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Mulvihill, Lindsay A.

Mayo Clinic

Mayo Clinic

Citations 2

Distribution of Chromosome-Arm Specific Telomere Length in Patients with Telomere Biology Disorders
Stephens, Zachary, Geyer, Susan M. , Simon, Rachel A, Finke, Christy M. , Burnap, Brittany, Mulvihill, Lindsay A., McAllister, Tammy M., Vitek, Carolyn R. Rohrer , Jain, Angita , Klee, Eric W. , Kocher, Jean‐Pierre , Patnaik, Mrinal M. , Ferrer, Alejandro , Lasho, Terra L. , Lazaridis, Konstantinos N.

Blood | December 1, 2023 | Volume: 142 | Issue: Supplement 1 | Pages: 4103-4103

10.1182/blood-2023-187486 Get It

Introduction: Telomere biology disorders (TBD) are multisystem diseases often associated with bone marrow failure (BMF) and pulmonary fibrosis. TBD are clinically diagnosed when mean telomere lengths (TL) in blood cells measured by clinical flowFISH assays fall <1 st percentile, in comparison to age-matched reference controls. This information has limitations, e.g. TL in blood cells may not represent TL in other organs (e.g. lung, liver) and moreover, individuals with high clinical suspicion of TBD can show borderline average TL which complicates their diagnosis. The likely reason for this is that cell senescence can be triggered by shortening of a subset, or even a single chromosome arm telomere, a situation that may be missed when measuring average TL. Previous approaches to measure individual chromosome-arm telomere length (CA-TL) are only available for a small number of chromosome arms or can only estimate the number of shortened telomeres without matching them to specific chromosome arms. Taking advantage of recent developments in long-read next generation sequencing (NGS) and the availability of the recently published telomere-to-telomere (T2T) reference human genome, our group developed Telogator, (Stephens Z. et al, 2022) a bioinformatic tool that estimates CA-TL for most chromosome arms using long-read NGS data. Here we use Telogator to describe for the first time the CA-TL pattern in TBD patients in comparison with a control non-TBD cohort. Methods: TBD patients were identified through the Pre-Myeloid and Bone Marrow Failure Specialty Clinic at Mayo Clinic. All patients underwent flowFISH and genetic testing. Age-matched non-TBD patients identified at the Center for Individualized Medicine (Mayo Clinic) were used as reference controls. Informed consent was obtained from all individuals with approval from the Mayo Clinic Institutional Review Board. DNA from peripheral blood mononuclear cells was sequenced using PacBio Sequel II following the manufacturer indications for HiFi sequencing. BAM files were aligned to the T2T reference and CA-TL was calculated using Telogator as described in Stephens Z. et al. 2022. Average TL, CA-TL, and percent of short telomeres (both defined as <5 kb and <3.2 kb) were calculated. Comparisons of average TL and percent of short telomeres were performed using t-test, while Wilcoxon rank-sum test was used to compare CA-TL. Results: Four TBD patients [median age = 58.5 (52-60), 50% female] and 6 non-TBD controls [Median age = 56 (50-63), 33% female] were included in the analysis. All TBD patients presented average TL below the 1 st centile in both lymphocytes and granulocytes, and TBD-related phenotype (100% with pulmonary fibrosis, 50% with BMF, 25% with liver fibrosis). Three had a pathogenic variant in a TBD related genes [2 in TERT (NM_198253.3: c.2030G>A, p.(Gly677Asp) and c.2515_2533del, p.(Thr839Alafs*29)) and 1 in NHP2 (NM_017838.3: c.459_460delAT; p.(X154Argext29))]. The average TL calculated by Telogator showed high correlation with flowFISH values (r 2 = 0.9883, p = 0.0059) and was lower in TBD patients than controls (p = 0.0012). Next, when comparing individual CA-TL between groups, only half of CA-TL was statistically different in the TBD group compared to controls (1p, 3q, 4p, 5p, 5q, 6q, 7p, 7q, 8q, 9p, 9q, 10q, 11p, 12q, 12q, 16p, 16q, 18q, 19p, 19q, 20p, 20q, 21q - Figure 1). The percentage of telomeres <5kb and <3 kb was significantly increased in TBD patients compared to controls (p= 0.014 and 0.0333, respectively). Discussion: Using a novel informatic tool, we replicate previous results obtained using classic approaches and were able to expand on these studies by measuring specific CA-TL in TBD patients. We identified statistically significant differences at the CA-TL level in these patients when compared to age-matched controls, while other CA-TL were not statistically different. Future studies and the inclusion of additional TBD patients will help define the clinical relevance of the differential CA-TL shortening and its prevalence among TBD patients. While limited by the small number of samples in the study, we show the feasibility of using this approach to study TL with unprecedented resolution and show that Telogator offers important advantages compared to classic methods to study telomere biology that can be used in other relevant fields like aging and/or cancer. Our results pave the way to advance the mechanistic understanding of TBD.
Implementation of genomic medicine for rare disease in a tertiary healthcare system: Mayo Clinic Program for Rare and Undiagnosed Diseases (PRaUD)
Kemppainen, Jennifer L., Vitek, Carolyn R. Rohrer , Whalen, Denise A., Kolbert, Kayla J., Sikkink, Kaitlin J. , Kroc, Sarah A., Kruisselbrink, Teresa , Shupe, Gabrielle F., Knudson, Alyssa K., Burke, Elizabeth , Loftus, Elle C., Bandel, Lorelei A. , Prochnow, Carri A., Mulvihill, Lindsay A., Thomas, Brittany C. , Gamble, Dale M., Graddy, Courtney B., Garzon, Giovanna G. Moreno, Ekpoh, Idara U., Porquera, Eva M. Carmona, Hogan, Marie C. , Ters, Mireille El , Davis, III John M., Vella, Adrian, Kumar, Seema , Creo, Ana L. , Lteif, Aida, Pittock, Siobhán T. , Tebben, Peter J. , Abate, Ejigayehu G., Joshi, Avni Y. , Ristagno, Elizabeth H. , Patnaik, Mrinal S., Sabrowsky, Sonia M., Wierenga, Klaas J. , Keddis, Mira T. , Samadder, N. Jewel , Presutti, R. John , Stephens, Michael C., Roberts, Lewis R. , Faubion, William A. , Driscoll, Sherilyn W. , Selcen, Duygu , Jackson, Lauren , Ortega, Victor E. , Anderson, Sarah , Aoudia, Stacy L., Klee, Eric W. , McAllister, Tammy M., Carmona, Eva M. , Carmona, Eva M , Roberts, Lewis R , Presutti, Richard J , Tebben, Peter , Hogan, Marie C , Vairo, Filippo Pinto e , Burke, Elizabeth M., Fervenza, Fernando C. , Warrington, Kenneth J. , Koster, Matthew J. , Orandi, Amir B. , Basiaga, Matthew L. , Patnaik, Mrinal S., Schimmenti, Lisa A. , Dhamija, Radhika , Robinson, Steven I. , Wong‐Kisiel, Lily C. , Flanagan, Eoin P. , Ramanan, Vijay K. , Mauermann, Michelle L. , Lazaridis, Konstantinos N.

