Nucleotide, Aged
Abstract: Clonal hematopoiesis (CH) is characterized by the acquisition of a somatic mutation in a hematopoietic stem cell that results in a clonal expansion. These driver mutations can be single nucleotide variants in cancer driver genes or larger structural rearrangements called mosaic chromosomal alterations (mCAs). The factors that influence the variations in mCA fitness and ultimately result in different clonal expansion rates are not well understood. We used the Passenger-Approximated Clonal Expansion Rate (PACER) method to estimate clonal expansion rate as PACER scores for 6,381 individuals in the NHLBI TOPMed cohort with gain, loss, and copy-neutral loss of heterozygosity mCAs. Our mCA fitness estimates, derived by aggregating per-individual PACER scores, were correlated (R2 = 0.49) with an alternative approach that estimated fitness of mCAs in the UK Biobank using population-level distributions of clonal fraction. Among individuals with JAK2 V617F clonal hematopoiesis of indeterminate potential or mCAs affecting the JAK2 gene on chromosome 9, PACER score was strongly correlated with erythrocyte count. In a cross-sectional analysis, genome-wide association study of estimates of mCA expansion rate identified a TCL1A locus variant associated with mCA clonal expansion rate, with suggestive variants in NRIP1 and TERT.
Published: 2024

3. Identification of proteins associated with type 2 diabetes risk in diverse racial and ethnic populations

Author: Liu, Shuai, Zhu, Jingjing, Zhong, Hua, Wu, Chong, Xue, Haoran, Darst, Burcu F., Guo, Xiuqing, Durda, Peter, Tracy, Russell P., Liu, Yongmei, Johnson, W. Craig, Taylor, Kent D., Manichaikul, Ani W., Goodarzi, Mark O., Gerszten, Robert E., Clish, Clary B., Chen, Yii-Der Ida, Highland, Heather, Haiman, Christopher A., Gignoux, Christopher R., Lange, Leslie, Conti, David V., Raffield, Laura M., Wilkens, Lynne, Marchand, Loïc Le, North, Kari E., Young, Kristin L., Loos, Ruth J., Buyske, Steve, Matise, Tara, Peters, Ulrike, Kooperberg, Charles, Reiner, Alexander P., Yu, Bing, Boerwinkle, Eric, Sun, Quan, Rooney, Mary R., Echouffo-Tcheugui, Justin B., Daviglus, Martha L., Qi, Qibin, Mancuso, Nicholas, Li, Changwei, Deng, Youping, Manning, Alisa, Meigs, James B., Rich, Stephen S., Rotter, Jerome I., and Wu, Lang
Published: 2024
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4. Validation of human telomere length multi-ancestry meta-analysis association signals identifies POP5 and KBTBD6 as human telomere length regulation genes

Author: Keener, Rebecca, Chhetri, Surya B, Connelly, Carla J, Taub, Margaret A, Conomos, Matthew P, Weinstock, Joshua, Ni, Bohan, Strober, Benjamin, Aslibekyan, Stella, Auer, Paul L, Barwick, Lucas, Becker, Lewis C, Blangero, John, Bleecker, Eugene R, Brody, Jennifer A, Cade, Brian E, Celedon, Juan C, Chang, Yi-Cheng, Cupples, L Adrienne, Custer, Brian, Freedman, Barry I, Gladwin, Mark T, Heckbert, Susan R, Hou, Lifang, Irvin, Marguerite R, Isasi, Carmen R, Johnsen, Jill M, Kenny, Eimear E, Kooperberg, Charles, Minster, Ryan L, Naseri, Take, Viali, Satupa’itea, Nekhai, Sergei, Pankratz, Nathan, Peyser, Patricia A, Taylor, Kent D, Telen, Marilyn J, Wu, Baojun, Yanek, Lisa R, Yang, Ivana V, Albert, Christine, Arnett, Donna K, Ashley-Koch, Allison E, Barnes, Kathleen C, Bis, Joshua C, Blackwell, Thomas W, Boerwinkle, Eric, Burchard, Esteban G, Carson, April P, Chen, Zhanghua, Chen, Yii-Der Ida, Darbar, Dawood, de Andrade, Mariza, Ellinor, Patrick T, Fornage, Myriam, Gelb, Bruce D, Gilliland, Frank D, He, Jiang, Islam, Talat, Kaab, Stefan, Kardia, Sharon LR, Kelly, Shannon, Konkle, Barbara A, Kumar, Rajesh, Loos, Ruth JF, Martinez, Fernando D, McGarvey, Stephen T, Meyers, Deborah A, Mitchell, Braxton D, Montgomery, Courtney G, North, Kari E, Palmer, Nicholette D, Peralta, Juan M, Raby, Benjamin A, Redline, Susan, Rich, Stephen S, Roden, Dan, Rotter, Jerome I, Ruczinski, Ingo, Schwartz, David, Sciurba, Frank, Shoemaker, M Benjamin, Silverman, Edwin K, Sinner, Moritz F, Smith, Nicholas L, Smith, Albert V, Tiwari, Hemant K, Vasan, Ramachandran S, Weiss, Scott T, Williams, L Keoki, Zhang, Yingze, Ziv, Elad, Raffield, Laura M, Reiner, Alexander P, Arvanitis, Marios, Greider, Carol W, Mathias, Rasika A, and Battle, Alexis
Subjects: Biological Sciences, Genetics, Human Genome, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Generic health relevance, Humans, Genome-Wide Association Study, Telomere, K562 Cells, Telomere Homeostasis, Polymorphism, Single Nucleotide, Gene Expression Regulation, CRISPR-Cas Systems, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Hematology and Hemostasis Working Group, TOPMed Structural Variation Working Group
Abstract: Genome-wide association studies (GWAS) have become well-powered to detect loci associated with telomere length. However, no prior work has validated genes nominated by GWAS to examine their role in telomere length regulation. We conducted a multi-ancestry meta-analysis of 211,369 individuals and identified five novel association signals. Enrichment analyses of chromatin state and cell-type heritability suggested that blood/immune cells are the most relevant cell type to examine telomere length association signals. We validated specific GWAS associations by overexpressing KBTBD6 or POP5 and demonstrated that both lengthened telomeres. CRISPR/Cas9 deletion of the predicted causal regions in K562 blood cells reduced expression of these genes, demonstrating that these loci are related to transcriptional regulation of KBTBD6 and POP5. Our results demonstrate the utility of telomere length GWAS in the identification of telomere length regulation mechanisms and validate KBTBD6 and POP5 as genes affecting telomere length regulation.
Published: 2024

5. Whole-genome sequencing in 333,100 individuals reveals rare non-coding single variant and aggregate associations with height

Author: Hawkes, Gareth, Beaumont, Robin N., Li, Zilin, Mandla, Ravi, Li, Xihao, Albert, Christine M., Arnett, Donna K., Ashley-Koch, Allison E., Ashrani, Aneel A., Barnes, Kathleen C., Boerwinkle, Eric, Brody, Jennifer A., Carson, April P., Chami, Nathalie, Chen, Yii-Der Ida, Chung, Mina K., Curran, Joanne E., Darbar, Dawood, Ellinor, Patrick T., Fornage, Myrian, Gordeuk, Victor R., Guo, Xiuqing, He, Jiang, Hwu, Chii-Min, Kalyani, Rita R., Kaplan, Robert, Kardia, Sharon L. R., Kooperberg, Charles, Loos, Ruth J. F., Lubitz, Steven A., Minster, Ryan L., Naseri, Take, Viali, Satupa’itea, Mitchell, Braxton D., Murabito, Joanne M., Palmer, Nicholette D., Psaty, Bruce M., Redline, Susan, Shoemaker, M. Benjamin, Silverman, Edwin K., Telen, Marilyn J., Weiss, Scott T., Yanek, Lisa R., Zhou, Hufeng, Liu, Ching-Ti, North, Kari E., Justice, Anne E., Locke, Jonathan M., Owens, Nick, Murray, Anna, Patel, Kashyap, Frayling, Timothy M., Wright, Caroline F., Wood, Andrew R., Lin, Xihong, Manning, Alisa, and Weedon, Michael N.
Published: 2024
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6. Mosaic chromosomal alterations in blood across ancestries using whole-genome sequencing.

Author: Jakubek, Yasminka, Zhou, Ying, Stilp, Adrienne, Bacon, Jason, Wong, Justin, Ozcan, Zuhal, Arnett, Donna, Barnes, Kathleen, Bis, Joshua, Boerwinkle, Eric, Brody, Jennifer, Carson, April, Chasman, Daniel, Chen, Jiawen, Cho, Michael, Conomos, Matthew, Cox, Nancy, Doyle, Margaret, Fornage, Myriam, Guo, Xiuqing, Kardia, Sharon, Lewis, Joshua, Loos, Ruth, Ma, Xiaolong, Machiela, Mitchell, Mack, Taralynn, Mathias, Rasika, Mitchell, Braxton, Mychaleckyj, Josyf, North, Kari, Pankratz, Nathan, Peyser, Patricia, Preuss, Michael, Psaty, Bruce, Raffield, Laura, Vasan, Ramachandran, Redline, Susan, Rich, Stephen, Silverman, Edwin, Smith, Jennifer, Smith, Aaron, Taub, Margaret, Taylor, Kent, Yun, Jeong, Li, Yun, Desai, Pinkal, Bick, Alexander, Reiner, Alexander, Scheet, Paul, Auer, Paul, and Rotter, Jerome
Subjects: Humans, Black People, Genome-Wide Association Study, Hispanic or Latino, Precision Medicine, Mosaicism, Genome, Human
Abstract: Megabase-scale mosaic chromosomal alterations (mCAs) in blood are prognostic markers for a host of human diseases. Here, to gain a better understanding of mCA rates in genetically diverse populations, we analyzed whole-genome sequencing data from 67,390 individuals from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program. We observed higher sensitivity with whole-genome sequencing data, compared with array-based data, in uncovering mCAs at low mutant cell fractions and found that individuals of European ancestry have the highest rates of autosomal mCAs and the lowest rates of chromosome X mCAs, compared with individuals of African or Hispanic ancestry. Although further studies in diverse populations will be needed to replicate our findings, we report three loci associated with loss of chromosome X, associations between autosomal mCAs and rare variants in DCPS, ADM17, PPP1R16B and TET2 and ancestry-specific variants in ATM and MPL with mCAs in cis.
Published: 2023

7. Cumulative socioeconomic status and incident type 2 diabetes among African American adults from the Jackson heart study.

Author: Glover, LáShauntá M, Martin, Chantel L, Green-Howard, Annie, Adatorwovor, Reuben, Loehr, Laura, Staley-Salil, Brooke, North, Kari E, and Sims, Mario
Subjects: Clinical Research, Obesity, Aging, Cardiovascular, Behavioral and Social Science, Diabetes, Prevention, Metabolic and endocrine, Public Health and Health Services
Abstract: BackgroundThe cumulative socioeconomic status (SES) model posits that childhood and adult experiences accumulate to influence disease risk. While individual SES indicators such as education and income are independently associated with incident type 2 diabetes (T2D), the association of cumulative SES and incident T2D is unclear, especially in African American adults.MethodsWe utilized cohort data of African American participants (n = 3681, mean age 52.6 years) enrolled in the Jackson Heart Study from 2000 to 2013 free of T2D or cardiovascular disease at baseline (2000-2004). Cumulative SES scores at baseline were derived using six SES indicators (education, wealth, income, occupation, employment status, and mother's education) categorized as low, middle, and high. Incident T2D was defined at exam 2 (2005-2008) or exam 3 (2009-2013) based on fasting glucose ≥126 mg/dL, HbA1c ≥ 6.5, reported diabetic medication use, or self-reported physician diagnosis. Proportional hazards regression, allowing for interval censoring, was used to estimate the association between cumulative SES and incident T2D (hazard ratio(HR), 95% confidence interval (CI)) after adjustment for covariates. Sex and age differences were tested using interaction terms.ResultsThere were 544 incident T2D cases. The association between low (versus high) cumulative SES and incident T2D was not significant (HR 1.04 [95% CI 0.85, 1.28]) and did not differ by sex (p value for interaction>0.05). However, there were differences by (age p value for interaction = 0.0052 for middle-aged adults and 0.0186 for older adults). Low (versus high) cumulative SES was associated a greater hazard of incident T2D among those 20-46 years (HR 1.12 [95% CI 1.03, 1.21]), 47-59 years (HR 1.25 [95% CI 1.06, 1.47]) and those 60-93 years (HR 1.39 [95% CI 1.09, 1.78]) after adjustment for sex and family history of diabetes. Associations attenuated after adding behavioral and lifestyle risk factors.ConclusionThe association of low cumulative SES and incident T2D differed by age, which may suggest interventionist should consider impacts of SES on T2D by age.
Published: 2023

8. Investigating Gene-Diet Interactions Impacting the Association Between Macronutrient Intake and Glycemic Traits.

Author: Westerman, Kenneth E, Walker, Maura E, Gaynor, Sheila M, Wessel, Jennifer, DiCorpo, Daniel, Ma, Jiantao, Alonso, Alvaro, Aslibekyan, Stella, Baldridge, Abigail S, Bertoni, Alain G, Biggs, Mary L, Brody, Jennifer A, Chen, Yii-Der Ida, Dupuis, Joseé, Goodarzi, Mark O, Guo, Xiuqing, Hasbani, Natalie R, Heath, Adam, Hidalgo, Bertha, Irvin, Marguerite R, Johnson, W Craig, Kalyani, Rita R, Lange, Leslie, Lemaitre, Rozenn N, Liu, Ching-Ti, Liu, Simin, Moon, Jee-Young, Nassir, Rami, Pankow, James S, Pettinger, Mary, Raffield, Laura M, Rasmussen-Torvik, Laura J, Selvin, Elizabeth, Senn, Mackenzie K, Shadyab, Aladdin H, Smith, Albert V, Smith, Nicholas L, Steffen, Lyn, Talegakwar, Sameera, Taylor, Kent D, de Vries, Paul S, Wilson, James G, Wood, Alexis C, Yanek, Lisa R, Yao, Jie, Zheng, Yinan, Boerwinkle, Eric, Morrison, Alanna C, Fornage, Miriam, Russell, Tracy P, Psaty, Bruce M, Levy, Daniel, Heard-Costa, Nancy L, Ramachandran, Vasan S, Mathias, Rasika A, Arnett, Donna K, Kaplan, Robert, North, Kari E, Correa, Adolfo, Carson, April, Rotter, Jerome I, Rich, Stephen S, Manson, JoAnn E, Reiner, Alexander P, Kooperberg, Charles, Florez, Jose C, Meigs, James B, Merino, Jordi, Tobias, Deirdre K, Chen, Han, and Manning, Alisa K
Subjects: Biomedical and Clinical Sciences, Nutrition and Dietetics, Nutrition, Diabetes, Human Genome, Minority Health, Genetics, Cardiovascular, Health Disparities, Prevention, Precision Medicine, Clinical Research, Metabolic and endocrine, Good Health and Well Being, Humans, Glycated Hemoglobin, Diet, Diabetes Mellitus, Eating, Guanine Nucleotide Dissociation Inhibitors, Genome-Wide Association Study, Medical and Health Sciences, Endocrinology & Metabolism, Biomedical and clinical sciences
Abstract: Few studies have demonstrated reproducible gene-diet interactions (GDIs) impacting metabolic disease risk factors, likely due in part to measurement error in dietary intake estimation and insufficient capture of rare genetic variation. We aimed to identify GDIs across the genetic frequency spectrum impacting the macronutrient-glycemia relationship in genetically and culturally diverse cohorts. We analyzed 33,187 participants free of diabetes from 10 National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program cohorts with whole-genome sequencing, self-reported diet, and glycemic trait data. We fit cohort-specific, multivariable-adjusted linear mixed models for the effect of diet, modeled as an isocaloric substitution of carbohydrate for fat, and its interactions with common and rare variants genome-wide. In main effect meta-analyses, participants consuming more carbohydrate had modestly lower glycemic trait values (e.g., for glycated hemoglobin [HbA1c], -0.013% HbA1c/250 kcal substitution). In GDI meta-analyses, a common African ancestry-enriched variant (rs79762542) reached study-wide significance and replicated in the UK Biobank cohort, indicating a negative carbohydrate-HbA1c association among major allele homozygotes only. Simulations revealed that >150,000 samples may be necessary to identify similar macronutrient GDIs under realistic assumptions about effect size and measurement error. These results generate hypotheses for further exploration of modifiable metabolic disease risk in additional cohorts with African ancestry.Article highlightsWe aimed to identify genetic modifiers of the dietary macronutrient-glycemia relationship using whole-genome sequence data from 10 Trans-Omics for Precision Medicine program cohorts. Substitution models indicated a modest reduction in glycemia associated with an increase in dietary carbohydrate at the expense of fat. Genome-wide interaction analysis identified one African ancestry-enriched variant near the FRAS1 gene that may interact with macronutrient intake to influence hemoglobin A1c. Simulation-based power calculations accounting for measurement error suggested that substantially larger sample sizes may be necessary to discover further gene-macronutrient interactions.
Published: 2023

9. Causal effects on complex traits are similar for common variants across segments of different continental ancestries within admixed individuals.

