Publications

Anna L Gloyn
Professor of Pediatrics (Endocrinology) and of Genetics

Publications

  • Multiplexed CRISPR gene editing in primary human islet cells with Cas9 ribonucleoprotein. iScience Bevacqua, R. J., Zhao, W., Merheb, E., Kim, S. H., Marson, A., Gloyn, A. L., Kim, S. K. 2024; 27 (1): 108693

    Abstract

    Successful genome editing in primary human islets could reveal features of the genetic regulatory landscape underlying beta cell function and diabetes risk. Here, we describe a CRISPR-based strategy to interrogate functions of predicted regulatory DNA elements using electroporation of a complex of Cas9 ribonucleoprotein (Cas9 RNP) and guide RNAs into primary human islet cells. We successfully targeted coding regions including the PDX1 exon 1, and non-coding DNA linked to diabetes susceptibility. CRISPR-Cas9 RNP approaches revealed genetic targets of regulation by DNA elements containing candidate diabetes risk SNPs, including an invivo enhancer of the MPHOSPH9 gene. CRISPR-Cas9 RNP multiplexed targeting of two cis-regulatory elements linked to diabetes risk in PCSK1, which encodes an endoprotease crucial for Insulin processing, also demonstrated efficient simultaneous editing of PCSK1 regulatory elements, resulting in impaired beta cell PCSK1 regulation and Insulin secretion. Multiplex CRISPR-Cas9 RNP provides powerful approaches to investigate and elucidate human islet cell gene regulation in health and diabetes.

    View details for DOI 10.1016/j.isci.2023.108693

    View details for PubMedID 38205242

  • Heterogeneity of increased biological age in type 2 diabetes correlates with differential tissue DNA methylation, biological variables, and pharmacological treatments. GeroScience Cortez, B. N., Pan, H., Hinthorn, S., Sun, H., Neretti, N., Gloyn, A. L., Aguayo-Mazzucato, C. 2023

    Abstract

    Biological age (BA) closely depicts age-related changes at a cellular level. Type 2 diabetes mellitus (T2D) accelerates BA when calculated using clinical biomarkers, but there is a large spread in the magnitude of individuals' age acceleration in T2D suggesting additional factors contributing to BA. Additionally, it is unknown whether BA can be changed with treatment. We hypothesized that potential determinants of the heterogeneous BA distribution in T2D could be due to differential tissue aging as reflected at the DNA methylation (DNAm) level, or biological variables and their respective therapeutic treatments. Publicly available DNAm samples were obtained to calculate BA using the DNAm phenotypic age (DNAmPhenoAge) algorithm. DNAmPhenoAge showed age acceleration in T2D samples of whole blood, pancreatic islets, and liver, but not in adipose tissue or skeletal muscle. Analysis of genes associated with differentially methylated CpG sites found a significant correlation between eight individual CpG methylation sites and gene expression. Clinical biomarkers from participants in the NHANES 2017-2018 and ACCORD cohorts were used to calculate BA using the Klemera and Doubal (KDM) method. Cardiovascular and glycemic biomarkers associated with increased BA while intensive blood pressure and glycemic management reduced BA to CA levels, demonstrating that accelerated BA can be restored in the setting of T2D.