No container title available | March 7, 2023 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.21203/rs.3.rs-2617916/v1 Get It

Abstract Background In the United States, rare disease (RD) is defined as a condition that affects fewer than 200,000 individuals. Collectively, RD affects an estimated 30 million Americans. A significant portion of RD has an underlying genetic cause; however, this may go undiagnosed. To better serve these patients, the Mayo Clinic Program for Rare and Undiagnosed Diseases (PRaUD) was created under the auspices of the Center for Individualized Medicine (CIM) aiming to integrate genomics into subspecialty practice including targeted genetic testing, research, and education. Methods Patients were identified by subspecialty healthcare providers from 11 clinical divisions/departments. Targeted multi-gene panels or custom exome/genome-based panels were utilized. To support the goals of PRaUD, a new clinical service model, the Genetic Testing and Counseling (GTAC) unit, was established to improve access and increase efficiency for genetic test facilitation. The GTAC unit includes genetic counselors, genetic counseling assistants, genetic nurses, and a medical geneticist. Patients receive abbreviated point-of-care genetic counseling and testing through a partnership with subspecialty providers. Results Implementation of PRaUD began in 2018 and GTAC unit launched in 2020 to support program expansion. Currently, 29 RD clinical indications are included in 11 specialty divisions/departments with over 142 referring providers. To date, 1,152 patients have been evaluated with an overall solve rate of 14.1% and as high as 66.7% depending on the phenotype. Noteworthy, 42.7% of the solved or likely solved patients underwent changes in medical management and outcome based on genetic test results. Conclusion Implementation of PRaUD and GTAC have enabled subspecialty practices advance expertise in RD where genetic counselors have not historically been embedded in practice. Democratizing access to genetic testing and counseling can broaden the reach of patients with RD and increase the diagnostic yield of such indications leading to better medical management as well as expanding research opportunities.