Author: Mester, Rachel, Belbin, Gillian, Buyske, Steve, Conti, David, Darst, Burcu, Fornage, Myriam, Gignoux, Chris, Guo, Xiuqing, Haiman, Christopher, Kenny, Eimear, Kim, Michelle, Kooperberg, Charles, Lange, Leslie, Manichaikul, Ani, North, Kari, Peters, Ulrike, Rasmussen-Torvik, Laura, Rich, Stephen, Hou, Kangcheng, Ding, Yi, Xu, Ziqi, Wu, Yue, Wheeler, Heather, Wojcik, Genevieve, Zhou, Ying, Sankararaman, Sriram, Pasaniuc, Bogdan, Rotter, Jerome, and Bhattacharya, Arjun
Subjects: Humans, Genetics, Population, Multifactorial Inheritance, Genome-Wide Association Study, Racial Groups, Black or African American, Polymorphism, Single Nucleotide
Abstract: Individuals of admixed ancestries (for example, African Americans) inherit a mosaic of ancestry segments (local ancestry) originating from multiple continental ancestral populations. This offers the unique opportunity of investigating the similarity of genetic effects on traits across ancestries within the same population. Here we introduce an approach to estimate correlation of causal genetic effects (radmix) across local ancestries and analyze 38 complex traits in African-European admixed individuals (N = 53,001) to observe very high correlations (meta-analysis radmix = 0.95, 95% credible interval 0.93-0.97), much higher than correlation of causal effects across continental ancestries. We replicate our results using regression-based methods from marginal genome-wide association study summary statistics. We also report realistic scenarios where regression-based methods yield inflated heterogeneity-by-ancestry due to ancestry-specific tagging of causal effects, and/or polygenicity. Our results motivate genetic analyses that assume minimal heterogeneity in causal effects by ancestry, with implications for the inclusion of ancestry-diverse individuals in studies.
Published: 2023

10. Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Author: Suzuki, Ken, Hatzikotoulas, Konstantinos, Southam, Lorraine, Taylor, Henry J., Yin, Xianyong, Lorenz, Kim M., Mandla, Ravi, Huerta-Chagoya, Alicia, Melloni, Giorgio E. M., Kanoni, Stavroula, Rayner, Nigel W., Bocher, Ozvan, Arruda, Ana Luiza, Sonehara, Kyuto, Namba, Shinichi, Lee, Simon S. K., Preuss, Michael H., Petty, Lauren E., Schroeder, Philip, Vanderwerff, Brett, Kals, Mart, Bragg, Fiona, Lin, Kuang, Guo, Xiuqing, Zhang, Weihua, Yao, Jie, Kim, Young Jin, Graff, Mariaelisa, Takeuchi, Fumihiko, Nano, Jana, Lamri, Amel, Nakatochi, Masahiro, Moon, Sanghoon, Scott, Robert A., Cook, James P., Lee, Jung-Jin, Pan, Ian, Taliun, Daniel, Parra, Esteban J., Chai, Jin-Fang, Bielak, Lawrence F., Tabara, Yasuharu, Hai, Yang, Thorleifsson, Gudmar, Grarup, Niels, Sofer, Tamar, Wuttke, Matthias, Sarnowski, Chloé, Gieger, Christian, Nousome, Darryl, Trompet, Stella, Kwak, Soo-Heon, Long, Jirong, Sun, Meng, Tong, Lin, Chen, Wei-Min, Nongmaithem, Suraj S., Noordam, Raymond, Lim, Victor J. Y., Tam, Claudia H. T., Joo, Yoonjung Yoonie, Chen, Chien-Hsiun, Raffield, Laura M., Prins, Bram Peter, Nicolas, Aude, Yanek, Lisa R., Chen, Guanjie, Brody, Jennifer A., Kabagambe, Edmond, An, Ping, Xiang, Anny H., Choi, Hyeok Sun, Cade, Brian E., Tan, Jingyi, Broadaway, K. Alaine, Williamson, Alice, Kamali, Zoha, Cui, Jinrui, Thangam, Manonanthini, Adair, Linda S., Adeyemo, Adebowale, Aguilar-Salinas, Carlos A., Ahluwalia, Tarunveer S., Anand, Sonia S., Bertoni, Alain, Bork-Jensen, Jette, Brandslund, Ivan, Buchanan, Thomas A., Burant, Charles F., Butterworth, Adam S., Canouil, Mickaël, Chan, Juliana C. N., Chang, Li-Ching, Chee, Miao-Li, Chen, Ji, Chen, Shyh-Huei, Chen, Yuan-Tsong, Chen, Zhengming, Chuang, Lee-Ming, Cushman, Mary, Danesh, John, Das, Swapan K., de Silva, H. Janaka, Dedoussis, George, Dimitrov, Latchezar, Doumatey, Ayo P., Du, Shufa, Duan, Qing, Eckardt, Kai-Uwe, Emery, Leslie S., Evans, Daniel S., Evans, Michele K., Fischer, Krista, Floyd, James S., Ford, Ian, Franco, Oscar H., Frayling, Timothy M., Freedman, Barry I., Genter, Pauline, Gerstein, Hertzel C., Giedraitis, Vilmantas, González-Villalpando, Clicerio, González-Villalpando, Maria Elena, Gordon-Larsen, Penny, Gross, Myron, Guare, Lindsay A., Hackinger, Sophie, Hakaste, Liisa, Han, Sohee, Hattersley, Andrew T., Herder, Christian, Horikoshi, Momoko, Howard, Annie-Green, Hsueh, Willa, Huang, Mengna, Huang, Wei, Hung, Yi-Jen, Hwang, Mi Yeong, Hwu, Chii-Min, Ichihara, Sahoko, Ikram, Mohammad Arfan, Ingelsson, Martin, Islam, Md. Tariqul, Isono, Masato, Jang, Hye-Mi, Jasmine, Farzana, Jiang, Guozhi, Jonas, Jost B., Jørgensen, Torben, Kamanu, Frederick K., Kandeel, Fouad R., Kasturiratne, Anuradhani, Katsuya, Tomohiro, Kaur, Varinderpal, Kawaguchi, Takahisa, Keaton, Jacob M., Kho, Abel N., Khor, Chiea-Chuen, Kibriya, Muhammad G., Kim, Duk-Hwan, Kronenberg, Florian, Kuusisto, Johanna, Läll, Kristi, Lange, Leslie A., Lee, Kyung Min, Lee, Myung-Shik, Lee, Nanette R., Leong, Aaron, Li, Liming, Li, Yun, Li-Gao, Ruifang, Ligthart, Symen, Lindgren, Cecilia M., Linneberg, Allan, Liu, Ching-Ti, Liu, Jianjun, Locke, Adam E., Louie, Tin, Luan, Jian’an, Luk, Andrea O., Luo, Xi, Lv, Jun, Lynch, Julie A., Lyssenko, Valeriya, Maeda, Shiro, Mamakou, Vasiliki, Mansuri, Sohail Rafik, Matsuda, Koichi, Meitinger, Thomas, Melander, Olle, Metspalu, Andres, Mo, Huan, Morris, Andrew D., Moura, Filipe A., Nadler, Jerry L., Nalls, Michael A., Nayak, Uma, Ntalla, Ioanna, Okada, Yukinori, Orozco, Lorena, Patel, Sanjay R., Patil, Snehal, Pei, Pei, Pereira, Mark A., Peters, Annette, Pirie, Fraser J., Polikowsky, Hannah G., Porneala, Bianca, Prasad, Gauri, Rasmussen-Torvik, Laura J., Reiner, Alexander P., Roden, Michael, Rohde, Rebecca, Roll, Katheryn, Sabanayagam, Charumathi, Sandow, Kevin, Sankareswaran, Alagu, Sattar, Naveed, Schönherr, Sebastian, Shahriar, Mohammad, Shen, Botong, Shi, Jinxiu, Shin, Dong Mun, Shojima, Nobuhiro, Smith, Jennifer A., So, Wing Yee, Stančáková, Alena, Steinthorsdottir, Valgerdur, Stilp, Adrienne M., Strauch, Konstantin, Taylor, Kent D., Thorand, Barbara, Thorsteinsdottir, Unnur, Tomlinson, Brian, Tran, Tam C., Tsai, Fuu-Jen, Tuomilehto, Jaakko, Tusie-Luna, Teresa, Udler, Miriam S., Valladares-Salgado, Adan, van Dam, Rob M., van Klinken, Jan B., Varma, Rohit, Wacher-Rodarte, Niels, Wheeler, Eleanor, Wickremasinghe, Ananda R., van Dijk, Ko Willems, Witte, Daniel R., Yajnik, Chittaranjan S., Yamamoto, Ken, Yamamoto, Kenichi, Yoon, Kyungheon, Yu, Canqing, Yuan, Jian-Min, Yusuf, Salim, Zawistowski, Matthew, Zhang, Liang, Zheng, Wei, Raffel, Leslie J., Igase, Michiya, Ipp, Eli, Redline, Susan, Cho, Yoon Shin, Lind, Lars, Province, Michael A., Fornage, Myriam, Hanis, Craig L., Ingelsson, Erik, Zonderman, Alan B., Psaty, Bruce M., Wang, Ya-Xing, Rotimi, Charles N., Becker, Diane M., Matsuda, Fumihiko, Liu, Yongmei, Yokota, Mitsuhiro, Kardia, Sharon L. R., Peyser, Patricia A., Pankow, James S., Engert, James C., Bonnefond, Amélie, Froguel, Philippe, Wilson, James G., Sheu, Wayne H. H., Wu, Jer-Yuarn, Hayes, M. Geoffrey, Ma, Ronald C. W., Wong, Tien-Yin, Mook-Kanamori, Dennis O., Tuomi, Tiinamaija, Chandak, Giriraj R., Collins, Francis S., Bharadwaj, Dwaipayan, Paré, Guillaume, Sale, Michèle M., Ahsan, Habibul, Motala, Ayesha A., Shu, Xiao-Ou, Park, Kyong-Soo, Jukema, J. Wouter, Cruz, Miguel, Chen, Yii-Der Ida, Rich, Stephen S., McKean-Cowdin, Roberta, Grallert, Harald, Cheng, Ching-Yu, Ghanbari, Mohsen, Tai, E-Shyong, Dupuis, Josee, Kato, Norihiro, Laakso, Markku, Köttgen, Anna, Koh, Woon-Puay, Bowden, Donald W., Palmer, Colin N. A., Kooner, Jaspal S., Kooperberg, Charles, Liu, Simin, North, Kari E., Saleheen, Danish, Hansen, Torben, Pedersen, Oluf, Wareham, Nicholas J., Lee, Juyoung, Kim, Bong-Jo, Millwood, Iona Y., Walters, Robin G., Stefansson, Kari, Ahlqvist, Emma, Goodarzi, Mark O., Mohlke, Karen L., Langenberg, Claudia, Haiman, Christopher A., Loos, Ruth J. F., Florez, Jose C., Rader, Daniel J., Ritchie, Marylyn D., Zöllner, Sebastian, Mägi, Reedik, Marston, Nicholas A., Ruff, Christian T., van Heel, David A., Finer, Sarah, Denny, Joshua C., Yamauchi, Toshimasa, Kadowaki, Takashi, Chambers, John C., Ng, Maggie C. Y., Sim, Xueling, Below, Jennifer E., Tsao, Philip S., Chang, Kyong-Mi, McCarthy, Mark I., Meigs, James B., Mahajan, Anubha, Spracklen, Cassandra N., Mercader, Josep M., Boehnke, Michael, Rotter, Jerome I., Vujkovic, Marijana, Voight, Benjamin F., Morris, Andrew P., and Zeggini, Eleftheria
Published: 2024
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11. Whole-exome sequencing study identifies four novel gene loci associated with diabetic kidney disease.

Author: Pan, Yang, Sun, Xiao, Mi, Xuenan, Huang, Zhijie, Hsu, Yenchih, Hixson, James, Munzy, Donna, Metcalf, Ginger, Franceschini, Nora, Tin, Adrienne, Köttgen, Anna, Francis, Michael, Brody, Jennifer, Kestenbaum, Bryan, Sitlani, Colleen, Mychaleckyj, Josyf, Kramer, Holly, Lange, Leslie, Guo, Xiuqing, Hwang, Shih-Jen, Irvin, Marguerite, Smith, Jennifer, Yanek, Lisa, Vaidya, Dhananjay, Chen, Yii-Der, Fornage, Myriam, Lloyd-Jones, Donald, Hou, Lifang, Mathias, Rasika, Mitchell, Braxton, Peyser, Patricia, Kardia, Sharon, Arnett, Donna, Correa, Adolfo, Raffield, Laura, Vasan, Ramachandran, Cupple, L, Levy, Daniel, Kaplan, Robert, North, Kari, Kooperberg, Charles, Reiner, Alexander, Psaty, Bruce, Tracy, Russell, Gibbs, Richard, Morrison, Alanna, Feldman, Harold, Boerwinkle, Eric, He, Jiang, Kelly, Tanika, and Rotter, Jerome
Subjects: Humans, Aminopeptidases, Diabetes Mellitus, Diabetic Nephropathies, Exome Sequencing, Kidney, Renal Insufficiency, Chronic
Abstract: Diabetic kidney disease (DKD) is recognized as an important public health challenge. However, its genomic mechanisms are poorly understood. To identify rare variants for DKD, we conducted a whole-exome sequencing (WES) study leveraging large cohorts well-phenotyped for chronic kidney disease and diabetes. Our two-stage WES study included 4372 European and African ancestry participants from the Chronic Renal Insufficiency Cohort and Atherosclerosis Risk in Communities studies (stage 1) and 11 487 multi-ancestry Trans-Omics for Precision Medicine participants (stage 2). Generalized linear mixed models, which accounted for genetic relatedness and adjusted for age, sex and ancestry, were used to test associations between single variants and DKD. Gene-based aggregate rare variant analyses were conducted using an optimized sequence kernel association test implemented within our mixed model framework. We identified four novel exome-wide significant DKD-related loci through initiating diabetes. In single-variant analyses, participants carrying a rare, in-frame insertion in the DIS3L2 gene (rs141560952) exhibited a 193-fold increased odds [95% confidence interval (CI): 33.6, 1105] of DKD compared with noncarriers (P = 3.59 × 10-9). Likewise, each copy of a low-frequency KRT6B splice-site variant (rs425827) conferred a 5.31-fold higher odds (95% CI: 3.06, 9.21) of DKD (P = 2.72 × 10-9). Aggregate gene-based analyses further identified ERAP2 (P = 4.03 × 10-8) and NPEPPS (P = 1.51 × 10-7), which are both expressed in the kidney and implicated in renin-angiotensin-aldosterone system modulated immune response. In the largest WES study of DKD, we identified novel rare variant loci attaining exome-wide significance. These findings provide new insights into the molecular mechanisms underlying DKD.
Published: 2023