    View details for DOI 10.1007/s11357-023-01009-8

    View details for PubMedID 37987887

  • Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine. Nature medicine Tobias, D. K., Merino, J., Ahmad, A., Aiken, C., Benham, J. L., Bodhini, D., Clark, A. L., Colclough, K., Corcoy, R., Cromer, S. J., Duan, D., Felton, J. L., Francis, E. C., Gillard, P., Gingras, V., Gaillard, R., Haider, E., Hughes, A., Ikle, J. M., Jacobsen, L. M., Kahkoska, A. R., Kettunen, J. L., Kreienkamp, R. J., Lim, L. L., Männistö, J. M., Massey, R., Mclennan, N. M., Miller, R. G., Morieri, M. L., Most, J., Naylor, R. N., Ozkan, B., Patel, K. A., Pilla, S. J., Prystupa, K., Raghavan, S., Rooney, M. R., Schön, M., Semnani-Azad, Z., Sevilla-Gonzalez, M., Svalastoga, P., Takele, W. W., Tam, C. H., Thuesen, A. C., Tosur, M., Wallace, A. S., Wang, C. C., Wong, J. J., Yamamoto, J. M., Young, K., Amouyal, C., Andersen, M. K., Bonham, M. P., Chen, M., Cheng, F., Chikowore, T., Chivers, S. C., Clemmensen, C., Dabelea, D., Dawed, A. Y., Deutsch, A. J., Dickens, L. T., DiMeglio, L. A., Dudenhöffer-Pfeifer, M., Evans-Molina, C., Fernández-Balsells, M. M., Fitipaldi, H., Fitzpatrick, S. L., Gitelman, S. E., Goodarzi, M. O., Grieger, J. A., Guasch-Ferré, M., Habibi, N., Hansen, T., Huang, C., Harris-Kawano, A., Ismail, H. M., Hoag, B., Johnson, R. K., Jones, A. G., Koivula, R. W., Leong, A., Leung, G. K., Libman, I. M., Liu, K., Long, S. A., Lowe, W. L., Morton, R. W., Motala, A. A., Onengut-Gumuscu, S., Pankow, J. S., Pathirana, M., Pazmino, S., Perez, D., Petrie, J. R., Powe, C. E., Quinteros, A., Jain, R., Ray, D., Ried-Larsen, M., Saeed, Z., Santhakumar, V., Kanbour, S., Sarkar, S., Monaco, G. S., Scholtens, D. M., Selvin, E., Sheu, W. H., Speake, C., Stanislawski, M. A., Steenackers, N., Steck, A. K., Stefan, N., Støy, J., Taylor, R., Tye, S. C., Ukke, G. G., Urazbayeva, M., Van der Schueren, B., Vatier, C., Wentworth, J. M., Hannah, W., White, S. L., Yu, G., Zhang, Y., Zhou, S. J., Beltrand, J., Polak, M., Aukrust, I., de Franco, E., Flanagan, S. E., Maloney, K. A., McGovern, A., Molnes, J., Nakabuye, M., Njølstad, P. R., Pomares-Millan, H., Provenzano, M., Saint-Martin, C., Zhang, C., Zhu, Y., Auh, S., de Souza, R., Fawcett, A. J., Gruber, C., Mekonnen, E. G., Mixter, E., Sherifali, D., Eckel, R. H., Nolan, J. J., Philipson, L. H., Brown, R. J., Billings, L. K., Boyle, K., Costacou, T., Dennis, J. M., Florez, J. C., Gloyn, A. L., Gomez, M. F., Gottlieb, P. A., Greeley, S. A., Griffin, K., Hattersley, A. T., Hirsch, I. B., Hivert, M. F., Hood, K. K., Josefson, J. L., Kwak, S. H., Laffel, L. M., Lim, S. S., Loos, R. J., Ma, R. C., Mathieu, C., Mathioudakis, N., Meigs, J. B., Misra, S., Mohan, V., Murphy, R., Oram, R., Owen, K. R., Ozanne, S. E., Pearson, E. R., Perng, W., Pollin, T. I., Pop-Busui, R., Pratley, R. E., Redman, L. M., Redondo, M. J., Reynolds, R. M., Semple, R. K., Sherr, J. L., Sims, E. K., Sweeting, A., Tuomi, T., Udler, M. S., Vesco, K. K., Vilsbøll, T., Wagner, R., Rich, S. S., Franks, P. W. 2023

    Abstract

    Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.

