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127 citation(s) found for "Wheeler, A".

From Housing to Hotspots: Integrating a Housing-Based Measure of Individual Socioeconomic Status with Geospatial Analysis to Target Colorectal Cancer Screening in Rural Communities
Yao, Rebecca , Beenken, Madison, Watson, Dave , Wheeler, Philip H., Finch, Mike, Kelleher, Dan , Anil, Gokhan , Anderson, Trent, Madden, Kathy A., Okuno, Scott H. , Odedina, Folakemi T., Park, Eunice , Dugani, Sagar B., Sosso, Jessica , Sabarish, Shivani , Singh, Gurpreet, Lugo-Fagundo, Nahyr, Kim, W. Ray, Walker-Mcgill, Cheryl L., Juhn, Young J. , Lynch, Brian , Wi, Chung‐Il , Madden, Kathy A., Westfall, Erin , Sharma, Pravesh , Dugani, Sagar B. , Foss, Randy , Hidaka, Brandon H. , Singh, Gurpreet, Howick V, James F , Calvin, Andrew D. , Walker-McGill, Cheryl Lynn, Rennert, Lior , Cerhan, James R. , Beenken, Madison J, Kelleher, Dan P., Westfall, Erin C, Park, Eunice Y., Sharma, Pravesh , Foss, Randy M, Sosso, Jessica L

Mayo Clinic

No container title available | September 3, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.64898/2026.08.28.26361444 | PMID 42922856 Get It