12. Multi-ancestry transcriptome-wide association analyses yield insights into tobacco use biology and drug repurposing

Author: Chen, Fang, Wang, Xingyan, Jang, Seon-Kyeong, Quach, Bryan C, Weissenkampen, J Dylan, Khunsriraksakul, Chachrit, Yang, Lina, Sauteraud, Renan, Albert, Christine M, Allred, Nicholette DD, Arnett, Donna K, Ashley-Koch, Allison E, Barnes, Kathleen C, Barr, R Graham, Becker, Diane M, Bielak, Lawrence F, Bis, Joshua C, Blangero, John, Boorgula, Meher Preethi, Chasman, Daniel I, Chavan, Sameer, Chen, Yii-Der I, Chuang, Lee-Ming, Correa, Adolfo, Curran, Joanne E, David, Sean P, Fuentes, Lisa de las, Deka, Ranjan, Duggirala, Ravindranath, Faul, Jessica D, Garrett, Melanie E, Gharib, Sina A, Guo, Xiuqing, Hall, Michael E, Hawley, Nicola L, He, Jiang, Hobbs, Brian D, Hokanson, John E, Hsiung, Chao A, Hwang, Shih-Jen, Hyde, Thomas M, Irvin, Marguerite R, Jaffe, Andrew E, Johnson, Eric O, Kaplan, Robert, Kardia, Sharon LR, Kaufman, Joel D, Kelly, Tanika N, Kleinman, Joel E, Kooperberg, Charles, Lee, I-Te, Levy, Daniel, Lutz, Sharon M, Manichaikul, Ani W, Martin, Lisa W, Marx, Olivia, McGarvey, Stephen T, Minster, Ryan L, Moll, Matthew, Moussa, Karine A, Naseri, Take, North, Kari E, Oelsner, Elizabeth C, Peralta, Juan M, Peyser, Patricia A, Psaty, Bruce M, Rafaels, Nicholas, Raffield, Laura M, Reupena, Muagututi’a Sefuiva, Rich, Stephen S, Rotter, Jerome I, Schwartz, David A, Shadyab, Aladdin H, Sheu, Wayne H-H, Sims, Mario, Smith, Jennifer A, Sun, Xiao, Taylor, Kent D, Telen, Marilyn J, Watson, Harold, Weeks, Daniel E, Weir, David R, Yanek, Lisa R, Young, Kendra A, Young, Kristin L, Zhao, Wei, Hancock, Dana B, Jiang, Bibo, Vrieze, Scott, and Liu, Dajiang J
Subjects: Genetics, Tobacco, Drug Abuse (NIDA only), Tobacco Smoke and Health, Substance Misuse, Brain Disorders, Human Genome, Good Health and Well Being, Humans, Transcriptome, Drug Repositioning, Genome-Wide Association Study, Tobacco Use, Biology, Polymorphism, Single Nucleotide, Genetic Predisposition to Disease, Biological Sciences, Medical and Health Sciences, 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.
Published: 2023

13. Natural selection of immune and metabolic genes associated with health in two lowland Bolivian populations

Author: Lea, Amanda J, Garcia, Angela, Arevalo, Jesusa, Ayroles, Julien F, Buetow, Kenneth, Cole, Steve W, Rodriguez, Daniel Eid, Gutierrez, Maguin, Highland, Heather M, Hooper, Paul L, Justice, Anne, Kraft, Thomas, North, Kari E, Stieglitz, Jonathan, Kaplan, Hillard, Trumble, Benjamin C, and Gurven, Michael D
Subjects: Human Genome, Genetics, Biotechnology, Clinical Research, 2.1 Biological and endogenous factors, Aetiology, Generic health relevance, Good Health and Well Being, Humans, Bolivia, Genome, Genotype, Genomics, Phenotype, Biomarkers, Selection, Genetic, Polymorphism, Single Nucleotide, natural selection, evolution, Tsimane, genotype-phenotype, health, genotype–phenotype, Health Status, Genetics, Population, Genome, Human
Abstract: A growing body of work has addressed human adaptations to diverse environments using genomic data, but few studies have connected putatively selected alleles to phenotypes, much less among underrepresented populations such as Amerindians. Studies of natural selection and genotype-phenotype relationships in underrepresented populations hold potential to uncover previously undescribed loci underlying evolutionarily and biomedically relevant traits. Here, we worked with the Tsimane and the Moseten, two Amerindian populations inhabiting the Bolivian lowlands. We focused most intensively on the Tsimane, because long-term anthropological work with this group has shown that they have a high burden of both macro and microparasites, as well as minimal cardiometabolic disease or dementia. We therefore generated genome-wide genotype data for Tsimane individuals to study natural selection, and paired this with blood mRNA-seq as well as cardiometabolic and immune biomarker data generated from a larger sample that included both populations. In the Tsimane, we identified 21 regions that are candidates for selective sweeps, as well as 5 immune traits that show evidence for polygenic selection (e.g., C-reactive protein levels and the response to coronaviruses). Genes overlapping candidate regions were strongly enriched for known involvement in immune-related traits, such as abundance of lymphocytes and eosinophils. Importantly, we were also able to draw on extensive phenotype information for the Tsimane and Moseten and link five regions (containing PSD4, MUC21 and MUC22, TOX2, ANXA6, and ABCA1) with biomarkers of immune and metabolic function. Together, our work highlights the utility of pairing evolutionary analyses with anthropological and biomedical data to gain insight into the genetic basis of health-related traits.
Published: 2023

14. Whole-exome sequence analysis of anthropometric traits illustrates challenges in identifying effects of rare genetic variants

Author: Young, Kristin L, Fisher, Virginia, Deng, Xuan, Brody, Jennifer A, Graff, Misa, Lim, Elise, Lin, Bridget M, Xu, Hanfei, Amin, Najaf, An, Ping, Aslibekyan, Stella, Fohner, Alison E, Hidalgo, Bertha, Lenzini, Petra, Kraaij, Robert, Medina-Gomez, Carolina, Prokić, Ivana, Rivadeneira, Fernando, Sitlani, Colleen, Tao, Ran, van Rooij, Jeroen, Zhang, Di, Broome, Jai G, Buth, Erin J, Heavner, Benjamin D, Jain, Deepti, Smith, Albert V, Barnes, Kathleen, Boorgula, Meher Preethi, Chavan, Sameer, Darbar, Dawood, De Andrade, Mariza, Guo, Xiuqing, Haessler, Jeffrey, Irvin, Marguerite R, Kalyani, Rita R, Kardia, Sharon LR, Kooperberg, Charles, Kim, Wonji, Mathias, Rasika A, McDonald, Merry-Lynn, Mitchell, Braxton D, Peyser, Patricia A, Regan, Elizabeth A, Redline, Susan, Reiner, Alexander P, Rich, Stephen S, Rotter, Jerome I, Smith, Jennifer A, Weiss, Scott, Wiggins, Kerri L, Yanek, Lisa R, Arnett, Donna, Heard-Costa, Nancy L, Leal, Suzanne, Lin, Danyu, McKnight, Barbara, Province, Michael, van Duijn, Cornelia M, North, Kari E, Cupples, L Adrienne, and Liu, Ching-Ti
Subjects: Biological Sciences, Genetics, Clinical Research, Biotechnology, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Generic health relevance, Good Health and Well Being, Humans, Genome-Wide Association Study, Exome, Body Mass Index, Quantitative Trait Loci, Anthropometry, Intercellular Signaling Peptides and Proteins, Cell Cycle Proteins, body mass index, central obesity, exome sequencing, height
Abstract: Anthropometric traits, measuring body size and shape, are highly heritable and significant clinical risk factors for cardiometabolic disorders. These traits have been extensively studied in genome-wide association studies (GWASs), with hundreds of genome-wide significant loci identified. We performed a whole-exome sequence analysis of the genetics of height, body mass index (BMI) and waist/hip ratio (WHR). We meta-analyzed single-variant and gene-based associations of whole-exome sequence variation with height, BMI, and WHR in up to 22,004 individuals, and we assessed replication of our findings in up to 16,418 individuals from 10 independent cohorts from Trans-Omics for Precision Medicine (TOPMed). We identified four trait associations with single-nucleotide variants (SNVs; two for height and two for BMI) and replicated the LECT2 gene association with height. Our expression quantitative trait locus (eQTL) analysis within previously reported GWAS loci implicated CEP63 and RFT1 as potential functional genes for known height loci. We further assessed enrichment of SNVs, which were monogenic or syndromic variants within loci associated with our three traits. This led to the significant enrichment results for height, whereas we observed no Bonferroni-corrected significance for all SNVs. With a sample size of ∼20,000 whole-exome sequences in our discovery dataset, our findings demonstrate the importance of genomic sequencing in genetic association studies, yet they also illustrate the challenges in identifying effects of rare genetic variants.
Published: 2023

15. Rare coding variants in RCN3 are associated with blood pressure

Author: He, Karen Y, Kelly, Tanika N, Wang, Heming, Liang, Jingjing, Zhu, Luke, Cade, Brian E, Assimes, Themistocles L, Becker, Lewis C, Beitelshees, Amber L, Bielak, Lawrence F, Bress, Adam P, Brody, Jennifer A, Chang, Yen-Pei Christy, Chang, Yi-Cheng, de Vries, Paul S, Duggirala, Ravindranath, Fox, Ervin R, Franceschini, Nora, Furniss, Anna L, Gao, Yan, Guo, Xiuqing, Haessler, Jeffrey, Hung, Yi-Jen, Hwang, Shih-Jen, Irvin, Marguerite Ryan, Kalyani, Rita R, Liu, Ching-Ti, Liu, Chunyu, Martin, Lisa Warsinger, Montasser, May E, Muntner, Paul M, Mwasongwe, Stanford, Naseri, Take, Palmas, Walter, Reupena, Muagututi’a Sefuiva, Rice, Kenneth M, Sheu, Wayne H-H, Shimbo, Daichi, Smith, Jennifer A, Snively, Beverly M, Yanek, Lisa R, Zhao, Wei, Blangero, John, Boerwinkle, Eric, Chen, Yii-Der Ida, Correa, Adolfo, Cupples, L Adrienne, Curran, Joanne E, Fornage, Myriam, He, Jiang, Hou, Lifang, Kaplan, Robert C, Kardia, Sharon LR, Kenny, Eimear E, Kooperberg, Charles, Lloyd-Jones, Donald, Loos, Ruth JF, Mathias, Rasika A, McGarvey, Stephen T, Mitchell, Braxton D, North, Kari E, Peyser, Patricia A, Psaty, Bruce M, Raffield, Laura M, Rao, DC, Redline, Susan, Reiner, Alex P, Rich, Stephen S, Rotter, Jerome I, Taylor, Kent D, Tracy, Russell, Vasan, Ramachandran S, Morrison, Alanna C, Levy, Daniel, Chakravarti, Aravinda, Arnett, Donna K, and Zhu, Xiaofeng
Subjects: Biological Sciences, Genetics, Cardiovascular, Human Genome, Clinical Research, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Blood Pressure, Genetic Linkage, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Precision Medicine, Whole Genome Sequencing, Rare variant analysis, Blood pressure, Whole genome sequencing, Samoan Obesity, Lifestyle and Genetic Adaptations Study (OLaGA) Group, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Information and Computing Sciences, Medical and Health Sciences, Bioinformatics, Biological sciences, Biomedical and clinical sciences
Abstract: BackgroundWhile large genome-wide association studies have identified nearly one thousand loci associated with variation in blood pressure, rare variant identification is still a challenge. In family-based cohorts, genome-wide linkage scans have been successful in identifying rare genetic variants for blood pressure. This study aims to identify low frequency and rare genetic variants within previously reported linkage regions on chromosomes 1 and 19 in African American families from the Trans-Omics for Precision Medicine (TOPMed) program. Genetic association analyses weighted by linkage evidence were completed with whole genome sequencing data within and across TOPMed ancestral groups consisting of 60,388 individuals of European, African, East Asian, Hispanic, and Samoan ancestries.ResultsAssociations of low frequency and rare variants in RCN3 and multiple other genes were observed for blood pressure traits in TOPMed samples. The association of low frequency and rare coding variants in RCN3 was further replicated in UK Biobank samples (N = 403,522), and reached genome-wide significance for diastolic blood pressure (p = 2.01 × 10- 7).ConclusionsLow frequency and rare variants in RCN3 contributes blood pressure variation. This study demonstrates that focusing association analyses in linkage regions greatly reduces multiple-testing burden and improves power to identify novel rare variants associated with blood pressure traits.
Published: 2022

16. Rare genetic variants explain missing heritability in smoking.

Author: Jang, Seon-Kyeong, Evans, Luke, Fialkowski, Allison, Arnett, Donna K, Ashley-Koch, Allison E, Barnes, Kathleen C, Becker, Diane M, Bis, Joshua C, Blangero, John, Bleecker, Eugene R, Boorgula, Meher Preethi, Bowden, Donald W, Brody, Jennifer A, Cade, Brian E, Jenkins, Brenda W Campbell, Carson, April P, Chavan, Sameer, Cupples, L Adrienne, Custer, Brian, Damrauer, Scott M, David, Sean P, de Andrade, Mariza, Dinardo, Carla L, Fingerlin, Tasha E, Fornage, Myriam, Freedman, Barry I, Garrett, Melanie E, Gharib, Sina A, Glahn, David C, Haessler, Jeffrey, Heckbert, Susan R, Hokanson, John E, Hou, Lifang, Hwang, Shih-Jen, Hyman, Matthew C, Judy, Renae, Justice, Anne E, Kaplan, Robert C, Kardia, Sharon LR, Kelly, Shannon, Kim, Wonji, Kooperberg, Charles, Levy, Daniel, Lloyd-Jones, Donald M, Loos, Ruth JF, Manichaikul, Ani W, Gladwin, Mark T, Martin, Lisa Warsinger, Nouraie, Mehdi, Melander, Olle, Meyers, Deborah A, Montgomery, Courtney G, North, Kari E, Oelsner, Elizabeth C, Palmer, Nicholette D, Payton, Marinelle, Peljto, Anna L, Peyser, Patricia A, Preuss, Michael, Psaty, Bruce M, Qiao, Dandi, Rader, Daniel J, Rafaels, Nicholas, Redline, Susan, Reed, Robert M, Reiner, Alexander P, Rich, Stephen S, Rotter, Jerome I, Schwartz, David A, Shadyab, Aladdin H, Silverman, Edwin K, Smith, Nicholas L, Smith, J Gustav, Smith, Albert V, Smith, Jennifer A, Tang, Weihong, Taylor, Kent D, Telen, Marilyn J, Vasan, Ramachandran S, Gordeuk, Victor R, Wang, Zhe, Wiggins, Kerri L, Yanek, Lisa R, Yang, Ivana V, Young, Kendra A, Young, Kristin L, Zhang, Yingze, Liu, Dajiang J, Keller, Matthew C, and Vrieze, Scott
Subjects: Smoking, Gene Frequency, Phenotype, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Tobacco, Genetics, Tobacco Smoke and Health, Human Genome, Cancer
Abstract: Common genetic variants explain less variation in complex phenotypes than inferred from family-based studies, and there is a debate on the source of this 'missing heritability'. We investigated the contribution of rare genetic variants to tobacco use with whole-genome sequences from up to 26,257 unrelated individuals of European ancestries and 11,743 individuals of African ancestries. Across four smoking traits, single-nucleotide-polymorphism-based heritability ([Formula: see text]) was estimated from 0.13 to 0.28 (s.e., 0.10-0.13) in European ancestries, with 35-74% of it attributable to rare variants with minor allele frequencies between 0.01% and 1%. These heritability estimates are 1.5-4 times higher than past estimates based on common variants alone and accounted for 60% to 100% of our pedigree-based estimates of narrow-sense heritability ([Formula: see text], 0.18-0.34). In the African ancestry samples, [Formula: see text] was estimated from 0.03 to 0.33 (s.e., 0.09-0.14) across the four smoking traits. These results suggest that rare variants are important contributors to the heritability of smoking.
Published: 2022

17. Genetics of Latin American Diversity Project: Insights into population genetics and association studies in admixed groups in the Americas

Author: Borda, Victor, Loesch, Douglas P., Guo, Bing, Laboulaye, Roland, Veliz-Otani, Diego, French, Jennifer N., Leal, Thiago Peixoto, Gogarten, Stephanie M., Ikpe, Sunday, Gouveia, Mateus H., Mendes, Marla, Abecasis, Gonçalo R., Alvim, Isabela, Arboleda-Bustos, Carlos E., Arboleda, Gonzalo, Arboleda, Humberto, Barreto, Mauricio L., Barwick, Lucas, Bezzera, Marcos A., Blangero, John, Borges, Vanderci, Caceres, Omar, Cai, Jianwen, Chana-Cuevas, Pedro, Chen, Zhanghua, Custer, Brian, Dean, Michael, Dinardo, Carla, Domingos, Igor, Duggirala, Ravindranath, Dieguez, Elena, Fernandez, Willian, Ferraz, Henrique B., Gilliland, Frank, Guio, Heinner, Horta, Bernardo, Curran, Joanne E., Johnsen, Jill M., Kaplan, Robert C., Kelly, Shannon, Kenny, Eimear E., Konkle, Barbara A., Kooperberg, Charles, Lescano, Andres, Lima-Costa, M. Fernanda, Loos, Ruth J.F., Manichaikul, Ani, Meyers, Deborah A., Naslavsky, Michel S., Nickerson, Deborah A., North, Kari E., Padilla, Carlos, Preuss, Michael, Raggio, Victor, Reiner, Alexander P., Rich, Stephen S., Rieder, Carlos R., Rienstra, Michiel, Rotter, Jerome I., Rundek, Tatjana, Sacco, Ralph L., Sanchez, Cesar, Sankaran, Vijay G., Santos-Lobato, Bruno Lopes, Schumacher-Schuh, Artur Francisco, Scliar, Marilia O., Silverman, Edwin K., Sofer, Tamar, Lasky-Su, Jessica, Tumas, Vitor, Weiss, Scott T., Mata, Ignacio F., Hernandez, Ryan D., Tarazona-Santos, Eduardo, and O’Connor, Timothy D.
Published: 2024
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18. Multivariable Mendelian randomization with incomplete measurements on the exposure variables in the Hispanic Community Health Study/Study of Latinos

Author: Li, Yilun, Wong, Kin Yau, Howard, Annie Green, Gordon-Larsen, Penny, Highland, Heather M., Graff, Mariaelisa, North, Kari E., Downie, Carolina G., Avery, Christy L., Yu, Bing, Young, Kristin L., Buchanan, Victoria L., Kaplan, Robert, Hou, Lifang, Joyce, Brian Thomas, Qi, Qibin, Sofer, Tamar, Moon, Jee-Young, and Lin, Dan-Yu
Published: 2024
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19. Advancements in genetic research by the Hispanic Community Health Study/Study of Latinos: A 10-year retrospective review

Author: Rao, Hridya, Weiss, Margaret C., Moon, Jee Young, Perreira, Krista M., Daviglus, Martha L., Kaplan, Robert, North, Kari E., Argos, Maria, Fernández-Rhodes, Lindsay, and Sofer, Tamar
Published: 2025
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20. Assessing efficiency of fine-mapping obesity-associated variants through leveraging ancestry architecture and functional annotation using PAGE and UKBB cohorts

Author: Anwar, Mohammad Yaser, Graff, Mariaelisa, Highland, Heather M., Smit, Roelof, Wang, Zhe, Buchanan, Victoria L., Young, Kristin L., Kenny, Eimear E., Fernandez-Rhodes, Lindsay, Liu, Simin, Assimes, Themistocles, Garcia, David O., Daeeun, Kim, Gignoux, Christopher R., Justice, Anne E., Haiman, Christopher A., Buyske, Steve, Peters, Ulrike, Loos, Ruth J. F., Kooperberg, Charles, and North, Kari E.
Published: 2023
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21. Infant Growth Trajectories and Lipid Levels in Adolescence: Evidence From a Chilean Infancy Cohort.