    View details for DOI 10.1038/s41591-023-02502-5

    View details for PubMedID 37794253

    View details for PubMedCentralID 8563635

  • The use of precision diagnostics for monogenic diabetes: a systematic review and expert opinion. Communications medicine Murphy, R., Colclough, K., Pollin, T. I., Ikle, J. M., Svalastoga, P., Maloney, K. A., Saint-Martin, C., Molnes, J., Misra, S., Aukrust, I., de Franco, E., Flanagan, S. E., Njølstad, P. R., Billings, L. K., Owen, K. R., Gloyn, A. L. 2023; 3 (1): 136

    Abstract

    Monogenic diabetes presents opportunities for precision medicine but is underdiagnosed. This review systematically assessed the evidence for (1) clinical criteria and (2) methods for genetic testing for monogenic diabetes, summarized resources for (3) considering a gene or (4) variant as causal for monogenic diabetes, provided expert recommendations for (5) reporting of results; and reviewed (6) next steps after monogenic diabetes diagnosis and (7) challenges in precision medicine field.Pubmed and Embase databases were searched (1990-2022) using inclusion/exclusion criteria for studies that sequenced one or more monogenic diabetes genes in at least 100 probands (Question 1), evaluated a non-obsolete genetic testing method to diagnose monogenic diabetes (Question 2). The risk of bias was assessed using the revised QUADAS-2 tool. Existing guidelines were summarized for questions 3-5, and review of studies for questions 6-7, supplemented by expert recommendations. Results were summarized in tables and informed recommendations for clinical practice.There are 100, 32, 36, and 14 studies included for questions 1, 2, 6, and 7 respectively. On this basis, four recommendations for who to test and five on how to test for monogenic diabetes are provided. Existing guidelines for variant curation and gene-disease validity curation are summarized. Reporting by gene names is recommended as an alternative to the term MODY. Key steps after making a genetic diagnosis and major gaps in our current knowledge are highlighted.We provide a synthesis of current evidence and expert opinion on how to use precision diagnostics to identify individuals with monogenic diabetes.

    View details for DOI 10.1038/s43856-023-00369-8

    View details for PubMedID 37794142

    View details for PubMedCentralID 6058077

  • PAX4 loss of function increases diabetes risk by altering human pancreatic endocrine cell development. Nature communications Lau, H. H., Krentz, N. A., Abaitua, F., Perez-Alcantara, M., Chan, J. W., Ajeian, J., Ghosh, S., Lee, Y., Yang, J., Thaman, S., Champon, B., Sun, H., Jha, A., Hoon, S., Tan, N. S., Gardner, D. S., Kao, S. L., Tai, E. S., Gloyn, A. L., Teo, A. K. 2023; 14 (1): 6119

    Abstract

    The coding variant (p.Arg192His) in the transcription factor PAX4 is associated with an altered risk for type 2 diabetes (T2D) in East Asian populations. In mice, Pax4 is essential for beta cell formation but its role on human beta cell development and/or function is unknown. Participants carrying the PAX4 p.His192 allele exhibited decreased pancreatic beta cell function compared to homozygotes for the p.192Arg allele in a cross-sectional study in which we carried out an intravenous glucose tolerance test and an oral glucose tolerance test. In a pedigree of a patient with young onset diabetes, several members carry a newly identified p.Tyr186X allele. In the human beta cell model, EndoC-βH1, PAX4 knockdown led to impaired insulin secretion, reduced total insulin content, and altered hormone gene expression. Deletion of PAX4 in human induced pluripotent stem cell (hiPSC)-derived islet-like cells resulted in derepression of alpha cell gene expression. In vitro differentiation of hiPSCs carrying PAX4 p.His192 and p.X186 risk alleles exhibited increased polyhormonal endocrine cell formation and reduced insulin content that can be reversed with gene correction. Together, we demonstrate the role of PAX4 in human endocrine cell development, beta cell function, and its contribution to T2D-risk.

    View details for DOI 10.1038/s41467-023-41860-z

    View details for PubMedID 37777536

    View details for PubMedCentralID 5034897

Mission Statement

Our mission is to improve understanding of pancreatic islet cell dysfunction in type 2 diabetes using human genetics as a tool to uncover causal disease mechanisms and shed light on potential targets for therapeutic development.

Lab Moto

Think Big, Ask Questions, Search for the Truth, Support each other & Be Kind

#diversityinscience matters

Resources

To request access to our Human Iset Data Deposited in EGA follow the links listed in the Datasets section.