ABSTRACT Purpose This study assesses the association between colorectal cancer (CRC) screening and a validated, housing-based measure of individual-level socioeconomic status (SES, called HOUSES hereafter) within rural communities and determines whether HOUSES-integrated geospatial analysis can be used to tailor interventions. Methods We used CRC screening data from a subset of Mayo Clinic Midwest patients living in cities without ready access to routine care in the Mayo Clinic Health System in 2019 to represent rural communities. At the individual level, we assessed the association between CRC screening rates and the HOUSES index, adjusting for age, sex, race/ethnicity, comorbidity, distance from home address to clinic, and area deprivation index, using a multilevel mixed-effects logistic regression model. Additionally, we conducted geospatial analysis to examine the correlation between hotspots of 1) lower CRC screening rates and 2) lower SES of the subject population (HOUSES quartile 1). Findings Among 34,489 individuals (median age 64.0 years, 52.4% female), those with the lowest SES (HOUSES Q1) had 37% lower odds of being CRC screening adherent than those with the highest SES (HOUSES Q4) (adj. OR [95% CI]: 0.63 [0.58-0.69]). In the 14 identified HOUSES Q1 hotspots, there was a significant correlation in counts of HOUSES Q1 and low CRC screening (correlation coefficient=0.81). Conclusion Lower SES was significantly associated with lower CRC screening among rural populations. HOUSES-enabled geospatial analysis identified geographic hotspots with lower CRC screening rates for targeted interventions to address disparities in CRC screening in rural communities. HOUSES may be a useful digital tool for cancer preventive care and research.
Cross-cohort analysis of expression and splicing quantitative trait loci in TOPMed
Blackwell, Thomas W., Kachuri, Linda , Castaldi, Peter J. , Cho, Michael H. , Christenson, Stephanie A. , Durda, Peter , Gabriel, Stacey , Hersh, Craig P. , Huntsman, Scott , Hwang, S.-J., Joehanes, Roby, Johnson, Mari , Li, Xingnan , Lin, Honghuang , Liu, Ching‐Ti , Liu, Yongmei , Mak, Angel C. Y. , Manichaikul, Ani , Paik, David T. , Saferali, Aabida , Smith, Joshua D. , Taylor, Kent D. , Wang, Jiongming , Weinstock, Joshua S. , Weiss, Jeffrey, Wheeler, Heather E. , Zhou, Ying , Zoellner, Sebastian, Mestroni, Luisa , Graw, Sharon , Taylor, Matthew R.G. , Ortega, Victor E. , Johnson, Craig , Gan, Weiniu , Abecasis, Gonçalo , Nickerson, Deborah A. , Ardlie, Kristin G., Woodruff, Prescott G. , Bowler, Russell P. , Meyers, Deborah A. , Reiner, Alex, Kooperberg, Charles , Ziv, Elad , Vasan, Ramachandran S. , Silverman, Edwin K. , Rich, Stephen S., Heard‐Costa, Nancy L. , Tang, Hua, Rotter, Jerome I. , Smith, Albert V. , Aguet, François, Scott, Laura J. , Raffield, Laura M. , Parker, Stephen C.J. , Abe, Namiko, Almasy, Laura, Ament, Seth, Anugu, Pramod, Auer, Paul, Avramopoulos, Dimitrios, Balasubramanian, Adithya, Barr, R. Graham, Barwick, Lucas, Beaty, Terri, Becker, Diane, Becker, Lewis, Beitelshees, Amber, Benos, Takis, Bezerra, Marcos, Bis, Joshua, Brody, Jennifer, Broeckel, Ulrich, Broome, Jai, Bunting, Karen, Buth, Erin, Carey, Vincent, Carty, Cara, Casaburi, Richard, Chaffin, Mark, Chang, Christy, Chang, Yi-Cheng, Chavan, Sameer, Chen, Bo-Juen, Chen, Wei-Min, Choi, Seung Hoan, Chuang, Lee-Ming, Chung, Ren-Hua, Conomos, Matthew, Cornell, Elaine, Crandall, Carolyn, Crapo, James, Curtis, Jeffrey, Damcott, Coleen, David, Sean, Fuentes, Lisa de las, Vries, Paul de, Deka, Ranjan, DeMeo, Dawn, Devine, Scott, Dinh, Huyen, Doddapaneni, Harsha, Duan, Qing, Duggirala, Ravi, Eaton, Charles, Ekunwe, Lynette, Boueiz, Adel El, Emery, Leslie, Farber, Charles, Farek, Jesse, Franceschini, Nora, Frazar, Chris, Fu, Mao, Fullerton, Stephanie M., Fulton, Lucinda, Gao, Shanshan, Gao, Yan, Gass, Margery, Geiger, Heather, Ghosh, Auyon, Gignoux, Chris, Glahn, David, Gogarten, Stephanie, Gong, Da-Wei, Goring, Harald, Grine, Daniel, Gu, C. 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, Pankow, James, 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, Rich, Stephen S. , Pankow, James S. , Reiner, Alex P. , Aguet, François , Johnson, W. Craig , Ardlie, Kristin , Orchard, Peter , Kachuri, Linda , Castaldi, Peter J , Cho, Michael H , Christenson, Stephanie A , Durda, Peter , Hersh, Craig P , Huntsman, Scott , Hwang, Seungyong , Joehanes, Roby , Johnson, Mari , Li, Xingnan , Lin, Honghuang , Liu, Ching-Ti , Liu, Yongmei , Mak, Angel C Y , Manichaikul, Ani W , Paik, David T , Smith, Joshua D , Taylor, Kent D , Tracy, Russell P , Wang, Jiongming , Wang, Mingqiang , Weinstock, Joshua S , Weiss, Jeffrey , Wheeler, Heather E , Zhou, Ying , Zöllner, Sebastian , Wu, Joseph C , Mestroni, Luisa , Graw, Sharon , Taylor, Matthew R G , Ortega, Victor E , Johnson, W Craig , Gan, Weiniu , Gupta, Namrata , Ardlie, Kristin , Woodruff, Prescott G , Bowler, Russell P , Reiner, Alexander P , Kooperberg, Charles , Ziv, Elad , Vasan, Ramachandran S , Silverman, Edwin K , Rich, Stephen S , Heard-Costa, Nancy , Tang, Hua , Rotter, Jerome I , Smith, Albert V , Levy, Daniel , Aguet, François , Scott, Laura J , Raffield, Laura M , Parker, Stephen C J , Pankow, James S , Tracy, Russell P. , Wu, Joseph C. , Larson, Martin G. , Cupples, L. Adrienne , Abe, Namiko, Almasy, Laura, Ament, Seth, Anugu, Pramod, Auer, Paul, Avramopoulos, Dimitrios, Balasubramanian, Adithya, Barr, R. Graham, Barwick, Lucas, Beaty, Terri, Becker, Diane, Becker, Lewis, Beitelshees, Amber, Benos, Takis, Bezerra, Marcos, Bis, Joshua, Brody, Jennifer, Broeckel, Ulrich, Broome, Jai, Bunting, Karen, Buth, Erin, Carey, Vincent, Carty, Cara, Casaburi, Richard, Chaffin, Mark, Chang, Christy, Chang, Yi-Cheng, Chavan, Sameer, Chen, Bo-Juen, Chen, Wei-Min, Choi, Seung Hoan , Chuang, Lee-Ming, Chung, Ren-Hua, Conomos, Matthew, Cornell, Elaine, Crandall, Carolyn, Crapo, James, Curtis, Jeffrey, Damcott, Coleen, David, Sean, Fuentes, Lisa de las, Vries, Paul de, Deka, Ranjan, DeMeo, Dawn, Devine, Scott, Dinh, Huyen, Doddapaneni, Harsha, Duan, Qing, Duggirala, Ravi, Eaton, Charles, Ekunwe, Lynette, Boueiz, Adel El, Emery, Leslie, Farber, Charles, Farek, Jesse, Franceschini, Nora, Frazar, Chris, Fu, Mao, Fullerton, Stephanie M., Fulton, Lucinda, Gao, Shanshan, Gao, Yan, Gass, Margery, Geiger, Heather, Ghosh, Auyon, Gignoux, Chris, Glahn, David, Gogarten, Stephanie, Gong, Da-Wei, Goring, Harald, Grine, Daniel, Gu, C. 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