Author: Von Holle, Ann, North, Kari E, Gahagan, Sheila, Blanco, Estela, Burrows, Raquel, Lozoff, Betsy, Howard, Annie Green, Justice, Anne E, Graff, Mariaelisa, and Voruganti, Saroja
Subjects: Pediatric, Pediatric Research Initiative, Clinical Research, Nutrition, Cardiovascular, 2.1 Biological and endogenous factors, Aetiology, Adolescent, Chile, Cholesterol, LDL, Cohort Studies, Female, Humans, Infant, Lipoproteins, HDL, Longitudinal Studies, Male, high-density lipoprotein cholesterol, infant growth, length, low-density lipoprotein cholesterol, triglycerides, weight, weight-for-length, Mathematical Sciences, Medical and Health Sciences, Epidemiology
Abstract: Growth in early infancy is hypothesized to affect chronic disease risk factors later in life. To date, most reports draw on European-ancestry cohorts with few repeated observations in early infancy. We investigated the association between infant growth before 6 months and lipid levels in adolescents in a Hispanic/Latino cohort. We characterized infant growth from birth to 5 months in male (n = 311) and female (n = 285) infants from the Santiago Longitudinal Study (1991-1996) using 3 metrics: weight (kg), length (cm), and weight-for-length (g/cm). Superimposition by translation and rotation (SITAR) and latent growth mixture models (LGMMs) were used to estimate the association between infant growth characteristics and lipid levels at age 17 years. We found a positive relationship between the SITAR length velocity parameter before 6 months of age and high-density lipoprotein cholesterol levels in adolescence (11.5, 95% confidence interval; 3.4, 19.5), indicating higher high-density lipoprotein cholesterol levels occurring with faster length growth. The strongest associations from the LGMMs were between higher low-density lipoprotein cholesterol and slower weight-for-length growth, following a pattern of associations between slower growth and adverse lipid profiles. Further research in this window of time can confirm the association between early infant growth as an exposure and adolescent cardiovascular disease risk factors.
Published: 2022

22. Insights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension

Author: Kelly, Tanika N, Sun, Xiao, He, Karen Y, Brown, Michael R, Taliun, Sarah A Gagliano, Hellwege, Jacklyn N, Irvin, Marguerite R, Mi, Xuenan, Brody, Jennifer A, Franceschini, Nora, Guo, Xiuqing, Hwang, Shih-Jen, de Vries, Paul S, Gao, Yan, Moscati, Arden, Nadkarni, Girish N, Yanek, Lisa R, Elfassy, Tali, Smith, Jennifer A, Chung, Ren-Hua, Beitelshees, Amber L, Patki, Amit, Aslibekyan, Stella, Blobner, Brandon M, Peralta, Juan M, Assimes, Themistocles L, Palmas, Walter R, Liu, Chunyu, Bress, Adam P, Huang, Zhijie, Becker, Lewis C, Hwa, Chii-Min, O’Connell, Jeffrey R, Carlson, Jenna C, Warren, Helen R, Das, Sayantan, Giri, Ayush, Martin, Lisa W, Johnson, W Craig, Fox, Ervin R, Bottinger, Erwin P, Razavi, Alexander C, Vaidya, Dhananjay, Chuang, Lee-Ming, Chang, Yen-Pei C, Naseri, Take, Jain, Deepti, Kang, Hyun Min, Hung, Adriana M, Srinivasasainagendra, Vinodh, Snively, Beverly M, Gu, Dongfeng, Montasser, May E, Reupena, Muagututi A Sefuiva, Heavner, Benjamin D, LeFaive, Jonathon, Hixson, James E, Rice, Kenneth M, Wang, Fei Fei, Nielsen, Jonas B, Huang, Jianfeng, Khan, Alyna T, Zhou, Wei, Nierenberg, Jovia L, Laurie, Cathy C, Armstrong, Nicole D, Shi, Mengyao, Pan, Yang, Stilp, Adrienne M, Emery, Leslie, Wong, Quenna, Hawley, Nicola L, Minster, Ryan L, Curran, Joanne E, Munroe, Patricia B, Weeks, Daniel E, North, Kari E, Tracy, Russell P, Kenny, Eimear E, Shimbo, Daichi, Chakravarti, Aravinda, Rich, Stephen S, Reiner, Alex P, Blangero, John, Redline, Susan, Mitchell, Braxton D, Rao, Dabeeru C, Chen, Yii-Der Ida, Kardia, Sharon LR, Kaplan, Robert C, Mathias, Rasika A, He, Jiang, Psaty, Bruce M, Fornage, Myriam, Loos, Ruth JF, Correa, Adolfo, Boerwinkle, Eric, Rotter, Jerome I, Kooperberg, Charles, and Edwards, Todd L
Subjects: Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Human Genome, Genetics, 2.1 Biological and endogenous factors, Aetiology, Cardiovascular, Good Health and Well Being, Blood Pressure, Genome-Wide Association Study, Genomics, Humans, Hypertension, Polymorphism, Single Nucleotide, Precision Medicine, allele, blood pressure, genome, hypertension, whole genome sequencing, Samoan Obesity, Lifestyle, and Genetic Adaptations Study (OLaGA) Group, ‡ NHLBI Trans-Omics for Precision Medicine TOPMed) Consortium, Cardiorespiratory Medicine and Haematology, Public Health and Health Services, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences
Abstract: BackgroundThe 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.MethodsWe 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.ResultsTwo blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings (P
Published: 2022

23. Clonal hematopoiesis driven by mutated DNMT3A promotes inflammatory bone loss

Author: Wang, Hui, Divaris, Kimon, Pan, Bohu, Li, Xiaofei, Lim, Jong-Hyung, Saha, Gundappa, Barovic, Marko, Giannakou, Danai, Korostoff, Jonathan M., Bing, Yu, Sen, Souvik, Moss, Kevin, Wu, Di, Beck, James D., Ballantyne, Christie M., Natarajan, Pradeep, North, Kari E., Netea, Mihai G., Chavakis, Triantafyllos, and Hajishengallis, George
Published: 2024
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24. Mendelian randomization supports bidirectional causality between telomere length and clonal hematopoiesis of indeterminate potential

Author: Nakao, Tetsushi, Bick, Alexander G, Taub, Margaret A, Zekavat, Seyedeh M, Uddin, Md M, Niroula, Abhishek, Carty, Cara L, Lane, John, Honigberg, Michael C, Weinstock, Joshua S, Pampana, Akhil, Gibson, Christopher J, Griffin, Gabriel K, Clarke, Shoa L, Bhattacharya, Romit, Assimes, Themistocles L, Emery, Leslie S, Stilp, Adrienne M, Wong, Quenna, Broome, Jai, Laurie, Cecelia A, Khan, Alyna T, Smith, Albert V, Blackwell, Thomas W, Codd, Veryan, Nelson, Christopher P, Yoneda, Zachary T, Peralta, Juan M, Bowden, Donald W, Irvin, Marguerite R, Boorgula, Meher, Zhao, Wei, Yanek, Lisa R, Wiggins, Kerri L, Hixson, James E, Gu, C Charles, Peloso, Gina M, Roden, Dan M, Reupena, Muagututi’a S, Hwu, Chii-Min, DeMeo, Dawn L, North, Kari E, Kelly, Shannon, Musani, Solomon K, Bis, Joshua C, Lloyd-Jones, Donald M, Johnsen, Jill M, Preuss, Michael, Tracy, Russell P, Peyser, Patricia A, Qiao, Dandi, Desai, Pinkal, Curran, Joanne E, Freedman, Barry I, Tiwari, Hemant K, Chavan, Sameer, Smith, Jennifer A, Smith, Nicholas L, Kelly, Tanika N, Hidalgo, Bertha, Cupples, L Adrienne, Weeks, Daniel E, Hawley, Nicola L, Minster, Ryan L, Deka, Ranjan, Naseri, Take T, de las Fuentes, Lisa, Raffield, Laura M, Morrison, Alanna C, Vries, Paul S, Ballantyne, Christie M, Kenny, Eimear E, Rich, Stephen S, Whitsel, Eric A, Cho, Michael H, Shoemaker, M Benjamin, Pace, Betty S, Blangero, John, Palmer, Nicholette D, Mitchell, Braxton D, Shuldiner, Alan R, Barnes, Kathleen C, Redline, Susan, Kardia, Sharon LR, Abecasis, Gonçalo R, Becker, Lewis C, Heckbert, Susan R, He, Jiang, Post, Wendy, Arnett, Donna K, Vasan, Ramachandran S, Darbar, Dawood, Weiss, Scott T, McGarvey, Stephen T, de Andrade, Mariza, Chen, Yii-Der Ida, Kaplan, Robert C, Meyers, Deborah A, Custer, Brian S, and Correa, Adolfo
Subjects: Cardiovascular, Genetics, Aging, Heart Disease, Heart Disease - Coronary Heart Disease, Human Genome, Atherosclerosis, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Samoan Obesity, Lifestyle and Genetic Adaptations Study (OLaGA) Group, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium
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.
Published: 2022

