Imperial College London

Dr Shivani Misra

Faculty of MedicineDepartment of Metabolism, Digestion and Reproduction

Clinical Senior Lecturer in Diabetes and Endocrinology
 
 
 
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s.misra

 
 
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Commonwealth BuildingHammersmith Campus

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Summary

 

Publications

Publication Type
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113 results found

Cherkaoui I, Du Q, Elgi D, Misra S, Rutter Get al., 2024, Optimized protocol for generating functional pancreatic insulin-secreting cells from human pluripotent stem cells, Journal of Visualized Experiments, Vol: 204, ISSN: 1940-087X

Human pluripotent stem cells (hPSCs) can differentiate into any kind of cell, making them an excellent alternative source of human pancreatic β-cells. hPSCs can either be embryonic stem cells (hESCs) derived from the blastocyst or induced pluripotent cells (hiPSCs) generated directly from somatic cells using a reprogramming process. Here a video-based protocol is presented to outline the optimal culture and passage conditions for hPSCs, prior to their differentiation and subsequent generation of insulin-producing pancreatic cells. This methodology follows the six-stage process for β-cell directed differentiation, wherein hPSCs differentiate into definitive endoderm (DE), primitive gut tube, posterior foregut fate, pancreatic progenitors, pancreatic endocrine progenitors, and ultimately pancreatic β-cells. It is noteworthy that this differentiation methodology takes a period of 27 days to generate human pancreatic β-cells. The potential of insulin secretion was evaluated through three experiments, which included immunostaining and glucose-stimulated insulin secretion.

Journal article

Khunti K, Chudasama YV, Gregg EW, Kamkuemah M, Misra S, Suls J, Venkateshmurthy NS, Valabhji Jet al., 2023, Diabetes and Multiple Long-term Conditions: A Review of Our Current Global Health Challenge., Diabetes Care, Vol: 46, Pages: 2092-2101

Use of effective treatments and management programs is leading to longer survival of people with diabetes. This, in combination with obesity, is thus contributing to a rise in people living with more than one condition, known as multiple long-term conditions (MLTC or multimorbidity). MLTC is defined as the presence of two or more long-term conditions, with possible combinations of physical, infectious, or mental health conditions, where no one condition is considered as the index. These include a range of conditions such as cardiovascular diseases, cancer, chronic kidney disease, arthritis, depression, dementia, and severe mental health illnesses. MLTC has major implications for the individual such as poor quality of life, worse health outcomes, fragmented care, polypharmacy, poor treatment adherence, mortality, and a significant impact on health care services. MLTC is a challenge, where interventions for prevention and management are lacking a robust evidence base. The key research directions for diabetes and MLTC from a global perspective include system delivery and care coordination, lifestyle interventions and therapeutic interventions.

Journal article

Misra S, Aguilar-Salinas CA, Chikowore T, Konradsen F, Ma RCW, Mbau L, Mohan V, Morton RW, Nyirenda MJ, Tapela N, Franks PWet al., 2023, The case for precision medicine in the prevention, diagnosis, and treatment of cardiometabolic diseases in low-income and middle-income countries., Lancet Diabetes Endocrinol, Vol: 11, Pages: 836-847

Cardiometabolic diseases are the leading preventable causes of death in most geographies. The causes, clinical presentations, and pathogenesis of cardiometabolic diseases vary greatly worldwide, as do the resources and strategies needed to prevent and treat them. Therefore, there is no single solution and health care should be optimised, if not to the individual (ie, personalised health care), then at least to population subgroups (ie, precision medicine). This optimisation should involve tailoring health care to individual disease characteristics according to ethnicity, biology, behaviour, environment, and subjective person-level characteristics. The capacity and availability of local resources and infrastructures should also be considered. Evidence needed for equitable precision medicine cannot be generated without adequate data from all target populations, and the idea that research done in high-income countries will transfer adequately to low-income and middle-income countries (LMICs) is problematic, as many migration studies and transethnic comparisons have shown. However, most data for precision medicine research are derived from people of European ancestry living in high-income countries. In this Series paper, we discuss the case for precision medicine for cardiometabolic diseases in LMICs, the barriers and enablers, and key considerations for implementation. We focus on three propositions: first, failure to explore and implement precision medicine for cardiometabolic disease in LMICs will enhance global health disparities. Second, some LMICs might already be placed to implement cardiometabolic precision medicine under appropriate circumstances, owing to progress made in treating infectious diseases. Third, improvements in population health from precision medicine are most probably asymptotic; the greatest gains are more likely to be obtained in countries where health-care systems are less developed. We outline key recommendations for implementation of precis

Journal article

Murphy R, Colclough K, Pollin TI, Ikle JM, Svalastoga P, Maloney KA, Saint-Martin C, Molnes J, ADAEASD PMDI, Misra S, Aukrust I, de Franco E, Flanagan SE, Njølstad PR, Billings LK, Owen KR, Gloyn ALet al., 2023, The use of precision diagnostics for monogenic diabetes: a systematic review and expert opinion., Commun Med (Lond), Vol: 3

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: We provide a synthesis of current evidence and expert opinion on how to use precision diagnostics to identify individuals with monogenic diabetes.