Mayo Clinic

Science | July 16, 2026 | Volume: 393 | Issue: 6808 | Pages: No page available

10.1126/science.adx2989 | PMID 42462027 Get It

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.
Toward autonomous robotic-assisted and microrobotic surgery
Yang, Sungyun , Kang, Byung Ha , Min, Hyeongho , Wachs, Juan , Alambeigi, Farshid , Desai, Jaydev P. , Yaeger, Kurt , Anderson, Katherine, Kuntz, Alan , Alterovitz, Ron , Webster, Robert J. , Hata, Nobuhiko , Reisenauer, Janani , Clinch, McKenna, Abramson, Alex , Wu, Jie Ying , Ranzani, Tommaso , Kim, Peter C., Huang, Alex S. , Zhang, Hao F. , Riviere, Cameron N. , Henderson, Eric R. , Yip, Michael C. , Dong, Xiaoguang , Wollin, Daniel , Mair, Lamar O. , Karpelson, Michael , Wood, Robert J. , Cohen, Itai , Strano, Michael S. , Wachs, Juan P , Dupont, Pierre E , Yaeger, Kurt , Anderson, Katherine , Kuntz, Alan , Alterovitz, Ron , Webster, Robert J , Hata, Nobuhiko , Reisenauer, Janani S , Clinch, McKenna , Abramson, Alex , Wu, Jie Ying , Ranzani, Tommaso , Sun, Cheng , Zhang, Hao F , Riviere, Cameron N , Henderson, Eric R , Yip, Michael , Dong, Xiaoguang , Wollin, Daniel A , Gracias, David H , Mair, Lamar O , Karpelson, Michael , Wood, Robert J , Cohen, Itai , Strano, Michael S

Mayo Clinic

Science Advances | July 1, 2026 | Volume: 12 | Issue: 27 | Pages: No page available

10.1126/sciadv.aec4197 | PMID 42384805 Get It

Autonomous robotic-assisted surgery (RAS) has emerged as a promising objective in biomedical technology, further enhanced by miniaturization toward microrobotic-assisted surgery (μ-RAS). This reduction in scale promises minimally invasive, partially or fully automated surgical procedures, with the potential to reduce patient recovery times, lower medical costs, and enable previously unavailable procedural options. This perspective highlights the specific advances in RAS that potentially map to the microscale (μ-RAS), organized across five surgical domains: endovascular, endoluminal, laparoscopic, ophthalmic, and orthopedic. We examine both clinical demands and technological advances in surgical robotics and identify the key innovations required for progress across these surgical fields. Our contribution is distinct in combining the perspectives of both surgical experts and bioengineering innovators, outlining a roadmap for the advancement and eventual integration of autonomous RAS and μ-RAS into mainstream surgical practice.
Exploring Healthcare Continuity in Pediatric‐Onset Multiple Sclerosis in the United States
Abrams, Aaron , Waltz, Michael , Race, Jonathan, Casper, T. Charles, Gambrah‐Lyles, Claudia, O’Neill, Kimberly, Wright, Melissa A. , Poisson, Kelsey E. , Bernfeld, Eva‐Chava M., Aaen, Gregory, Benson, Leslie A., Chitnis, Tanuja, Francisco, Carla, Gorman, Mark , Lotze, Timothy E., Mar, Soe, Ness, Jayne, Schreiner, Teri , Shukla, Nikita, Tillema, Jan‐Mendelt, Weinstock‐Guttman, Bianca, Wheeler, Yolanda, Waubant, Emmanuelle, Rose, John W. , Abrams, Aaron , Wright, Melissa A , Gombolay, Grace Y , Race, Jonathan , Casper, T. Charles , Gambrah-Lyles, Claudia , O'Neill, Kimberly , Virupakshaiah, Akash , Fisher, Kristen , Bernfeld, Eva Chava, Aaen, Gregory , Benson, Leslie , Chitnis, Tanuja , Francisco, Carla , Gombolay, Grace , Graves, Jennifer , Krupp, Lauren , Mar, Soe , Ness, Jayne , Rensel, Mary R. , Rodriguez, Moses , Schreiner, Teri , Tillema, Jan‐Mendelt , Weinstock‐Guttman, Bianca , Wheeler, Yolanda , Waubant, Emmanuelle L.