25. A genetic association study of circulating coagulation factor VIII and von Willebrand factor levels

Author: Abe, Namiko, Abecasis, Gonçalo, Aguet, Francois, Albert, Christine, Almasy, Laura, Alonso, Alvaro, Ament, Seth, Anderson, Peter, Anugu, Pramod, Applebaum-Bowden, Deborah, Ardlie, Kristin, Arking, Dan, Arnett, Donna K, Ashley-Koch, Allison, Aslibekyan, Stella, Assimes, Tim, Auer, Paul, Avramopoulos, Dimitrios, Ayas, Najib, Balasubramanian, Adithya, Barnard, John, Barnes, Kathleen, Barr, R. Graham, Barron-Casella, Emily, Barwick, Lucas, Beaty, Terri, Beck, Gerald, Becker, Diane, Becker, Lewis, Beer, Rebecca, Beitelshees, Amber, Benjamin, Emelia, Benos, Takis, Bezerra, Marcos, Bielak, Larry, Bis, Joshua, Blackwell, Thomas, Blangero, John, Blue, Nathan, Boerwinkle, Eric, Bowden, Donald W., Bowler, Russell, Brody, Jennifer, Broeckel, Ulrich, Broome, Jai, Brown, Deborah, Bunting, Karen, Burchard, Esteban, Bustamante, Carlos, Buth, Erin, Cade, Brian, Cardwell, Jonathan, Carey, Vincent, Carrier, Julie, Carson, April P., Carty, Cara, Casaburi, Richard, Casas Romero, Juan P, Casella, James, Castaldi, Peter, Chaffin, Mark, Chang, Christy, Chang, Yi-Cheng, Chasman, Daniel, Chavan, Sameer, Chen, Bo-Juen, Chen, Wei-Min, Ida Chen, Yii-Der, Cho, Michael, Choi, Seung Hoan, Chuang, Lee-Ming, Chung, Mina, Chung, Ren-Hua, Clish, Clary, Comhair, Suzy, Conomos, Matthew, Cornell, Elaine, Correa, Adolfo, Crandall, Carolyn, Crapo, James, Cupples, L. Adrienne, Curran, Joanne, Curtis, Jeffrey, Custer, Brian, Damcott, Coleen, Darbar, Dawood, David, Sean, Davis, Colleen, Daya, Michelle, de Andrade, Mariza, de las Fuentes, Lisa, de Vries, Paul, DeBaun, Michael, Deka, Ranjan, DeMeo, Dawn, Devine, Scott, Dinh, Huyen, Doddapaneni, Harsha, Duan, Qing, Dugan-Perez, Shannon, Duggirala, Ravi, Durda, Jon Peter, Dutcher, Susan K., Eaton, Charles, Ekunwe, Lynette, El Boueiz, Adel, Ellinor, Patrick, Emery, Leslie, Erzurum, Serpil, Farber, Charles, Farek, Jesse, Fingerlin, Tasha, Flickinger, Matthew, Fornage, Myriam, Franceschini, Nora, Frazar, Chris, Fu, Mao, Fullerton, Stephanie M., Fulton, Lucinda, Gabriel, Stacey, Gan, Weiniu, Gao, Shanshan, Gao, Yan, Gass, Margery, Geiger, Heather, Gelb, Bruce, Geraci, Mark, Germer, Soren, Gerszten, Robert, Ghosh, Auyon, Gibbs, Richard, Gignoux, Chris, Gladwin, Mark, Glahn, David, Gogarten, Stephanie, Gong, Da-Wei, Goring, Harald, Graw, Sharon, Gray, Kathryn J., Grine, Daniel, Gross, Colin, Gu, C. Charles, Guan, Yue, Guo, Xiuqing, Gupta, Namrata, Haessler, Jeff, Hall, Michael, Han, Yi, Hanly, Patrick, Harris, Daniel, Hawley, Nicola L., He, Jiang, Heavner, Ben, Heckbert, Susan, Hernandez, Ryan, Herrington, David, Hersh, Craig, Hidalgo, Bertha, Hixson, James, Hobbs, Brian, Hokanson, John, Hong, Elliott, Hoth, Karin, Hsiung, Chao (Agnes), Hu, Jianhong, Hung, Yi-Jen, Huston, Haley, Hwu, Chii Min, Irvin, Marguerite Ryan, Jackson, Rebecca, Jain, Deepti, Jaquish, Cashell, Johnsen, Jill, Johnson, Andrew, Johnson, Craig, Johnston, Rich, Jones, Kimberly, Kang, Hyun Min, Kaplan, Robert, Kardia, Sharon, Kelly, Shannon, Kenny, Eimear, Kessler, Michael, Khan, Alyna, Khan, Ziad, Kim, Wonji, Kimoff, John, Kinney, Greg, Konkle, Barbara, Kooperberg, Charles, Kramer, Holly, Lange, Christoph, Lange, Ethan, Lange, Leslie, Laurie, Cathy, Laurie, Cecelia, LeBoff, Meryl, Lee, Jiwon, Lee, Sandra, Lee, Wen-Jane, LeFaive, Jonathon, Levine, David, Levy, Dan, Lewis, Joshua, Li, Xiaohui, Li, Yun, Lin, Henry, Lin, Honghuang, Lin, Xihong, Liu, Simin, Liu, Yongmei, Liu, Yu, Loos, Ruth J. F., Lubitz, Steven, Lunetta, Kathryn, Luo, James, Magalang, Ulysses, Mahaney, Michael, Make, Barry, Manichaikul, Ani, Manning, Alisa, Manson, JoAnn, Martin, Lisa, Marton, Melissa, Mathai, Susan, Mathias, Rasika, May, Susanne, McArdle, Patrick, McDonald, Merry-Lynn, McFarland, Sean, McGarvey, Stephen, McGoldrick, Daniel, McHugh, Caitlin, McNeil, Becky, Mei, Hao, Meigs, James, Menon, Vipin, Mestroni, Luisa, Metcalf, Ginger, Meyers, Deborah A, Mignot, Emmanuel, Mikulla, Julie, Min, Nancy, Minear, Mollie, Minster, Ryan L, Mitchell, Braxton D., Moll, Matt, Momin, Zeineen, Montasser, May E., Montgomery, Courtney, Muzny, Donna, Mychaleckyj, Josyf C, Nadkarni, Girish, Naik, Rakhi, Naseri, Take, Natarajan, Pradeep, Nekhai, Sergei, Nelson, Sarah C., Neltner, Bonnie, Nessner, Caitlin, Nickerson, Deborah, Nkechinyere, Osuji, North, Kari, O'Connell, Jeff, O'Connor, Tim, Ochs-Balcom, Heather, Okwuonu, Geoffrey, Pack, Allan, Paik, David T., Palmer, Nicholette, Pankow, James, Papanicolaou, George, Parker, Cora, Peloso, Gina, Peralta, Juan Manuel, Perez, Marco, Perry, James, Peters, Ulrike, Peyser, Patricia, Phillips, Lawrence S, Pleiness, Jacob, Pollin, Toni, Post, Wendy, Becker, Julia Powers, Boorgula, Meher Preethi, Preuss, Michael, Psaty, Bruce, Qasba, Pankaj, Qiao, Dandi, Qin, Zhaohui, Rafaels, Nicholas, Raffield, Laura, Rajendran, Mahitha, Ramachandran, Vasan S., Rao, D. C., Rasmussen-Torvik, Laura, Ratan, Aakrosh, Redline, Susan, Reed, Robert, Reeves, Catherine, Regan, Elizabeth, Reiner, Alex, Reupena, Muagututi‘a Sefuiva, Rice, Ken, Rich, Stephen, Robillard, Rebecca, Robine, Nicolas, Roden, Dan, Roselli, Carolina, Rotter, Jerome, Ruczinski, Ingo, Runnels, Alexi, Russell, Pamela, Ruuska, Sarah, Ryan, Kathleen, Sabino, Ester Cerdeira, Saleheen, Danish, Salimi, Shabnam, Salvi, Sejal, Salzberg, Steven, Sandow, Kevin, Sankaran, Vijay G., Santibanez, Jireh, Schwander, Karen, Schwartz, David, Sciurba, Frank, Seidman, Christine, Seidman, Jonathan, Sériès, Frédéric, Sheehan, Vivien, Sherman, Stephanie L., Shetty, Amol, Shetty, Aniket, Hui-Heng Sheu, Wayne, Shoemaker, M. Benjamin, Silver, Brian, Silverman, Edwin, Skomro, Robert, Smith, Albert Vernon, Smith, Jennifer, Smith, Josh, Smith, Nicholas, Smith, Tanja, Smoller, Sylvia, Snively, Beverly, Snyder, Michael, Sofer, Tamar, Sotoodehnia, Nona, Stilp, Adrienne M., Storm, Garrett, Streeten, Elizabeth, Su, Jessica Lasky, Sung, Yun Ju, Sylvia, Jody, Szpiro, Adam, Taliun, Daniel, Tang, Hua, Taub, Margaret, Taylor, Kent D., Taylor, Matthew, Taylor, Simeon, Telen, Marilyn, Thornton, Timothy A., Threlkeld, Machiko, Tinker, Lesley, Tirschwell, David, Tishkoff, Sarah, Tiwari, Hemant, Tong, Catherine, Tracy, Russell, Tsai, Michael, Vaidya, Dhananjay, Van Den Berg, David, VandeHaar, Peter, Vrieze, Scott, Walker, Tarik, Wallace, Robert, Walts, Avram, Wang, Fei Fei, Wang, Heming, Wang, Jiongming, Watson, Karol, Watt, Jennifer, Weeks, Daniel E., Weinstock, Joshua, Weir, Bruce, Weiss, Scott T, Weng, Lu-Chen, Wessel, Jennifer, Willer, Cristen, Williams, Kayleen, Williams, L. Keoki, Wilson, Carla, Wilson, James, Winterkorn, Lara, Wong, Quenna, Wu, Joseph, Xu, Huichun, Yanek, Lisa, Yang, Ivana, Yu, Ketian, Zekavat, Seyedeh Maryam, Zhang, Yingze, Zhao, Snow Xueyan, Zhao, Wei, Zhu, Xiaofeng, Ziv, Elad, Zody, Michael, Zoellner, Sebastian, Lindstrom, Sara, Wang, Lu, Smith, Erin N., Gordon, William, van Hylckama Vlieg, Astrid, Brody, Jennifer A., Pattee, Jack W., Haessler, Jeffrey, Brumpton, Ben M., Chasman, Daniel I., Suchon, Pierre, Chen, Ming-Huei, Turman, Constance, Germain, Marine, Wiggins, Kerri L., MacDonald, James, Braekkan, Sigrid K., Armasu, Sebastian M., Pankratz, Nathan, Jackson, Rabecca D., Nielsen, Jonas B., Giulianini, Franco, Puurunen, Marja K., Ibrahim, Manal, Heckbert, Susan R., Bammler, Theo K., Frazer, Kelly A., McCauley, Bryan M., Taylor, Kent, Pankow, James S., Reiner, Alexander P., Gabrielsen, Maiken E., Deleuze, Jean-François, O'Donnell, Chris J., Kim, Jihye, McKnight, Barbara, Kraft, Peter, Hansen, John-Bjarne, Rosendaal, Frits R., Heit, John A., Psaty, Bruce M., Tang, Weihong, Hveem, Kristian, Ridker, Paul M., Morange, Pierre-Emmanuel, Johnson, Andrew D., Kabrhel, Christopher, AlexandreTrégouët, David, Smith, Nicholas L., de Vries, Paul S., Reventun, Paula, Brown, Michael R., Heath, Adam S., Huffman, Jennifer E., Le, Ngoc-Quynh, Bebo, Allison, Temprano-Sagrera, Gerard, Raffield, Laura M., Ozel, Ayse Bilge, Thibord, Florian, Lewis, Joshua P., Rodriguez, Benjamin A. T., Polasek, Ozren, Yanek, Lisa R., Carrasquilla, German D., Marioni, Riccardo E., Kleber, Marcus E., Trégouët, David-Alexandre, Yao, Jie, Li-Gao, Ruifang, Joshi, Peter K., Trompet, Stella, Martinez-Perez, Angel, Ghanbari, Mohsen, Howard, Tom E., Reiner, Alex P., Arvanitis, Marios, Ryan, Kathleen A., Bartz, Traci M., Rudan, Igor, Faraday, Nauder, Linneberg, Allan, Davies, Gail, Delgado, Graciela E., Klaric, Lucija, Noordam, Raymond, van Rooij, Frank, Curran, Joanne E., Wheeler, Marsha M., Osburn, William O., O'Connell, Jeffrey R., Beswick, Andrew, Kolcic, Ivana, Souto, Juan Carlos, Becker, Lewis C., Hansen, Torben, Doyle, Margaret F., Harris, Sarah E., Moissl, Angela P., Rich, Stephen S., Campbell, Harry, Stott, David J., Soria, Jose Manuel, de Maat, Moniek P. M., Brody, Lawrence C., Auer, Paul L., Ben-Shlomo, Yoav, Hayward, Caroline, Mathias, Rasika A., Kilpeläinen, Tuomas O., Lange, Leslie A., Cox, Simon R., März, Winfried, Rotter, Jerome I., Mook-Kanamori, Dennis O., Wilson, James F., van der Harst, Pim, Jukema, J. Wouter, Ikram, M. Arfan, Desch, Karl C., Sabater-Lleal, Maria, Lowenstein, Charles J., and Morrison, Alanna C.
Published: 2024
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26. Exploiting meta-analysis of genome-wide interaction with serum 25-hydroxyvitamin D to identify novel genetic loci associated with pulmonary function

Author: Seo, Jungkyun, Gaddis, Nathan C, Patchen, Bonnie K, Xu, Jiayi, Barr, R Graham, O’Connor, George, Manichaikul, Ani W, Gharib, Sina A, Dupuis, Josée, North, Kari E, Cassano, Patricia A, and Hancock, Dana B
Published: 2024
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27. MUSSEL: Enhanced Bayesian polygenic risk prediction leveraging information across multiple ancestry groups

Author: Aslibekyan, Stella, Auton, Adam, Babalola, Elizabeth, Bell, Robert K., Bielenberg, Jessica, Bryc, Katarzyna, Bullis, Emily, Coker, Daniella, Cuellar Partida, Gabriel, Dhamija, Devika, Das, Sayantan, Elson, Sarah L., Eriksson, Nicholas, Filshtein, Teresa, Fitch, Alison, Fletez-Brant, Kipper, Fontanillas, Pierre, Freyman, Will, Granka, Julie M., Heilbron, Karl, Hernandez, Alejandro, Hicks, Barry, Hinds, David A., Jewett, Ethan M., Jiang, Yunxuan, Kukar, Katelyn, Kwong, Alan, Lin, Keng-Han, Llamas, Bianca A., Lowe, Maya, McCreight, Jey C., McIntyre, Matthew H., Micheletti, Steven J., Moreno, Meghan E., Nandakumar, Priyanka, Nguyen, Dominique T., Noblin, Elizabeth S., O’Connell, Jared, Petrakovitz, Aaron A., Poznik, G. David, Reynoso, Alexandra, Schumacher, Morgan, Shastri, Anjali J., Shelton, Janie F., Shi, Jingchunzi, Shringarpure, Suyash, Su, Qiaojuan Jane, Tat, Susana A., Tchakouté, Christophe Toukam, Tran, Vinh, Tung, Joyce Y., Wang, Xin, Wang, Wei, Weldon, Catherine H., Wilton, Peter, Wong, Corinna D., Jin, Jin, Zhan, Jianan, Zhang, Jingning, Zhao, Ruzhang, Buyske, Steven, Gignoux, Christopher, Haiman, Christopher, Kenny, Eimear E., Kooperberg, Charles, North, Kari, Koelsch, Bertram L., Wojcik, Genevieve, Zhang, Haoyu, and Chatterjee, Nilanjan
Published: 2024
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28. Multi-ethnic GWAS and fine-mapping of glycaemic traits identify novel loci in the PAGE Study

Author: Downie, Carolina G, Dimos, Sofia F, Bien, Stephanie A, Hu, Yao, Darst, Burcu F, Polfus, Linda M, Wang, Yujie, Wojcik, Genevieve L, Tao, Ran, Raffield, Laura M, Armstrong, Nicole D, Polikowsky, Hannah G, Below, Jennifer E, Correa, Adolfo, Irvin, Marguerite R, Rasmussen-Torvik, Laura JF, Carlson, Christopher S, Phillips, Lawrence S, Liu, Simin, Pankow, James S, Rich, Stephen S, Rotter, Jerome I, Buyske, Steven, Matise, Tara C, North, Kari E, Avery, Christy L, Haiman, Christopher A, Loos, Ruth JF, Kooperberg, Charles, Graff, Mariaelisa, and Highland, Heather M
Subjects: Epidemiology, Health Sciences, Diabetes, Human Genome, Prevention, Genetics, Metabolic and endocrine, Blood Glucose, Diabetes Mellitus, Type 2, Genome-Wide Association Study, Genomics, Humans, Polymorphism, Single Nucleotide, Fine-mapping, Genome-wide association study, Glucose, Glycaemic traits, HbA(1c), Insulin, Transethnic population, HbA1c, Clinical Sciences, Paediatrics and Reproductive Medicine, Public Health and Health Services, Endocrinology & Metabolism, Clinical sciences, Public health
Abstract: Aims/hypothesisType 2 diabetes is a growing global public health challenge. Investigating quantitative traits, including fasting glucose, fasting insulin and HbA1c, that serve as early markers of type 2 diabetes progression may lead to a deeper understanding of the genetic aetiology of type 2 diabetes development. Previous genome-wide association studies (GWAS) have identified over 500 loci associated with type 2 diabetes, glycaemic traits and insulin-related traits. However, most of these findings were based only on populations of European ancestry. To address this research gap, we examined the genetic basis of fasting glucose, fasting insulin and HbA1c in participants of the diverse Population Architecture using Genomics and Epidemiology (PAGE) Study.MethodsWe conducted a GWAS of fasting glucose (n = 52,267), fasting insulin (n = 48,395) and HbA1c (n = 23,357) in participants without diabetes from the diverse PAGE Study (23% self-reported African American, 46% Hispanic/Latino, 40% European, 4% Asian, 3% Native Hawaiian, 0.8% Native American), performing transethnic and population-specific GWAS meta-analyses, followed by fine-mapping to identify and characterise novel loci and independent secondary signals in known loci.ResultsFour novel associations were identified (p < 5 × 10-9), including three loci associated with fasting insulin, and a novel, low-frequency African American-specific locus associated with fasting glucose. Additionally, seven secondary signals were identified, including novel independent secondary signals for fasting glucose at the known GCK locus and for fasting insulin at the known PPP1R3B locus in transethnic meta-analysis.Conclusions/interpretationOur findings provide new insights into the genetic architecture of glycaemic traits and highlight the continued importance of conducting genetic studies in diverse populations.Data availabilityFull summary statistics from each of the population-specific and transethnic results are available at NHGRI-EBI GWAS catalog ( https://www.ebi.ac.uk/gwas/downloads/summary-statistics ).
Published: 2022

29. Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data

Author: Wainschtein, Pierrick, Jain, Deepti, Zheng, Zhili, Cupples, L Adrienne, Shadyab, Aladdin H, McKnight, Barbara, Shoemaker, Benjamin M, Mitchell, Braxton D, Psaty, Bruce M, Kooperberg, Charles, Liu, Ching-Ti, Albert, Christine M, Roden, Dan, Chasman, Daniel I, Darbar, Dawood, Lloyd-Jones, Donald M, Arnett, Donna K, Regan, Elizabeth A, Boerwinkle, Eric, Rotter, Jerome I, O’Connell, Jeffrey R, Yanek, Lisa R, de Andrade, Mariza, Allison, Matthew A, McDonald, Merry-Lynn N, Chung, Mina K, Fornage, Myriam, Chami, Nathalie, Smith, Nicholas L, Ellinor, Patrick T, Vasan, Ramachandran S, Mathias, Rasika A, Loos, Ruth JF, Rich, Stephen S, Lubitz, Steven A, Heckbert, Susan R, Redline, Susan, Guo, Xiuqing, Chen, Y-D Ida, Laurie, Cecelia A, Hernandez, Ryan D, McGarvey, Stephen T, Goddard, Michael E, Laurie, Cathy C, North, Kari E, Lange, Leslie A, Weir, Bruce S, Yengo, Loic, Yang, Jian, and Visscher, Peter M
Subjects: Human Genome, Genetics, 2.1 Biological and endogenous factors, Aetiology, Generic health relevance, Alleles, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Multifactorial Inheritance, Polymorphism, Single Nucleotide, TOPMed Anthropometry Working Group, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract: Analyses of data from genome-wide association studies on unrelated individuals have shown that, for human traits and diseases, approximately one-third to two-thirds of heritability is captured by common SNPs. However, it is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular whether the causal variants are rare, or whether it is overestimated due to bias in inference from pedigree data. Here we estimated heritability for height and body mass index (BMI) from whole-genome sequence data on 25,465 unrelated individuals of European ancestry. The estimated heritability was 0.68 (standard error 0.10) for height and 0.30 (standard error 0.10) for body mass index. Low minor allele frequency variants in low linkage disequilibrium (LD) with neighboring variants were enriched for heritability, to a greater extent for protein-altering variants, consistent with negative selection. Our results imply that rare variants, in particular those in regions of low linkage disequilibrium, are a major source of the still missing heritability of complex traits and disease.
Published: 2022

30. Whole genome sequence analysis of platelet traits in the NHLBI Trans-Omics for Precision Medicine (TOPMed) initiative

