Citations 2
Cross-cohort analysis of expression and splicing quantitative trait loci in TOPMed
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Adrienne , Abe, Namiko, Almasy, Laura, Ament, Seth, Anugu, Pramod, Auer, Paul, Avramopoulos, Dimitrios, Balasubramanian, Adithya, Barr, R. 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Charles, Guan, Yue, Hall, Michael, Han, Yi, Harris, Daniel, Heavner, Ben, Herrington, David, Hobbs, Brian, Hong, Elliott, Hoth, Karin, Hsiung, Chao (Agnes), Hu, Jianhong, Hung, Yi-Jen, Huston, Haley, Hwu, Chii Min, Jackson, Rebecca, Jain, Deepti, Johnsen, Jill, Johnston, Rich, Jones, Kimberly, Kessler, Michael, Khan, Alyna, Khan, Ziad, Kim, Wonji, Kimoff, John, Kinney, Greg, Kramer, Holly, Lange, Christoph, Lange, Ethan, Laurie, Cathy, Laurie, Cecelia, LeBoff, Meryl, Lee, Sandra, Lee, Wen-Jane, Levine, David, Lewis, Joshua, Li, Yun, Lin, Xihong, Liu, Simin, Liu, Yu, Make, Barry, Manning, Alisa, Manson, JoAnn, Martin, Lisa, Marton, Melissa, Mathai, Susan, May, Susanne, McArdle, Patrick, McDonald, Merry-Lynn, McFarland, Sean, McGoldrick, Daniel, McHugh, Caitlin, Mei, Hao, Meigs, James, Menon, Vipin, Min, Nancy, Moll, Matt, Momin, Zeineen, Montasser, May, Mychaleckyj, Josyf C, Naik, Rakhi, Naseri, Take, Natarajan, Pradeep, Nelson, Sarah C., Neltner, Bonnie, Nessner, Caitlin, Nkechinyere, Osuji, O'Connell, Jeff, O’Connor, Tim, Ochs-Balcom, Heather, Okwuonu, Geoffrey, Parker, Cora, Peloso, Gina, Peralta, Juan Manuel, Perez, Marco, Perry, James, Peters, Ulrike, Phillips, Lawrence S, Pollin, Toni, Becker, Julia Powers, Boorgula, Meher Preethi, Psaty, Bruce, Qiao, Dandi, Rafaels, Nicholas, Rajendran, Mahitha, Rasmussen-Torvik, Laura, Ratan, Aakrosh, Reed, Robert, Regan, Elizabeth, Reupena, Muagututi‘a Sefuiva, Robillard, Rebecca, Roselli, Carolina, Ruczinski, Ingo, Runnels, Alexi, Russell, Pamela, Ryan, Kathleen, Sabino, Ester Cerdeira, Salimi, Shabnam, Salvi, Sejal, Salzberg, Steven, Sandow, Kevin, Santibanez, Jireh, Schwander, Karen, Sciurba, Frank, Sériès, Frédéric , Shetty, Amol, Shetty, Aniket, Silver, Brian, Skomro, Robert, Smith, Tanja, Smoller, Sylvia, Snively, Beverly, Stilp, Adrienne M., Storm, Garrett, Streeten, Elizabeth, Su, Jessica Lasky, Sung, Yun Ju, Sylvia, Jody, Szpiro, Adam, Taub, Margaret, Taylor, Simeon, Thornton, Timothy A., Threlkeld, Machiko, Tinker, Lesley, Tirschwell, David, Tiwari, Hemant, Tong, Catherine, Tsai, Michael, Vaidya, Dhananjay, Walker, Tarik, Wallace, Robert, Walts, Avram, Wang, Fei Fei, Wang, Heming, Watson, Karol, Watt, Jennifer, Weng, Lu-Chen, Wessel, Jennifer, Williams, Kayleen, Wilson, Carla, Wilson, James, Winterkorn, Lara, Wong, Quenna, Wu, Baojun, Xu, Huichun, Yanek, Lisa, Yang, Ivana, Zekavat, Seyedeh Maryam, Zhao, Snow Xueyan, Zhao, Wei, Zhu, Xiaofeng
Science | July 16, 2026 | Volume: 393 | Issue: 6808 | Pages: No page available
Most genetic variants associated with complex traits are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterized 14,324 RNA-sequencing samples from the Trans-Omics for Precision Medicine program and performed expression and splicing quantitative trait locus (e/sQTL) analyses in six tissues and cell types, including whole blood ( n = 6454) and lung ( n = 1291). We detected tens of thousands of secondary cis-e/sQTLs, showing that secondary cis-e/sQTL discovery remains unsaturated. We fine-mapped UK Biobank–derived genome-wide association study (GWAS) signals from 164 traits and identified e/sQTL colocalizations for 10,611 GWAS signals, including 7096 that colocalize with secondary e/sQTLs. Our results suggest that even larger e/sQTL analyses will uncover additional secondary e/sQTLs, further benefiting GWAS interpretation.
Caloric Restriction Intervention Alters Specific Circulating Biomarkers of the Senescence-Associated Secretome in Middle-Aged and Older Adults With Obesity and Prediabetes in an 18-Week Randomized Controlled Trial
Justice, Jamie N. , Leng, Xiaoyan , Kirkland, James L. , Mitin, Natalia , Liu, Yongmei , Kritchevsky, Stephen B. , Nicklas, Barbara J. , Ding, Jingzhong , Tchkonia, Tamara, Kritchevsky, Stephen B , Justice, Jamie N , LeBrasseur, Nathan K. , Tchkonia, Tamar
The Journals of Gerontology: Series A | September 22, 2023 | Volume: 79 | Issue: 1 | Pages: No page available
Abstract Cellular senescence is a biological aging process that is exacerbated by obesity and leads to inflammation and age- and obesogenic-driven chronic diseases including type 2 diabetes. Caloric restriction (CR) may improve metabolic function in part by reducing cellular senescence and the pro-inflammatory senescence-associated phenotype (SASP). We conducted an ancillary investigation of an 18-week randomized controlled trial (RCT) of CR (n = 31) or Control (n = 27) in 58 middle-aged/older adults (57.6 ± 5.8 years; 75% Women) with obesity and prediabetes. We measured mRNA expression of select senescence and apoptosis genes in blood CD3 + T cells (qRT-PCR) and a panel of 25 plasma SASP proteins (Luminex/multiplex; ELISA). Participants randomized to CR lost −10.8 ± 0.9 kg (−11.3% ± 5.4%) over 18 weeks compared with +0.5 ± 0.9 kg (+0.03% ± 3.5%) in Control group. T-cell expression of senescence biomarkers, p16INK4a and p21CIP1/WAF1, and apoptosis markers, BCL2L1 and BAK1, was not different between CR and Control groups in age, race, and sex-adjusted mixed models (p > .05, all). Iterative principal axis factor analysis was used to develop composite SASP Factors, and the Factors comprising TNFRI, TNFRII, uPAR, MMP1, GDF15, OPN, Fas, and MPO were significantly altered with CR intervention (age, sex, race-adjusted mixed model time × treatment F = 4.17, p ≤ .05) and associated with the degree of weight loss (R2 = 0.12, p ≤ .05). Our study provides evidence from an RCT that specific circulating biomarkers of senescent cell burden are changed by CR in middle-aged and older adults with obesity and prediabetes. Future studies compare tissue and circulating levels of p16INK4a and pro-inflammatory SASP biomarkers in other populations, and interventions.