Mayo Clinic

Annals of the Child Neurology Society | June 25, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1002/cns3.70070 | PMID 42751265 Get It

ABSTRACT Objective Little is known about shifting from pediatric to adult‐focused multiple sclerosis (MS) care. This study aims to explore transition of care and follow‐up in the US pediatric‐onset MS (POMS) population. Methods Surveys were distributed to 10 sites in the US Network of Pediatric MS Centers (US NPMSC) about transition‐of‐care practices. A cohort of POMS/clinically isolated syndrome (CIS) at 12 US NPMSC sites was analyzed. The primary comparison was between < 18 and ≥ 18‐years of age. The primary outcome was 1‐ and 2‐year lapse in last follow‐up visit, measured from last recorded database visit to data lock date or, if ≥ 18 years of age, up to 1 year after a patient reached their site's typical transition age, if earlier. Secondary outcomes were baseline factors associated with follow‐up lapse. The model was adjusted for preidentified confounders. Results Compared with < 18 years, age ≥ 18 was associated with greater hazard of 1‐ and 2‐year follow‐up lapse. In POMS/CIS, the estimated hazard was 1.61 for 1‐year lapse (95% confidence interval [CI] 1.32–1.97, p < 0.001) and 1.40 for 2‐year lapse (95% CI 1.11–1.76, p = 0.004). In POMS‐only, the estimated hazard was 1.70 for 1‐year lapse (95% CI 1.33–2.18, p < 0.001) and 1.49 for 2‐year lapse (95% CI 1.11–1.99, p = 0.007). Platform injectable disease‐modifying therapy was associated with greater and intravenous with lesser hazard of lapse in follow‐up, while MS was associated with lower hazard than CIS. Conclusion Variable transition‐of‐care practices and barriers were reported by major US POMS centers. Before typical transition age, age ≥ 18 was associated with greater hazard of 1‐ and 2‐year follow‐up lapse than < 18. Developing standardized, targeted transition‐of‐care practices in POMS may be important.
Beyond Rurality: Individual Socioeconomic Status and Chronic Disease Prevalence
Sabarish, Shivani , Wi, Chung-Il, Beenken, Madison, Watson, Dave , Prissel, Christine M. , Wheeler, Philip H., Kelleher, Dan , Anil, Gokhan , Park, Eunice Y., Singh, Gurpreet, Lugo-Fagundo, Nahyr S, Howick, Jimmy F., Walker-Mcgill, Cheryl L., DUGANI, SAGAR, Pongdee, Thanai, Sosso, Jessica , Foss, Randy , Varkey, Prathibha, Juhn, Young J. , Wi, Chung‐Il , Wi, Chung-Ii , Patten, Christi A. , Wheeler, Philip, Lugo-Fagundo, Nahyr, Howick V, James F, Sharma, Pravesh , Dugani, Sagar B , Sosso, Jessica L , Foss, Randy M, Foss, Randy , Brockman, Tabetha A. , Wheeler, Philip H., Anderson, Trent, Lugo‐Fagundo, Nahyr , Walker-McGill, Cheryl Lynn, Hidaka, Brandon H. , Sharma, Pravesh , Dugani, Sagar B. , Pongdee, Thanai , Garovic, Vesna D.

Mayo Clinic

No container title available | April 6, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.64898/2026.04.02.26350063 | PMID 41959832 Get It

ABSTRACT Importance Rural-urban disparities in chronic disease prevalence are well established; however, the extent to which individual-level socioeconomic status (SES) contributes to these disparities remains unclear. Objective To examine the associations of rurality and SES with the prevalence of five most burdensome chronic diseases among adults. Design We conducted a retrospective cross-sectional study of adults across 27 Upper Midwest counties using the Expanded Rochester Epidemiology Project (E-REP) medical record data linkage system to evaluate associations between rurality, SES and chronic disease prevalence. Prevalence of clinically diagnosed asthma, diabetes, hypertension, coronary heart disease, and mood disorders was identified from International Classification of Diseases ICD9/10 codes over a five-year period (2014-2019). Setting Population based Participants Adults over 18 years residing in the 27 E-REP counties, excluding those missing rural-urban residence status. Exposure HOUSES index, an individual-level measure of SES, served as the primary measure, while rurality based on Rural Urban Commuting Area (RUCA) codes 4-10 was the secondary measure. Main Outcome Prevalence of the five clinically diagnosed chronic diseases was identified using ICD9/10 codes from 2014–2019. Mixed effect logistic regression models were used and adjusted for demographics and general medical examination receipt, to assess rural-urban and SES differences for prevalence of each chronic disease. Results Among 455,802 adults with available HOUSES index, 42.8% lived in rural areas, 53.8% were female and 87.4% were non-Hispanic White. In the unadjusted analysis, rural and urban populations showed comparable asthma and CHD prevalence, while mood disorders, hypertension, and diabetes were more common in urban areas. After adjusting for demographic factors and healthcare utilization, rural-urban differences were no longer statistically significant, whereas SES remained strongly associated with all diseases in a dose response manner (e.g., adjusted Odds Ratio for hypertension (ref: HOUSES index Q4): 1.14, 1.27, and 1.42 for HOUSES index Q3, Q2, and Q1, respectively). Conclusions and Relevance Individual-level SES measured by the HOUSES index, was more strongly associated with chronic disease prevalence than rurality, supporting its integration into population health assessment and risk stratification.
Circulating Nucleosomes are Elevated in Trauma Patients with Venous Thromboembolism: A Prospective Case-Cohort Study
Thompson, Riley J., Spears, Grant M. , Bailey, Kent R., Kelly, Theresa K., Wheeler, Christina, Dong, Jing-Fei, Kozar, Rosemary A. , Park, Myung S., Navarro, Sergio M. , Bailey, Kent R. , Kelly, Theresa Kathleen , Chen, Dong