Author: Little, Amarise, Hu, Yao, Sun, Quan, Jain, Deepti, Broome, Jai, Chen, Ming-Huei, Thibord, Florian, McHugh, Caitlin, Surendran, Praveen, Blackwell, Thomas W, Brody, Jennifer A, Bhan, Arunoday, Chami, Nathalie, de Vries, Paul S, Ekunwe, Lynette, Heard-Costa, Nancy, Hobbs, Brian D, Manichaikul, Ani, Moon, Jee-Young, Preuss, Michael H, Ryan, Kathleen, Wang, Zhe, Wheeler, Marsha, Yanek, Lisa R, Abecasis, Goncalo R, Almasy, Laura, Beaty, Terri H, Becker, Lewis C, Blangero, John, Boerwinkle, Eric, Butterworth, Adam S, Choquet, Hélène, Correa, Adolfo, Curran, Joanne E, Faraday, Nauder, Fornage, Myriam, Glahn, David C, Hou, Lifang, Jorgenson, Eric, Kooperberg, Charles, Lewis, Joshua P, Lloyd-Jones, Donald M, Loos, Ruth JF, Min, Yuan-I, Mitchell, Braxton D, Morrison, Alanna C, Nickerson, Deborah A, North, Kari E, O'Connell, Jeffrey R, Pankratz, Nathan, Psaty, Bruce M, Vasan, Ramachandran S, Rich, Stephen S, Rotter, Jerome I, Smith, Albert V, Smith, Nicholas L, Tang, Hua, Tracy, Russell P, Conomos, Matthew P, Laurie, Cecelia A, Mathias, Rasika A, Li, Yun, Auer, Paul L, Consortium, NHLBI Trans-Omics for Precision Medicine, Thornton, Timothy, Reiner, Alexander P, Johnson, Andrew D, and Raffield, Laura M
Subjects: Biological Sciences, Genetics, Hematology, Biotechnology, Clinical Research, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Blood Platelets, Genome-Wide Association Study, Humans, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Polymorphism, Single Nucleotide, Precision Medicine, United States, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Medical and Health Sciences, Genetics & Heredity
Abstract: Platelets play a key role in thrombosis and hemostasis. Platelet count (PLT) and mean platelet volume (MPV) are highly heritable quantitative traits, with hundreds of genetic signals previously identified, mostly in European ancestry populations. We here utilize whole genome sequencing (WGS) from NHLBI's Trans-Omics for Precision Medicine initiative (TOPMed) in a large multi-ethnic sample to further explore common and rare variation contributing to PLT (n = 61 200) and MPV (n = 23 485). We identified and replicated secondary signals at MPL (rs532784633) and PECAM1 (rs73345162), both more common in African ancestry populations. We also observed rare variation in Mendelian platelet-related disorder genes influencing variation in platelet traits in TOPMed cohorts (not enriched for blood disorders). For example, association of GP9 with lower PLT and higher MPV was partly driven by a pathogenic Bernard-Soulier syndrome variant (rs5030764, p.Asn61Ser), and the signals at TUBB1 and CD36 were partly driven by loss of function variants not annotated as pathogenic in ClinVar (rs199948010 and rs571975065). However, residual signal remained for these gene-based signals after adjusting for lead variants, suggesting that additional variants in Mendelian genes with impacts in general population cohorts remain to be identified. Gene-based signals were also identified at several genome-wide association study identified loci for genes not annotated for Mendelian platelet disorders (PTPRH, TET2, CHEK2), with somatic variation driving the result at TET2. These results highlight the value of WGS in populations of diverse genetic ancestry to identify novel regulatory and coding signals, even for well-studied traits like platelet traits.
Published: 2022

31. The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations.

Author: Wang, Zhe, Choi, Shing, Chami, Nathalie, Boerwinkle, Eric, Fornage, Myriam, Redline, Susan, Bis, Joshua, Brody, Jennifer, Psaty, Bruce, Kim, Wonji, McDonald, Merry-Lynn, Regan, Elizabeth, Silverman, Edwin, Liu, Ching-Ti, Vasan, Ramachandran, Kalyani, Rita, Mathias, Rasika, Yanek, Lisa, Arnett, Donna, Justice, Anne, North, Kari, Kaplan, Robert, Heckbert, Susan, de Andrade, Mariza, Guo, Xiuqing, Lange, Leslie, Rich, Stephen, Rotter, Jerome, Ellinor, Patrick, Lubitz, Steven, Blangero, John, Shoemaker, M, Darbar, Dawood, Gladwin, Mark, Albert, Christine, Chasman, Daniel, Jackson, Rebecca, Kooperberg, Charles, Reiner, Alexander, OReilly, Paul, and Loos, Ruth
Subjects: BMI - body mass index, C+T, PRS-CS, burden score, lassosum, obesity risk, polygenic risk score, rare variants, Gene Frequency, Genetic Variation, Genome-Wide Association Study, Humans, Obesity, Whole Genome Sequencing
Abstract: Polygenic risk scores (PRSs) aggregate the effects of genetic variants across the genome and are used to predict risk of complex diseases, such as obesity. Current PRSs only include common variants (minor allele frequency (MAF) ≥1%), whereas the contribution of rare variants in PRSs to predict disease remains unknown. Here, we examine whether augmenting the standard common variant PRS (PRScommon) with a rare variant PRS (PRSrare) improves prediction of obesity. We used genome-wide genotyped and imputed data on 451,145 European-ancestry participants of the UK Biobank, as well as whole exome sequencing (WES) data on 184,385 participants. We performed single variant analyses (for both common and rare variants) and gene-based analyses (for rare variants) for association with BMI (kg/m2), obesity (BMI ≥ 30 kg/m2), and extreme obesity (BMI ≥ 40 kg/m2). We built PRSscommon and PRSsrare using a range of methods (Clumping+Thresholding [C+T], PRS-CS, lassosum, gene-burden test). We selected the best-performing PRSs and assessed their performance in 36,757 European-ancestry unrelated participants with whole genome sequencing (WGS) data from the Trans-Omics for Precision Medicine (TOPMed) program. The best-performing PRScommon explained 10.1% of variation in BMI, and 18.3% and 22.5% of the susceptibility to obesity and extreme obesity, respectively, whereas the best-performing PRSrare explained 1.49%, and 2.97% and 3.68%, respectively. The PRSrare was associated with an increased risk of obesity and extreme obesity (ORobesity = 1.37 per SDPRS, Pobesity = 1.7x10-85; ORextremeobesity = 1.55 per SDPRS, Pextremeobesity = 3.8x10-40), which was attenuated, after adjusting for PRScommon (ORobesity = 1.08 per SDPRS, Pobesity = 9.8x10-6; ORextremeobesity= 1.09 per SDPRS, Pextremeobesity = 0.02). When PRSrare and PRScommon are combined, the increase in explained variance attributed to PRSrare was small (incremental Nagelkerke R2 = 0.24% for obesity and 0.51% for extreme obesity). Consistently, combining PRSrare to PRScommon provided little improvement to the prediction of obesity (PRSrare AUC = 0.591; PRScommon AUC = 0.708; PRScombined AUC = 0.710). In summary, while rare variants show convincing association with BMI, obesity and extreme obesity, the PRSrare provides limited improvement over PRScommon in the prediction of obesity risk, based on these large populations.
Published: 2022

32. Genetic pleiotropy underpinning adiposity and inflammation in self-identified Hispanic/Latino populations

Author: Anwar, Mohammad Yaser, Baldassari, Antoine R, Polikowsky, Hannah G, Sitlani, Colleen M, Highland, Heather M, Chami, Nathalie, Chen, Hung-Hsin, Graff, Mariaelisa, Howard, Annie Green, Jung, Su Yon, Petty, Lauren E, Wang, Zhe, Zhu, Wanying, Buyske, Steven, Cheng, Iona, Kaplan, Robert, Kooperberg, Charles, Loos, Ruth JF, Peters, Ulrike, McCormick, Joseph B, Fisher-Hoch, Susan P, Avery, Christy L, Taylor, Kira C, Below, Jennifer E, and North, Kari E
Subjects: Biological Sciences, Genetics, Human Genome, Clinical Research, Obesity, Aetiology, 2.1 Biological and endogenous factors, Adiposity, Genetic Pleiotropy, Hispanic or Latino, Humans, Inflammation, Genetic pleiotropy, Hispanic Americans, Medical Biochemistry and Metabolomics, Oncology and Carcinogenesis, Genetics & Heredity, Medical biochemistry and metabolomics
Abstract: BackgroundConcurrent variation in adiposity and inflammation suggests potential shared functional pathways and pleiotropic disease underpinning. Yet, exploration of pleiotropy in the context of adiposity-inflammation has been scarce, and none has included self-identified Hispanic/Latino populations. Given the high level of ancestral diversity in Hispanic American population, genetic studies may reveal variants that are infrequent/monomorphic in more homogeneous populations.MethodsUsing multi-trait Adaptive Sum of Powered Score (aSPU) method, we examined individual and shared genetic effects underlying inflammatory (CRP) and adiposity-related traits (Body Mass Index [BMI]), and central adiposity (Waist to Hip Ratio [WHR]) in HLA participating in the Population Architecture Using Genomics and Epidemiology (PAGE) cohort (N = 35,871) with replication of effects in the Cameron County Hispanic Cohort (CCHC) which consists of Mexican American individuals.ResultsOf the > 16 million SNPs tested, variants representing 7 independent loci were found to illustrate significant association with multiple traits. Two out of 7 variants were replicated at statistically significant level in multi-trait analyses in CCHC. The lead variant on APOE (rs439401) and rs11208712 were found to harbor multi-trait associations with adiposity and inflammation.ConclusionsResults from this study demonstrate the importance of considering pleiotropy for improving our understanding of the etiology of the various metabolic pathways that regulate cardiovascular disease development.
Published: 2022

33. Whole genome sequence analysis of blood lipid levels in >66,000 individuals

Author: Selvaraj, Margaret Sunitha, Li, Xihao, Li, Zilin, Pampana, Akhil, Zhang, David Y, Park, Joseph, Aslibekyan, Stella, Bis, Joshua C, Brody, Jennifer A, Cade, Brian E, Chuang, Lee-Ming, Chung, Ren-Hua, Curran, Joanne E, de las Fuentes, Lisa, de Vries, Paul S, Duggirala, Ravindranath, Freedman, Barry I, Graff, Mariaelisa, Guo, Xiuqing, Heard-Costa, Nancy, Hidalgo, Bertha, Hwu, Chii-Min, Irvin, Marguerite R, Kelly, Tanika N, Kral, Brian G, Lange, Leslie, Li, Xiaohui, Lisa, Martin, Lubitz, Steven A, Manichaikul, Ani W, Michael, Preuss, Montasser, May E, Morrison, Alanna C, Naseri, Take, O’Connell, Jeffrey R, Palmer, Nicholette D, Peyser, Patricia A, Reupena, Muagututia S, Smith, Jennifer A, Sun, Xiao, Taylor, Kent D, Tracy, Russell P, Tsai, Michael Y, Wang, Zhe, Wang, Yuxuan, Bao, Wei, Wilkins, John T, Yanek, Lisa R, Zhao, Wei, Arnett, Donna K, Blangero, John, Boerwinkle, Eric, Bowden, Donald W, Chen, Yii-Der Ida, Correa, Adolfo, Cupples, L Adrienne, Dutcher, Susan K, Ellinor, Patrick T, Fornage, Myriam, Gabriel, Stacey, Germer, Soren, Gibbs, Richard, He, Jiang, Kaplan, Robert C, Kardia, Sharon LR, Kim, Ryan, Kooperberg, Charles, Loos, Ruth JF, Viaud-Martinez, Karine A, Mathias, Rasika A, McGarvey, Stephen T, Mitchell, Braxton D, Nickerson, Deborah, North, Kari E, Psaty, Bruce M, Redline, Susan, Reiner, Alexander P, Vasan, Ramachandran S, Rich, Stephen S, Willer, Cristen, Rotter, Jerome I, Rader, Daniel J, Lin, Xihong, Peloso, Gina M, and Natarajan, Pradeep
Subjects: Biological Sciences, Biomedical and Clinical Sciences, Genetics, Epidemiology, Health Sciences, Biotechnology, Heart Disease - Coronary Heart Disease, Cardiovascular, Heart Disease, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Alleles, Cholesterol, LDL, Genome-Wide Association Study, Humans, Lipids, Whole Genome Sequencing, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium
Abstract: Blood lipids are heritable modifiable causal factors for coronary artery disease. Despite well-described monogenic and polygenic bases of dyslipidemia, limitations remain in discovery of lipid-associated alleles using whole genome sequencing (WGS), partly due to limited sample sizes, ancestral diversity, and interpretation of clinical significance. Among 66,329 ancestrally diverse (56% non-European) participants, we associate 428M variants from deep-coverage WGS with lipid levels; ~400M variants were not assessed in prior lipids genetic analyses. We find multiple lipid-related genes strongly associated with blood lipids through analysis of common and rare coding variants. We discover several associated rare non-coding variants, largely at Mendelian lipid genes. Notably, we observe rare LDLR intronic variants associated with markedly increased LDL-C, similar to rare LDLR exonic variants. In conclusion, we conducted a systematic whole genome scan for blood lipids expanding the alleles linked to lipids for multiple ancestries and characterize a clinically-relevant rare non-coding variant model for lipids.
Published: 2022

34. Genetic determinants of telomere length from 109,122 ancestrally diverse whole-genome sequences in TOPMed

Author: Taub, Margaret A, Conomos, Matthew P, Keener, Rebecca, Iyer, Kruthika R, Weinstock, Joshua S, Yanek, Lisa R, Lane, John, Miller-Fleming, Tyne W, Brody, Jennifer A, Raffield, Laura M, McHugh, Caitlin P, Jain, Deepti, Gogarten, Stephanie M, Laurie, Cecelia A, Keramati, Ali, Arvanitis, Marios, Smith, Albert V, Heavner, Benjamin, Barwick, Lucas, Becker, Lewis C, Bis, Joshua C, Blangero, John, Bleecker, Eugene R, Burchard, Esteban G, Celedón, Juan C, Chang, Yen Pei C, Custer, Brian, Darbar, Dawood, de las Fuentes, Lisa, DeMeo, Dawn L, Freedman, Barry I, Garrett, Melanie E, Gladwin, Mark T, Heckbert, Susan R, Hidalgo, Bertha A, Irvin, Marguerite R, Islam, Talat, Johnson, W Craig, Kaab, Stefan, Launer, Lenore, Lee, Jiwon, Liu, Simin, Moscati, Arden, North, Kari E, Peyser, Patricia A, Rafaels, Nicholas, Seidman, Christine, Weeks, Daniel E, Wen, Fayun, Wheeler, Marsha M, Williams, L Keoki, Yang, Ivana V, Zhao, Wei, Aslibekyan, Stella, Auer, Paul L, Bowden, Donald W, Cade, Brian E, Chen, Zhanghua, Cho, Michael H, Cupples, L Adrienne, Curran, Joanne E, Daya, Michelle, Deka, Ranjan, Eng, Celeste, Fingerlin, Tasha E, Guo, Xiuqing, Hou, Lifang, Hwang, Shih-Jen, Johnsen, Jill M, Kenny, Eimear E, Levin, Albert M, Liu, Chunyu, Minster, Ryan L, Naseri, Take, Nouraie, Mehdi, Reupena, Muagututi A Sefuiva, Sabino, Ester C, Smith, Jennifer A, Smith, Nicholas L, Lasky-Su, Jessica, Taylor, James G, Telen, Marilyn J, Tiwari, Hemant K, Tracy, Russell P, White, Marquitta J, Zhang, Yingze, Wiggins, Kerri L, Weiss, Scott T, Vasan, Ramachandran S, Taylor, Kent D, Sinner, Moritz F, Silverman, Edwin K, Shoemaker, M Benjamin, Sheu, Wayne H-H, Sciurba, Frank, Schwartz, David A, Rotter, Jerome I, Roden, Daniel, Redline, Susan, and Raby, Benjamin A
Subjects: Epidemiology, Biological Sciences, Health Sciences, Genetics, Human Genome, Biotechnology, Aetiology, 2.1 Biological and endogenous factors, Generic health relevance, Good Health and Well Being, NHLBI CARE Network, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Hematology and Hemostasis Working Group, TOPMed Structural Variation Working Group
Abstract: Genetic studies on telomere length are important for understanding age-related diseases. Prior GWAS 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-value
Published: 2022

35. Multi-ethnic genome-wide association analyses of white blood cell and platelet traits in the Population Architecture using Genomics and Epidemiology (PAGE) study

Author: Hu, Yao, Bien, Stephanie A, Nishimura, Katherine K, Haessler, Jeffrey, Hodonsky, Chani J, Baldassari, Antoine R, Highland, Heather M, Wang, Zhe, Preuss, Michael, Sitlani, Colleen M, Wojcik, Genevieve L, Tao, Ran, Graff, Mariaelisa, Huckins, Laura M, Sun, Quan, Chen, Ming-Huei, Mousas, Abdou, Auer, Paul L, Lettre, Guillaume, Tang, Weihong, Qi, Lihong, Thyagarajan, Bharat, Buyske, Steve, Fornage, Myriam, Hindorff, Lucia A, Li, Yun, Lin, Danyu, Reiner, Alexander P, North, Kari E, Loos, Ruth JF, Raffield, Laura M, Peters, Ulrike, Avery, Christy L, and Kooperberg, Charles
Subjects: Clinical Research, Hematology, Genetics, American Indian or Alaska Native, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Cardiovascular, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Humans, Leukocytes, Phenotype, Polymorphism, Single Nucleotide, GWAS, White blood cells, Platelets, Multi-ethnic, Blood Cell Consortium, Biological Sciences, Information and Computing Sciences, Medical and Health Sciences, Bioinformatics
Abstract: BackgroundCirculating white blood cell and platelet traits are clinically linked to various disease outcomes and differ across individuals and ancestry groups. Genetic factors play an important role in determining these traits and many loci have been identified. However, most of these findings were identified in populations of European ancestry (EA), with African Americans (AA), Hispanics/Latinos (HL), and other races/ethnicities being severely underrepresented.ResultsWe performed ancestry-combined and ancestry-specific genome-wide association studies (GWAS) for white blood cell and platelet traits in the ancestrally diverse Population Architecture using Genomics and Epidemiology (PAGE) Study, including 16,201 AA, 21,347 HL, and 27,236 EA participants. We identified six novel findings at suggestive significance (P < 5E-8), which need confirmation, and independent signals at six previously established regions at genome-wide significance (P < 2E-9). We confirmed multiple previously reported genome-wide significant variants in the single variant association analysis and multiple genes using PrediXcan. Evaluation of loci reported from a Euro-centric GWAS indicated attenuation of effect estimates in AA and HL compared to EA populations.ConclusionsOur results highlighted the potential to identify ancestry-specific and ancestry-agnostic variants in participants with diverse backgrounds and advocate for continued efforts in improving inclusion of racially/ethnically diverse populations in genetic association studies for complex traits.
Published: 2021

36. Whole-genome association analyses of sleep-disordered breathing phenotypes in the NHLBI TOPMed program

Author: Cade, Brian E, Lee, Jiwon, Sofer, Tamar, Wang, Heming, Zhang, Man, Chen, Han, Gharib, Sina A, Gottlieb, Daniel J, Guo, Xiuqing, Lane, Jacqueline M, Liang, Jingjing, Lin, Xihong, Mei, Hao, Patel, Sanjay R, Purcell, Shaun M, Saxena, Richa, Shah, Neomi A, Evans, Daniel S, Hanis, Craig L, Hillman, David R, Mukherjee, Sutapa, Palmer, Lyle J, Stone, Katie L, Tranah, Gregory J, Abecasis, Gonçalo R, Boerwinkle, Eric A, Correa, Adolfo, Cupples, L Adrienne, Kaplan, Robert C, Nickerson, Deborah A, North, Kari E, Psaty, Bruce M, Rotter, Jerome I, Rich, Stephen S, Tracy, Russell P, Vasan, Ramachandran S, Wilson, James G, Zhu, Xiaofeng, and Redline, Susan
Subjects: Biological Sciences, Genetics, Sleep Research, Dental/Oral and Craniofacial Disease, Lung, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Good Health and Well Being, Alleles, Chromatin Immunoprecipitation Sequencing, Female, Gene Expression Regulation, Genetic Association Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Male, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Precision Medicine, Research, Signal Transduction, Sleep Apnea Syndromes, United States, Whole Genome Sequencing, Sleep-disordered breathing, Sleep apnea, Whole-genome sequencing, WGS, Genome-wide association study, GWAS, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Sleep Working Group, Clinical Sciences
Abstract: BackgroundSleep-disordered breathing is a common disorder associated with significant morbidity. The genetic architecture of sleep-disordered breathing remains poorly understood. Through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, we performed the first whole-genome sequence analysis of sleep-disordered breathing.MethodsThe study sample was comprised of 7988 individuals of diverse ancestry. Common-variant and pathway analyses included an additional 13,257 individuals. We examined five complementary traits describing different aspects of sleep-disordered breathing: the apnea-hypopnea index, average oxyhemoglobin desaturation per event, average and minimum oxyhemoglobin saturation across the sleep episode, and the percentage of sleep with oxyhemoglobin saturation
Published: 2021

37. Microbial co-occurrence complicates associations of gut microbiome with US immigration, dietary intake and obesity

Author: Wang, Zheng, Usyk, Mykhaylo, Vázquez-Baeza, Yoshiki, Chen, Guo-Chong, Isasi, Carmen R, Williams-Nguyen, Jessica S, Hua, Simin, McDonald, Daniel, Thyagarajan, Bharat, Daviglus, Martha L, Cai, Jianwen, North, Kari E, Wang, Tao, Knight, Rob, Burk, Robert D, Kaplan, Robert C, and Qi, Qibin
Subjects: Nutrition, Obesity, Cardiovascular, Oral and gastrointestinal, Acculturation, Adult, Aged, Aged, 80 and over, Bacteria, Cohort Studies, Diet, Eating, Emigrants and Immigrants, Emigration and Immigration, Feces, Female, Gastrointestinal Microbiome, Hispanic or Latino, Humans, Male, Metagenomics, Middle Aged, RNA, Ribosomal, 16S, United States, Microbiome, Hispanic population, Environmental Sciences, Biological Sciences, Information and Computing Sciences, Bioinformatics
Abstract: BackgroundObesity and related comorbidities are major health concerns among many US immigrant populations. Emerging evidence suggests a potential involvement of the gut microbiome. Here, we evaluated gut microbiome features and their associations with immigration, dietary intake, and obesity in 2640 individuals from a population-based study of US Hispanics/Latinos.ResultsThe fecal shotgun metagenomics data indicate that greater US exposure is associated with reduced ɑ-diversity, reduced functions of fiber degradation, and alterations in individual taxa, potentially related to a westernized diet. However, a majority of gut bacterial genera show paradoxical associations, being reduced with US exposure and increased with fiber intake, but increased with obesity. The observed paradoxical associations are not explained by host characteristics or variation in bacterial species but might be related to potential microbial co-occurrence, as seen by positive correlations among Roseburia, Prevotella, Dorea, and Coprococcus. In the conditional analysis with mutual adjustment, including all genera associated with both obesity and US exposure in the same model, the positive associations of Roseburia and Prevotella with obesity did not persist, suggesting that their positive associations with obesity might be due to their co-occurrence and correlations with obesity-related taxa, such as Dorea and Coprococcus.ConclusionsAmong US Hispanics/Latinos, US exposure is associated with unfavorable gut microbiome profiles for obesity risk, potentially related to westernized diet during acculturation. Microbial co-occurrence could be an important factor to consider in future studies relating individual gut microbiome taxa to environmental factors and host health and disease.
Published: 2021

38. Genome-wide association study of body fat distribution traits in Hispanics/Latinos from the HCHS/SOL

Author: Justice, Anne E, Young, Kristin, Gogarten, Stephanie M, Sofer, Tamar, Graff, Misa, Love, Shelly Ann M, Wang, Yujie, Klimentidis, Yann C, Cruz, Miguel, Guo, Xiuqing, Hartwig, Fernando, Petty, Lauren, Yao, Jie, Allison, Matthew A, Below, Jennifer E, Buchanan, Thomas A, Chen, Yii-Der Ida, Goodarzi, Mark O, Hanis, Craig, Highland, Heather M, Hsueh, Willa A, Ipp, Eli, Parra, Esteban, Palmas, Walter, Raffel, Leslie J, Rotter, Jerome I, Tan, Jingyi, Taylor, Kent D, Valladares, Adan, Xiang, Anny H, Sánchez-Johnsen, Lisa, Isasi, Carmen R, and North, Kari E
Subjects: Biological Sciences, Genetics, Nutrition, Behavioral and Social Science, Prevention, Obesity, Clinical Research, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Stroke, Metabolic and endocrine, Good Health and Well Being, Adiposity, Alleles, Body Fat Distribution, Genome-Wide Association Study, Hispanic or Latino, Humans, Polymorphism, Single Nucleotide, Quantitative Trait, Heritable, Medical and Health Sciences, Genetics & Heredity
Abstract: Central obesity is a leading health concern with a great burden carried by ethnic minority populations, especially Hispanics/Latinos. Genetic factors contribute to the obesity burden overall and to inter-population differences. We aimed to identify the loci associated with central adiposity measured as waist-to-hip ratio (WHR), waist circumference (WC) and hip circumference (HIP) adjusted for body mass index (adjBMI) by using the Hispanic Community Health Study/Study of Latinos (HCHS/SOL); determine if differences in associations differ by background group within HCHS/SOL and determine whether previously reported associations generalize to HCHS/SOL. Our analyses included 7472 women and 5200 men of mainland (Mexican, Central and South American) and Caribbean (Puerto Rican, Cuban and Dominican) background residing in the USA. We performed genome-wide association analyses stratified and combined across sexes using linear mixed-model regression. We identified 16 variants for waist-to-hip ratio adjusted for body mass index (WHRadjBMI), 22 for waist circumference adjusted for body mass index (WCadjBMI) and 28 for hip circumference adjusted for body mass index (HIPadjBMI), which reached suggestive significance (P
Published: 2021

39. SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Author: D’Antonio, Matteo, Nguyen, Jennifer P, Arthur, Timothy D, Matsui, Hiroko, Neale, Benjamin M, Daly, Mark, Ganna, Andrea, Stevens, Christine, Pathak, Gita A, Andrews, Shea J, Kanai, Masahiro, Cordioli, Mattia, Karjalainen, Juha, Polimanti, Renato, Pirinen, Matti, Harerimana, Nadia, Veerapen, Kumar, Wolford, Brooke, Nguyen, Huy, Solomonson, Matthew, Liao, Rachel G, Chwialkowska, Karolina, Trankiem, Amy, Balaconis, Mary K, Hayward, Caroline, Richmond, Anne, Campbell, Archie, Morris, Marcela, Fawns-Ritchie, Chloe, Glessner, Joseph T, Shaw, Douglas M, Chang, Xiao, Polikowski, Hannah, Lauren, E, Chen, Hung-Hsin, Wanying, Zhu, Hakonarson, Hakon, Porteous, David J, Below, Jennifer, North, Kari, McCormick, Joseph B, Timmers, Paul RHJ, Wilson, James F, Tenesa, Albert, D’Mellow, Kenton, Kerr, Shona M, Niemi, Mari EK, Nkambul, Lindokuhle, von Hohenstaufen, Kathrin Aprile, Sobh, Ali, Eltoukhy, Madonna M, Yassen, Amr M, Hegazy, Mohamed AF, Okasha, Kamal, Eid, Mohammed A, Moahmed, Hanteera S, Shahin, Doaa, El-Sherbiny, Yasser M, Elhadidy, Tamer A, Elghafar, Mohamed S Abd, El-Jawhari, Jehan J, Mohamed, Attia AS, Elnagdy, Marwa H, Samir, Amr, Abdel-Aziz, Mahmoud, Khafaga, Walid T, El-Lawaty, Walaa M, Torky, Mohamed S, El-shanshory, Mohamed R, Batini, Chiara, Lee, Paul H, Shrine, Nick, Williams, Alexander T, Tobin, Martin D, Guyatt, Anna L, John, Catherine, Packer, Richard J, Ali, Altaf, Free, Robert C, Wang, Xueyang, Wain, Louise V, Hollox, Edward J, Venn, Laura D, Bee, Catherine E, Adams, Emma L, Niavarani, Ahmadreza, Sharififard, Bahareh, Aliannejad, Rasoul, Amirsavadkouhi, Ali, and Naderpour, Zeinab
Subjects: Biological Sciences, Genetics, Lung, Human Genome, Infectious Diseases, Emerging Infectious Diseases, Biotechnology, Coronaviruses, Coronaviruses Disparities and At-Risk Populations, 2.1 Biological and endogenous factors, Good Health and Well Being, COVID-19, Chromosome Mapping, Computational Biology, Databases, Genetic, Ethnicity, Gene Expression, Gene Expression Profiling, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Humans, Organ Specificity, Polymorphism, Single Nucleotide, Quantitative Trait Loci, SARS-CoV-2, Severity of Illness Index, Transcriptome, COVID-19 Host Genetics Initiative, GWAS, colocalization, eQTL, Biochemistry and Cell Biology, Medical Physiology, Biological sciences
Abstract: Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types.
Published: 2021

40. A System for Phenotype Harmonization in the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) Program

Author: Stilp, Adrienne M, Emery, Leslie S, Broome, Jai G, Buth, Erin J, Khan, Alyna T, Laurie, Cecelia A, Wang, Fei Fei, Wong, Quenna, Chen, Dongquan, D'Augustine, Catherine M, Heard-Costa, Nancy L, Hohensee, Chancellor R, Johnson, William Craig, Juarez, Lucia D, Liu, Jingmin, Mutalik, Karen M, Raffield, Laura M, Wiggins, Kerri L, de Vries, Paul S, Kelly, Tanika N, Kooperberg, Charles, Natarajan, Pradeep, Peloso, Gina M, Peyser, Patricia A, Reiner, Alex P, Arnett, Donna K, Aslibekyan, Stella, Barnes, Kathleen C, Bielak, Lawrence F, Bis, Joshua C, Cade, Brian E, Chen, Ming-Huei, Correa, Adolfo, Cupples, L Adrienne, de Andrade, Mariza, Ellinor, Patrick T, Fornage, Myriam, Franceschini, Nora, Gan, Weiniu, Ganesh, Santhi K, Graffelman, Jan, Grove, Megan L, Guo, Xiuqing, Hawley, Nicola L, Hsu, Wan-Ling, Jackson, Rebecca D, Jaquish, Cashell E, Johnson, Andrew D, Kardia, Sharon LR, Kelly, Shannon, Lee, Jiwon, Mathias, Rasika A, McGarvey, Stephen T, Mitchell, Braxton D, Montasser, May E, Morrison, Alanna C, North, Kari E, Nouraie, Seyed Mehdi, Oelsner, Elizabeth C, Pankratz, Nathan, Rich, Stephen S, Rotter, Jerome I, Smith, Jennifer A, Taylor, Kent D, Vasan, Ramachandran S, Weeks, Daniel E, Weiss, Scott T, Wilson, Carla G, Yanek, Lisa R, Psaty, Bruce M, Heckbert, Susan R, and Laurie, Cathy C
Subjects: Epidemiology, Health Sciences, Human Genome, Lung, Genetics, Clinical Research, Cardiovascular, Good Health and Well Being, Data Aggregation, Genetic Association Studies, Humans, Information Dissemination, National Heart, Lung, and Blood Institute (U.S.), Phenomics, Phenotype, Precision Medicine, Program Evaluation, United States, cardiovascular disease, common data elements, hematologic disease, information dissemination, lung diseases, phenotypes, sleep-wake disorders, Mathematical Sciences, Medical and Health Sciences
Abstract: Genotype-phenotype association studies often combine phenotype data from multiple studies to increase statistical power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data-set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data-sharing mechanisms. This system was developed for the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine (TOPMed) program, which is generating genomic and other -omics data for more than 80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants (recruited in 1948-2012) from up to 17 studies per phenotype. Here we discuss challenges in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include 1) the software code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify, or extend these harmonizations to additional studies, and 2) the results of labeling thousands of phenotype variables with controlled vocabulary terms.
Published: 2021

41. Whole-genome sequencing in diverse subjects identifies genetic correlates of leukocyte traits: The NHLBI TOPMed program