Mayo Clinic

Shock | March 26, 2026 | Volume: 66 | Issue: 3 | Pages: 666-675

10.1097/shk.0000000000002807 | PMID 41886536 Get It

Objective: The identification of reliable biomarkers in trauma patients (pts) remains a clinical challenge. Nucleosomes, which are DNA wrapped around histone protein cores, have been used as reliable markers for quantification in sepsis, acute respiratory distress syndrome, and lymphoma. We hypothesized that: 1) levels of circulating nucleosomes quantified after traumatic injury, specifically histone H3.1 and its citrullinated R8 posttranslation modification (H3R8 Cit), would be increased after trauma and 2) that levels of circulating nucleosomes would be further, increased in pts who went on to develop venous thromboembolism (VTE), as these nucleosomes may be clot-enhancing mediators. Methods: Trauma pts presenting to a Level I trauma center were evaluated for inclusion in a prospective case-cohort study, and citrated blood samples were collected within 12 hours of injury. Pts were followed for up to 90 days and VTE occurrence was confirmed via autopsy or imaging. Pts who developed incident, symptomatic VTE, and those who did not develop VTE were selected at a 1:3 ratio. The effect of trauma was assessed by comparison with healthy volunteer samples. Circulating nucleosomes were quantified using Nu.Q H3.1 and Nu.Q H3R8 Cit assays. Data are presented as median [interquartile range] or n (%), with Wilcoxon Rank-Sum or chi-squared test performed between trauma pts who developed symptomatic VTE versus those who did not, with a P value < 0.05 as statistically significant. Results: A total of 639 trauma pts were analyzed [51 years (33, 65), 71.0% male, 94.1% blunt, injury severity scores 17 (9, 27)]. Both H3.1 [359.7 (58.4, 1769.3) vs. 21.5 (15.3, 26.6) ng/mL, P < 0.001] and H3R8 Cit levels [209.4 (45.4, 665.5) vs. 22.3 (16.2, 28.9) ng/mL, P < 0.001] were greater in trauma pts than in 10 healthy volunteers. The 160 pts with VTE were then compared with 479 without VTE. VTE pts had a median time to VTE of 8.5 days, with 91 developing symptomatic deep venous thrombosis, 48 with pulmonary embolism, and 21 with both deep venous thrombosis and pulmonary embolism. No significant differences were found in age, sex, or mechanism between pts with or without VTE. However, VTE pts had higher injury severity scores [24 (14, 34), 14 (9, 24), P < 0.001] and body mass index [29.1 (24.3, 34.2), 27.6 (24.2, 32.0) kg/m 2 , P = 0.037]. A greater percentage of VTE pts underwent surgery requiring general anesthesia (53.1%, 34.0%, P < 0.001) and received blood transfusions within 24 hours of injury (51.9%, 24.0%, P < 0.001). H3.1 levels were significantly greater in trauma pts who developed VTE compared with those who did not [828.4 (112.0, 3186.5), vs. 276.7 (50.3, 1237.0) ng/mL, P < 0.001], as were H3R8 Cit levels [350.4 (77.4, 729.5), vs. 189.2 (40.8, 632.6) ng/mL, P = 0.005]. No differences in levels of H3.1 and H3R8 Cit were found between early (diagnosed day 0–7 after injury) and late (diagnosed > day 7) VTE. Conclusions: Levels of the H3.1 and H3R8 Cit nucleosomes are elevated early after traumatic injury, especially in those who developed VTE. These findings underscore the importance of understanding the pathophysiology of nucleosomes in inducing VTE and their role as biomarkers
Abstract PS2-07-17: Characterizing circulating tumor cell (CTC) enumeration and phenotypic profiling in blood with synchronously obtained tissue in metastatic breast cancer (MBC) in TBCRC /AURORA US
Giridhar, K. V., Nenad, W. C., Ye, H., Wheeler, G. L., Hinoue, T., Michmerhuizen, A. R., Felsheim, B. M., Chandran, U. R., Kelly, B. J., Mardis, E. R., Laird, P. W., Balko, J. M., Garrido-Castro, A. C., Coppens, Sara E. , Bowen, J., Nanda, R., Lin, N. U., Anders, C. K., Isaacs, C., Tao, J. J., Anampa, J. D., Jahan, N., Huppert, L., DeMichele, A., Park, B. H., Vinayak, Shaveta , Delson, A. L., Magbanua, M. M., Balic, M., Parsons, H. A., Lee, A. V., Carey, L. A., Norton, Larrw, Wolff, A. C., Davidson, N. E., Krop, I., King, T. A., Perou, C. M., Hoadley, K. A., Network, Aurora US Metastases, Giridhar, K. V., Wheeler, G. L., Hinoue, T., Michmerhuizen, Anna R. , Felsheim, Brooke , Kelly, B. J., Mardis, E. R., Laird, P. W., Balko, J. M., Garrido-Castro, Ana C. , Nanda, Rita , Lin, N. U., Anders, Carey K. , Isaacs, Claudine , Anampa, J. D., Jahan, N., Huppert, L. A., DeMichele, Angie, Park, B. H., Delson, A. L., Magbanua, MJM, Balic, M., Parsons, H. A., Lee, A. V., Wolff, Antonio C , Davidson, N. E., Krop, Ian E. , King, T. A., Perou, Charles M. , Hoadley, K.A., Network, AURORA US