Author: Mikhaylova, Anna V, McHugh, Caitlin P, Polfus, Linda M, Raffield, Laura M, Boorgula, Meher Preethi, Blackwell, Thomas W, Brody, Jennifer A, Broome, Jai, Chami, Nathalie, Chen, Ming-Huei, Conomos, Matthew P, Cox, Corey, Curran, Joanne E, Daya, Michelle, Ekunwe, Lynette, Glahn, David C, Heard-Costa, Nancy, Highland, Heather M, Hobbs, Brian D, Ilboudo, Yann, Jain, Deepti, Lange, Leslie A, Miller-Fleming, Tyne W, Min, Nancy, Moon, Jee-Young, Preuss, Michael H, Rosen, Jonathon, Ryan, Kathleen, Smith, Albert V, Sun, Quan, Surendran, Praveen, de Vries, Paul S, Walter, Klaudia, Wang, Zhe, Wheeler, Marsha, Yanek, Lisa R, Zhong, Xue, Abecasis, Goncalo R, Almasy, Laura, Barnes, Kathleen C, Beaty, Terri H, Becker, Lewis C, Blangero, John, Boerwinkle, Eric, Butterworth, Adam S, Chavan, Sameer, Cho, Michael H, Choquet, Hélène, Correa, Adolfo, Cox, Nancy, DeMeo, Dawn L, Faraday, Nauder, Fornage, Myriam, Gerszten, Robert E, Hou, Lifang, Johnson, Andrew D, Jorgenson, Eric, Kaplan, Robert, Kooperberg, Charles, Kundu, Kousik, Laurie, Cecelia A, Lettre, Guillaume, Lewis, Joshua P, Li, Bingshan, Li, Yun, Lloyd-Jones, Donald M, Loos, Ruth JF, Manichaikul, Ani, Meyers, Deborah A, Mitchell, Braxton D, Morrison, Alanna C, Ngo, Debby, Nickerson, Deborah A, Nongmaithem, Suraj, North, Kari E, O’Connell, Jeffrey R, Ortega, Victor E, Pankratz, Nathan, Perry, James A, Psaty, Bruce M, Rich, Stephen S, Soranzo, Nicole, Rotter, Jerome I, Silverman, Edwin K, Smith, Nicholas L, Tang, Hua, Tracy, Russell P, Thornton, Timothy A, Vasan, Ramachandran S, Zein, Joe, Mathias, Rasika A, Consortium, NHLBI Trans-Omics for Precision Medicine, Reiner, Alexander P, and Auer, Paul L
Subjects: Human Genome, Genetics, Aetiology, 2.1 Biological and endogenous factors, Inflammatory and immune system, Good Health and Well Being, Asthma, Biomarkers, Dermatitis, Atopic, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Leukocytes, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Polymorphism, Single Nucleotide, Prognosis, Proteome, Pulmonary Disease, Chronic Obstructive, Quantitative Trait Loci, United Kingdom, United States, Whole Genome Sequencing, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, blood-cell counts, whole-genome sequencing, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract: Many common and rare variants associated with hematologic traits have been discovered through imputation on large-scale reference panels. However, the majority of genome-wide association studies (GWASs) have been conducted in Europeans, and determining causal variants has proved challenging. We performed a GWAS of total leukocyte, neutrophil, lymphocyte, monocyte, eosinophil, and basophil counts generated from 109,563,748 variants in the autosomes and the X chromosome in the Trans-Omics for Precision Medicine (TOPMed) program, which included data from 61,802 individuals of diverse ancestry. We discovered and replicated 7 leukocyte trait associations, including (1) the association between a chromosome X, pseudo-autosomal region (PAR), noncoding variant located between cytokine receptor genes (CSF2RA and CLRF2) and lower eosinophil count; and (2) associations between single variants found predominantly among African Americans at the S1PR3 (9q22.1) and HBB (11p15.4) loci and monocyte and lymphocyte counts, respectively. We further provide evidence indicating that the newly discovered eosinophil-lowering chromosome X PAR variant might be associated with reduced susceptibility to common allergic diseases such as atopic dermatitis and asthma. Additionally, we found a burden of very rare FLT3 (13q12.2) variants associated with monocyte counts. Together, these results emphasize the utility of whole-genome sequencing in diverse samples in identifying associations missed by European-ancestry-driven GWASs.
Published: 2021

42. Mendelian randomization with incomplete measurements on the exposure in the Hispanic Community Health Study/Study of Latinos

Author: Li, Yilun, Wong, Kin Yau, Howard, Annie Green, Gordon-Larsen, Penny, Highland, Heather M., Graff, Mariaelisa, North, Kari E., Downie, Carolina G., Avery, Christy L., Yu, Bing, Young, Kristin L., Buchanan, Victoria L., Kaplan, Robert, Hou, Lifang, Joyce, Brian Thomas, Qi, Qibin, Sofer, Tamar, Moon, Jee-Young, and Lin, Dan-Yu
Published: 2024
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43. Causal effects on complex traits are similar for common variants across segments of different continental ancestries within admixed individuals

Author: Hou, Kangcheng, Ding, Yi, Xu, Ziqi, Wu, Yue, Bhattacharya, Arjun, Mester, Rachel, Belbin, Gillian M., Buyske, Steve, Conti, David V., Darst, Burcu F., Fornage, Myriam, Gignoux, Chris, Guo, Xiuqing, Haiman, Christopher, Kenny, Eimear E., Kim, Michelle, Kooperberg, Charles, Lange, Leslie, Manichaikul, Ani, North, Kari E., Peters, Ulrike, Rasmussen-Torvik, Laura J., Rich, Stephen S., Rotter, Jerome I., Wheeler, Heather E., Wojcik, Genevieve L., Zhou, Ying, Sankararaman, Sriram, and Pasaniuc, Bogdan
Published: 2023
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44. Branched chain amino acids harbor distinct and often opposing effects on health and disease

Author: Avery, Christy L., Howard, Annie Green, Lee, Harold H., Downie, Carolina G., Lee, Moa P., Koenigsberg, Sarah H., Ballou, Anna F., Preuss, Michael H., Raffield, Laura M., Yarosh, Rina A., North, Kari E., Gordon-Larsen, Penny, and Graff, Mariaelisa
Published: 2023
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45. Epigenome-wide methylation and progression to high-grade cervical intraepithelial neoplasia (CIN2+): a prospective cohort study in the United States

Author: Bukowski, Alexandra, Hoyo, Cathrine, Vielot, Nadja A., Graff, Misa, Kosorok, Michael R., Brewster, Wendy R., Maguire, Rachel L., Murphy, Susan K., Nedjai, Belinda, Ladoukakis, Efthymios, North, Kari E., and Smith, Jennifer S.
Published: 2023
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46. Sex-specific associations between adipokine profiles and carotid-intima media thickness in the Cameron County Hispanic Cohort (CCHC)

Author: Kim, Daeeun, Memili, Aylin, Chen, Hung-Hsin, Highland, Heather M., Polikowsky, Hannah G., Anwar, Mohammad Yaser, Laing, Susan T., Lee, Miryoung, McCormick, Joseph B., Fisher-Hoch, Susan P., Below, Jennifer E., North, Kari E., and Gutierrez, Absalon D.
Published: 2023
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47. Selenomonas sputigena acts as a pathobiont mediating spatial structure and biofilm virulence in early childhood caries

Author: Cho, Hunyong, Ren, Zhi, Divaris, Kimon, Roach, Jeffrey, Lin, Bridget M., Liu, Chuwen, Azcarate-Peril, M. Andrea, Simancas-Pallares, Miguel A., Shrestha, Poojan, Orlenko, Alena, Ginnis, Jeannie, North, Kari E., Zandona, Andrea G. Ferreira, Ribeiro, Apoena Aguiar, Wu, Di, and Koo, Hyun
Published: 2023
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48. Sugar-Sweetened Beverage Consumption May Modify Associations Between Genetic Variants in the CHREBP (Carbohydrate Responsive Element Binding Protein) Locus and HDL-C (High-Density Lipoprotein Cholesterol) and Triglyceride Concentrations.

Author: Haslam, Danielle E, Peloso, Gina M, Guirette, Melanie, Imamura, Fumiaki, Bartz, Traci M, Pitsillides, Achilleas N, Wang, Carol A, Li-Gao, Ruifang, Westra, Jason M, Pitkänen, Niina, Young, Kristin L, Graff, Mariaelisa, Wood, Alexis C, Braun, Kim VE, Luan, Jian'an, Kähönen, Mika, Kiefte-de Jong, Jessica C, Ghanbari, Mohsen, Tintle, Nathan, Lemaitre, Rozenn N, Mook-Kanamori, Dennis O, North, Kari, Helminen, Mika, Mossavar-Rahmani, Yasmin, Snetselaar, Linda, Martin, Lisa W, Viikari, Jorma S, Oddy, Wendy H, Pennell, Craig E, Rosendall, Frits R, Ikram, M Arfan, Uitterlinden, Andre G, Psaty, Bruce M, Mozaffarian, Dariush, Rotter, Jerome I, Taylor, Kent D, Lehtimäki, Terho, Raitakari, Olli T, Livingston, Kara A, Voortman, Trudy, Forouhi, Nita G, Wareham, Nick J, de Mutsert, Renée, Rich, Steven S, Manson, JoAnn E, Mora, Samia, Ridker, Paul M, Merino, Jordi, Meigs, James B, Dashti, Hassan S, Chasman, Daniel I, Lichtenstein, Alice H, Smith, Caren E, Dupuis, Josée, Herman, Mark A, and McKeown, Nicola M
Subjects: Humans, Triglycerides, Polymorphism, Single Nucleotide, Adult, Middle Aged, Female, Male, Basic Helix-Loop-Helix Leucine Zipper Transcription Factors, Cholesterol, HDL, Meta-Analysis as Topic, Sugar-Sweetened Beverages, carbohydrates, dyslipidemia, epidemiology, genetics, nutrition, sugars, triglyceride, Cardiovascular, Genetics, Human Genome
Abstract: BackgroundChREBP (carbohydrate responsive element binding protein) is a transcription factor that responds to sugar consumption. Sugar-sweetened beverage (SSB) consumption and genetic variants in the CHREBP locus have separately been linked to HDL-C (high-density lipoprotein cholesterol) and triglyceride concentrations. We hypothesized that SSB consumption would modify the association between genetic variants in the CHREBP locus and dyslipidemia.MethodsData from 11 cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (N=63 599) and the UK Biobank (N=59 220) were used to quantify associations of SSB consumption, genetic variants, and their interaction on HDL-C and triglyceride concentrations using linear regression models. A total of 1606 single nucleotide polymorphisms within or near CHREBP were considered. SSB consumption was estimated from validated questionnaires, and participants were grouped by their estimated intake.ResultsIn a meta-analysis, rs71556729 was significantly associated with higher HDL-C concentrations only among the highest SSB consumers (β, 2.12 [95% CI, 1.16-3.07] mg/dL per allele; P
Published: 2021

49. Whole-genome sequencing association analysis of quantitative red blood cell phenotypes: The NHLBI TOPMed program

Author: Hu, Yao, Stilp, Adrienne M, McHugh, Caitlin P, Rao, Shuquan, Jain, Deepti, Zheng, Xiuwen, Lane, John, de Bellefon, Sébastian Méric, Raffield, Laura M, Chen, Ming-Huei, Yanek, Lisa R, Wheeler, Marsha, Yao, Yao, Ren, Chunyan, Broome, Jai, Moon, Jee-Young, de Vries, Paul S, Hobbs, Brian D, Sun, Quan, Surendran, Praveen, Brody, Jennifer A, Blackwell, Thomas W, Choquet, Hélène, Ryan, Kathleen, Duggirala, Ravindranath, Heard-Costa, Nancy, Wang, Zhe, Chami, Nathalie, Preuss, Michael H, Min, Nancy, Ekunwe, Lynette, Lange, Leslie A, Cushman, Mary, Faraday, Nauder, Curran, Joanne E, Almasy, Laura, Kundu, Kousik, Smith, Albert V, Gabriel, Stacey, Rotter, Jerome I, Fornage, Myriam, Lloyd-Jones, Donald M, Vasan, Ramachandran S, Smith, Nicholas L, North, Kari E, Boerwinkle, Eric, Becker, Lewis C, Lewis, Joshua P, Abecasis, Goncalo R, Hou, Lifang, O’Connell, Jeffrey R, Morrison, Alanna C, Beaty, Terri H, Kaplan, Robert, Correa, Adolfo, Blangero, John, Jorgenson, Eric, Psaty, Bruce M, Kooperberg, Charles, Walton, Russell T, Kleinstiver, Benjamin P, Tang, Hua, Loos, Ruth JF, Soranzo, Nicole, Butterworth, Adam S, Nickerson, Debbie, Rich, Stephen S, Mitchell, Braxton D, Johnson, Andrew D, Auer, Paul L, Li, Yun, Mathias, Rasika A, Lettre, Guillaume, Pankratz, Nathan, Laurie, Cathy C, Laurie, Cecelia A, Bauer, Daniel E, Conomos, Matthew P, Reiner, Alexander P, and Consortium, NHLBI Trans-Omics for Precision Medicine
Subjects: Epidemiology, Biological Sciences, Health Sciences, Genetics, Biotechnology, Clinical Research, Hematology, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Adult, Aged, Chromosomes, Human, Pair 16, Datasets as Topic, Erythrocytes, Female, Gene Editing, Genetic Variation, Genome-Wide Association Study, HEK293 Cells, Humans, Male, Middle Aged, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Quality Control, Reproducibility of Results, United States, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, base editing, red blood cell traits, whole-genome sequencing, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract: Whole-genome sequencing (WGS), a powerful tool for detecting novel coding and non-coding disease-causing variants, has largely been applied to clinical diagnosis of inherited disorders. Here we leveraged WGS data in up to 62,653 ethnically diverse participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and assessed statistical association of variants with seven red blood cell (RBC) quantitative traits. We discovered 14 single variant-RBC trait associations at 12 genomic loci, which have not been reported previously. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, and G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these discovered variants are rare/low frequency, and several are observed disproportionately among non-European Ancestry (African, Hispanic/Latino, or East Asian) populations. We identified a 3 bp indel p.Lys2169del (g.88717175_88717177TCT[4]) (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis (MIM: 194380), associated with higher mean corpuscular hemoglobin concentration (MCHC). In stepwise conditional analysis and in gene-based rare variant aggregated association analysis, we identified several of the variants in HBB, HBA1, TMPRSS6, and G6PD that represent the carrier state for known coding, promoter, or splice site loss-of-function variants that cause inherited RBC disorders. Finally, we applied base and nuclease editing to demonstrate that the sentinel variant rs112097551 (nearest gene RPN1) acts through a cis-regulatory element that exerts long-range control of the gene RUVBL1 which is essential for hematopoiesis. Together, these results demonstrate the utility of WGS in ethnically diverse population-based samples and gene editing for expanding knowledge of the genetic architecture of quantitative hematologic traits and suggest a continuum between complex trait and Mendelian red cell disorders.
Published: 2021

50. Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices.

Author: Natarajan, Pradeep, Pampana, Akhil, Graham, Sarah E, Ruotsalainen, Sanni E, Perry, James A, de Vries, Paul S, Broome, Jai G, Pirruccello, James P, Honigberg, Michael C, Aragam, Krishna, Wolford, Brooke, Brody, Jennifer A, Antonacci-Fulton, Lucinda, Arden, Moscati, Aslibekyan, Stella, Assimes, Themistocles L, Ballantyne, Christie M, Bielak, Lawrence F, Bis, Joshua C, Cade, Brian E, Do, Ron, Doddapaneni, Harsha, Emery, Leslie S, Hung, Yi-Jen, Irvin, Marguerite R, Khan, Alyna T, Lange, Leslie, Lee, Jiwon, Lemaitre, Rozenn N, Martin, Lisa W, Metcalf, Ginger, Montasser, May E, Moon, Jee-Young, Muzny, Donna, O'Connell, Jeffrey R, Palmer, Nicholette D, Peralta, Juan M, Peyser, Patricia A, Stilp, Adrienne M, Tsai, Michael, Wang, Fei Fei, Weeks, Daniel E, Yanek, Lisa R, Wilson, James G, Abecasis, Goncalo, Arnett, Donna K, Becker, Lewis C, Blangero, John, Boerwinkle, Eric, Bowden, Donald W, Chang, Yi-Cheng, Chen, Yii-Der I, Choi, Won Jung, Correa, Adolfo, Curran, Joanne E, Daly, Mark J, Dutcher, Susan K, Ellinor, Patrick T, Fornage, Myriam, Freedman, Barry I, Gabriel, Stacey, Germer, Soren, Gibbs, Richard A, He, Jiang, Hveem, Kristian, Jarvik, Gail P, Kaplan, Robert C, Kardia, Sharon LR, Kenny, Eimear, Kim, Ryan W, Kooperberg, Charles, Laurie, Cathy C, Lee, Seonwook, Lloyd-Jones, Don M, Loos, Ruth JF, Lubitz, Steven A, Mathias, Rasika A, Martinez, Karine A Viaud, McGarvey, Stephen T, Mitchell, Braxton D, Nickerson, Deborah A, North, Kari E, Palotie, Aarno, Park, Cheol Joo, Psaty, Bruce M, Rao, DC, Redline, Susan, Reiner, Alexander P, Seo, Daekwan, Seo, Jeong-Sun, Smith, Albert V, Tracy, Russell P, Vasan, Ramachandran S, Kathiresan, Sekar, Cupples, L Adrienne, Rotter, Jerome I, Morrison, Alanna C, Rich, Stephen S, Ripatti, Samuli, and Willer, Cristen
Subjects: NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, FinnGen, Subcutaneous Tissue, Chromosomes, Human, X, Humans, Genetic Predisposition to Disease, Lipids, Eye Proteins, Nerve Tissue Proteins, Gene Expression Regulation, Genotype, Polymorphism, Single Nucleotide, Middle Aged, Female, Male, Genetic Loci, Genetic Association Studies, Whole Genome Sequencing, Phenomics, Cardiometabolic Risk Factors, Chromosomes, Human, X, Polymorphism, Single Nucleotide
Abstract: Autosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10-72), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10-4), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10-5). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids.
Published: 2021

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