Mayo Clinic

Clinical Cancer Research | February 20, 2026 | Volume: 32 | Issue: 4_Supplement | Pages: PS2-07-17-PS2-07-17

10.1158/1557-3265.sabcs25-ps2-07-17 Get It

Abstract Background: In MBC, CTC enumeration is highly prognostic for both progression free survival (PFS) and overall survival (OS). Multiparametric technologies enable for expanded phenotypic profiling of CTCs, including ER and HER2 assessment. Limited information is available on the concordance of CTC ER and HER2 levels compared to synchronously obtained tissue. We assessed the prognostic performance of CTC enumeration and phenotypic profiling of ER and HER2 on CTCs. Methods: The prospective, multi-institutional Aurora study enrolled pts with MBC of any subtype either at diagnosis of metastatic disease or at time of progression on any line of systemic therapy. Pts underwent a metastatic site biopsy, consented to archival primary tissue collection and donated blood samples serially every 3-4 months until progression. CTCs, from blood collected at study entry, were identified as nucleated, EpCAM+/ cytokeratin+/ CD45- cells using an automated imaging system (RareCyte, Seattle). ER and HER2 expression levels were measured by mean fluorescence intensity (MFI), with thresholds above 80 (ER) and 160 (HER2) considered positive. Comparisons were made to total RNAseq from paired metastatic tissue biopsies. PFS and OS were calculated from the time of study entry to last follow up or death. Results: Baseline CTC enumeration was performed in 154 pts. The most common clinical subtype was HR+/HER2- (59.7%), followed by HER2-positive (16.8%) and TNBC (15.5%). The median lines of prior therapy were 1 (range 0-10). At least 1 CTC was identified in 68/154 pts (44%), 30 (19%) had ≥ 5 CTCs, and 15 (9.7%) had CTC clusters. The median CTC value was 0 (0-877). The presence of CTCs (≥1 or ≥5) and CTC clusters was adversely associated with PFS and OS (Table 1 Table 1. CTC survival analyses Number Median PFS PFS HR (95% CI) Median OS OS HR (95% CI) Presence of CTC 0 CTC 86 7.37 (0.03 - 43.1) reference 20.72 (0.03 - 50.6) reference ≥ 1 CTC 68 4.7 (0.43 - 19.5) 1.65 (1.16-2.36) 12.04. (0.43-44.1) 2.13 (1.44-3.16) Presence of ≥ 5 CTC &lt;5 CTC 124 7.7 (0.03 - 43.1) reference 19.31 (0.03 - 50.6) reference ≥ 5 CTC 30 2.88 (0.43 - 18.7) 1.77 (1.15 - 2.71) 5.74 (0.43 - 29.3) 3.59 (2.26-5.70) Presence of clusters 0 clusters 139 7.37 (0.03 - 43.1) reference 18.06 (0.03 - 50.6) reference ≥ 1 cluster 15 1.91 (0.43 - 18.7) 2.06 (1.16 - 3.68) 3.42 (0.43 - 18.7) 5.44 (2.94-10.09) ). Across all subtypes, the median CTC ER-MFI across was 36.2 (range 4.2-10,016.6) and the median HER2-MFI was 139.6 (range 4.2-2480.5). We observed high intra-patient heterogeneity of ER-MFI (CV: 0.65 [0.34-1.25]) and HER2-MFI (CV: 0.79 [0.42-1.54]). Clinical metastatic subtype from metastasis at study entry was available in 54/68 pts with CTCs. Pts with clinical ER+ MBC had a higher median ER-MFI compared to clinical TNBC (111.9 vs 68.6, p = 0.02). However, 11 pts (26.8%) with clinical ER+ MBC had all CTCs with an ER-MFI &lt;80. Lower ER expression was observed in CTCs collected after prior exposure to a SERD (median ER-MFI: post-SERD [n=8] 27 vs post-aromatase inhibitor [n=4] 252, p&lt;2.22e-16). No correlations were observed between the median CTC ER-MFI or HER2-MFI and paired tissue ESR1 or ERBB2 RNA expression (n=66). Conclusions: CTCs are strongly predictive of PFS and OS. CTC ER- and HER2-MFI were highly heterogeneous without clear correlation with bulk tissue RNA expression. The clinical impact of discordant clinical receptor status and CTC receptor status warrants further exploration. Citation Format: K. V. Giridhar, W. C. Nenad, H. Ye, G. L. Wheeler, T. Hinoue, A. R. Michmerhuizen, B. M. Felsheim, U. R. Chandran, B. J. Kelly, E. R. Mardis, P. W. Laird, J. M. Balko, A. C. Garrido-Castro, S. Coppens, J. Bowen, R. Nanda, N. U. Lin, C. K. Anders, C. Isaacs, J. J. Tao, J. D. Anampa, N. Jahan, L. Huppert, A. DeMichele, B. H. Park, S. Vinayak, A. L. Delson, M. M. Magbanua, M. Balic, H. A. Parsons, A. V. Lee, L. A. Carey, L. Norton, A. C. Wolff, N. E. Davidson, I. Krop, T. A. King, C. M. Perou, K. A. Hoadley, Aurora US Metastases Network. Characterizing circulating tumor cell (CTC) enumeration and phenotypic profiling in blood with synchronously obtained tissue in metastatic breast cancer (MBC) in TBCRC /AURORA US [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS2-07-17.
Telomere length as a marker of biological age in paediatric multiple sclerosis
Jacques, Kayla , Race, Jonathan , Goyne, Christopher, Fair, Ashley, Schuette, Allison, Yang, Jennifer H. , Caillier, Stacy J. , Aaen, Gregory Scott, Abrams, Aaron , Benson, Leslie, Casper, T Charles, Chitnis, Tanuja, Gorman, Mark , Lotze, Tim, Mar, Soe , Ness, Jayne , Rose, John W. , Schreiner, Teri , Tillema, Jan-Mendelt , Waldman, Amy T, Wheeler, Yolanda , Oksenberg, Jorge, Lin, Jue , Waubant, Emmanuelle, Aaen, Gregory S , Krupp, Lauren , Wheeler, Yolanda S , Yang, Jennifer H , Aaen, Gregory , Benson, Leslie , Casper, T. Charles , Chitnis, Tanuja , Rensel, Mary R. , Rodriguez, Moses , Schreiner, Teri , Tillema, Jan‐Mendelt , Waldman, Amy , Oksenberg, Jorge R. , Waubant, Emmanuelle L. , Graves, Jennifer

Mayo Clinic

Journal of Neurology, Neurosurgery & Psychiatry | February 17, 2026 | Volume: 97 | Issue: 4 | Pages: 302-308

10.1136/jnnp-2025-336736 | PMID 41500800 Get It

Background Increased chronological age correlates with reduced relapse rates and increased disability in multiple sclerosis (MS). Biological age may better capture ageing’s impact on MS and might accelerate due to MS itself. Establishing accelerated biological ageing in adults is complicated by normal ageing and comorbidities. Telomere length, a well-recognised biological ageing marker, is shortened in adults with MS and associated with disability. Demonstrating accelerated biological ageing in paediatric-onset MS (POMS) would strengthen the hypothesis that MS drives premature biological ageing. This study aimed to determine if telomere length differs in POMS compared to age-similar healthy controls. Methods We performed a cross-sectional case-control study of whole blood samples and clinical data from The US Network of Pediatric MS Centers. Real-time quantitative PCR measured telomere length, expressed as a telomere to somatic DNA ratio (T/S ratio). T/S ratio was compared between cases and age-similar healthy controls using multivariate regression analysis adjusting for chronological age, sex, race, ethnicity, tobacco exposure, socioeconomic status and body mass index. Results We analysed 300 POMS cases and 200 controls. The unadjusted mean T/S ratios were 1.66 (SD 0.32) for cases and 1.71 (SD 0.29) for controls (mean difference –0.05, 95% CI –0.10 to 0.01, p=0.08). After adjusting for key covariables with face validity, POMS participants had a mean 0.086 shorter T/S ratio than controls (95% CI 0.015 to 0.157, p=0.018). Conclusions POMS participants demonstrated shorter telomeres than age-similar controls in a multivariable model adjusting for sociodemographic variables, suggesting that MS may contribute to accelerated biological ageing.
Abstract PD3-09: Molecular characterization of resistance to antibody drug conjugates in metastatic breast cancer: a prospective analysis from the AURORA US Network
Garrido-Castro, A. C., Nenad, W. C., Balko, J. M., Hinoue, T., Wheeler, G. L., Kelly, B. J., Felsheim, B. M., Michmerhuizen, A. R., Chandran, UR, Lee, A. V., Carey, L. A., King, T. A., Mardis, ER, Laird, P. W., Giridhar, K. V., Hoadley, K. A., Perou, C. M., Garrido-Castro, Ana C. , Nenad, William , Hinoue, T., Singha, Manali , Felsheim, Brooke , Michmerhuizen, Anna R. , Hoadley, Katherine A. , Perou, Charles M.

Mayo Clinic

Clinical Cancer Research | February 17, 2026 | Volume: 32 | Issue: 4_Supplement | Pages: PD3-09-PD3-09

10.1158/1557-3265.sabcs25-pd3-09 Get It

Abstract Introduction: With emerging antibody drug conjugates (ADC) as treatment of metastatic breast cancer (mBC), it is key to understand the mechanisms that drive resistance to inform optimal ADC selection and sequencing. The AURORA (AUR) US Network was established to characterize paired primary and metastatic (met) samples via multiplatform profiling, with a prospective phase of met tissue collection that included pre and post-ADC samples. Methods: Fresh frozen or FFPE met and archival primary tumors were analyzed across 3 platforms: DNA low pass whole genome and exome sequencing (WES), DNA methylation arrays (Methyl) and RNA sequencing (RNA seq). The molecular cohort included pts with data from ≥1 platform. Pairwise gene expression comparisons were performed in R using t-tests, and pathway analysis with GSEA. Results: A total of 168 pts comprised the molecular cohort: WES, 168; Methyl, 163; RNA seq, 168. Median age at mBC diagnosis was 56 (28-88). 21 pts (12.5%) had known germline BRCA1/2 mutations; 37 (22.0%) presented with de novo mBC. Subtype at mBC (if not available, at primary) diagnosis was: 108 (64.3%) HR+/HER2-, 22 (13.1%) HER2+, 33 (19.6%) TNBC and 5 (3.0%) unknown. Among 139 pts with known subtype in the first AUR met collected, 95 (68.3%) were HR+/HER2-, 17 (12.2%) HER2+ and 27 (19.4%) TNBC. 72 pts received ≥1 ADC with 1 (0-4) median line of chemotherapy for mBC prior to ADC1. As ADC1, 42 pts received HER2 ADC (35 trastuzumab deruxtecan, T-DXd; 7 trastuzumab emtansine), 29 TROP2 ADC (28 sacituzumab govitecan, SG; 1 datopotamab deruxtecan) and 1 NECTIN4 ADC. 22 pts received ≥2 ADC (16 immediate sequence; 6 intervening therapy); 11 T-DXd and 11 SG as ADC2. Median duration of ADC1 was 141 days (6-522); 81 (7-425) for ADC2. Progressive disease was the most common reason for ADC discontinuation, denoting resistance in post-ADC samples. 99 samples were collected pre-ADC1 and 24 post-ADC1, of which 5 were pre-ADC2. ERBB2 expression did not differ between samples after HER2 (n=9) vs non-HER2 ADC (n=8) (p=0.55), nor did TACSTD2 after TROP2 (n=8) vs non-TROP2 ADC (n=9) (p=0.16). In pts with HER2+ subtype at mBC diagnosis or AUR collection who received HER2 ADC, ERBB2 expression significantly decreased in post (n=4) vs pre-treatment (n=7) samples (p=0.043). ERBB2 downregulation was observed in 5 pts with paired pre vs post-HER2 ADC samples. In pts who received TROP2 ADC, TACSTD2 expression did not differ in post (n=10) vs pre-treatment (n=47) samples (p=0.63). GSEA of post-ADC samples revealed significant pathway differences by payload, including actin cytoskeleton in post-microtubule inhibitor (MTi) vs non-MTi ADC samples (p=0.001) and ATM-dependent DNA damage response after topoisomerase I inhibitor (TOP1i) vs non-TOP1i ADCs (p=0.043). Lysosomal vesicle biogenesis (p=0.014) and calcium release (p=0.05) pathways significantly differed between ADC naïve vs treated metastases. ERBB2 hypermethylation was not detected in the cohort. TACST2 promoter methylation was observed in 10 samples (β value &gt;0.3) without association with TROP2 ADC exposure. ERBB2 or TACSTD2 mutations were not identified in the ADC-treated cohort. A novel loss-of-function (LOF) mutation in MED12 was detected in one pt immediately post-T-DXd. MED12 LOF has been reported to promote PARP inhibitor and platinum resistance in BRCA-deficient tumors and may represent a novel resistance mechanism to TOP1i. Conclusions: Multiplatform molecular characterization of mBC treated with ADC revealed potential mechanisms of resistance related to downregulation of target expression, payload (e.g., microtubule formation, DNA damage repair) and lysosomal processing. Additional analyses integrating these multimodal data are ongoing. Strategies to overcome resistance, e.g. modifying ADC target, are being evaluated in clinical trials. Citation Format: A. C. Garrido-Castro, W. C. Nenad, J. M. Balko, T. Hinoue, G. L. Wheeler, B. J. Kelly, M. Singha, B. M. Felsheim, A. R. Michmerhuizen, U. Chandran, A. V. Lee, L. A. Carey, T. A. King, E. Mardis, P. W. Laird, K. V. Giridhar, K. A. Hoadley, C. M. Perou. Molecular characterization of resistance to antibody drug conjugates in metastatic breast cancer: a prospective analysis from the AURORA US Network [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PD3-09.