Journal article

Misra S, Wagner R, Ozkan B, Schön M, Sevilla-Gonzalez M, Prystupa K, Wang CC, Kreienkamp RJ, Cromer SJ, Rooney MR, Duan D, Thuesen ACB, Wallace AS, Leong A, Deutsch AJ, Andersen MK, Billings LK, Eckel RH, Sheu WH-H, Hansen T, Stefan N, Goodarzi MO, Ray D, Selvin E, Florez JC, ADAEASD PMDI, Meigs JB, Udler MSet al., 2023, Precision subclassification of type 2 diabetes: a systematic review., Commun Med (Lond), Vol: 3

BACKGROUND: Heterogeneity in type 2 diabetes presentation and progression suggests that precision medicine interventions could improve clinical outcomes. We undertook a systematic review to determine whether strategies to subclassify type 2 diabetes were associated with high quality evidence, reproducible results and improved outcomes for patients. METHODS: We searched PubMed and Embase for publications that used 'simple subclassification' approaches using simple categorisation of clinical characteristics, or 'complex subclassification' approaches which used machine learning or 'omics approaches in people with established type 2 diabetes. We excluded other diabetes subtypes and those predicting incident type 2 diabetes. We assessed quality, reproducibility and clinical relevance of extracted full-text articles and qualitatively synthesised a summary of subclassification approaches. RESULTS: Here we show data from 51 studies that demonstrate many simple stratification approaches, but none have been replicated and many are not associated with meaningful clinical outcomes. Complex stratification was reviewed in 62 studies and produced reproducible subtypes of type 2 diabetes that are associated with outcomes. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into clinically meaningful subtypes. CONCLUSION: Critical next steps toward clinical implementation are to test whether subtypes exist in more diverse ancestries and whether tailoring interventions to subtypes will improve outcomes.

Journal article

Tobias DK, Merino J, Ahmad A, Aiken C, Benham JL, Bodhini D, Clark AL, Colclough K, Corcoy R, Cromer SJ, Duan D, Felton JL, Francis EC, Gillard P, Gingras V, Gaillard R, Haider E, Hughes A, Ikle JM, Jacobsen LM, Kahkoska AR, Kettunen JLT, Kreienkamp RJ, Lim L-L, Männistö JME, Massey R, Mclennan N-M, Miller RG, Morieri ML, Most J, Naylor RN, Ozkan B, Patel KA, Pilla SJ, Prystupa K, Raghavan S, Rooney MR, Schön M, Semnani-Azad Z, Sevilla-Gonzalez M, Svalastoga P, Takele WW, Tam CH-T, Thuesen ACB, Tosur M, Wallace AS, Wang CC, Wong JJ, Yamamoto JM, Young K, Amouyal C, Andersen MK, Bonham MP, Chen M, Cheng F, Chikowore T, Chivers SC, Clemmensen C, Dabelea D, Dawed AY, Deutsch AJ, Dickens LT, DiMeglio LA, Dudenhöffer-Pfeifer M, Evans-Molina C, Fernández-Balsells MM, Fitipaldi H, Fitzpatrick SL, Gitelman SE, Goodarzi MO, Grieger JA, Guasch-Ferré M, Habibi N, Hansen T, Huang C, Harris-Kawano A, Ismail HM, Hoag B, Johnson RK, Jones AG, Koivula RW, Leong A, Leung GKW, Libman IM, Liu K, Long SA, Lowe WL, Morton RW, Motala AA, Onengut-Gumuscu S, Pankow JS, Pathirana M, Pazmino S, Perez D, Petrie JR, Powe CE, Quinteros A, Jain R, Ray D, Ried-Larsen M, Saeed Z, Santhakumar V, Kanbour S, Sarkar S, Monaco GSF, Scholtens DM, Selvin E, Sheu WH-H, Speake C, Stanislawski MA, Steenackers N, Steck AK, Stefan N, Støy J, Taylor R, Tye SC, Ukke GG, Urazbayeva M, Van der Schueren B, Vatier C, Wentworth JM, Hannah W, White SL, Yu G, Zhang Y, Zhou SJ, Beltrand J, Polak M, Aukrust I, de Franco E, Flanagan SE, Maloney KA, McGovern A, Molnes J, Nakabuye M, Njølstad PR, Pomares-Millan H, Provenzano M, Saint-Martin C, Zhang C, Zhu Y, Auh S, de Souza R, Fawcett AJ, Gruber C, Mekonnen EG, Mixter E, Sherifali D, Eckel RH, Nolan JJ, Philipson LH, Brown RJ, Billings LK, Boyle K, Costacou T, Dennis JM, Florez JC, Gloyn AL, Gomez MF, Gottlieb PA, Greeley SAW, Griffin K, Hattersley AT, Hirsch IB, Hivert M-F, Hood KK, Josefson JL, Kwak SH, Laffel LM, Lim SS, Loos RJF, Ma RCW, Mathieu C, Mathioudakis N, Meiet al., 2023, Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine., Nat Med, Vol: 29, Pages: 2438-2457

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.

Journal article

Misra S, Ke C, Srinivasan S, Goyal A, Nyriyenda MJ, Florez JC, Khunti K, Magliano DJ, Luk Aet al., 2023, Current insights and emerging trends in early-onset type 2 diabetes., Lancet Diabetes Endocrinol, Vol: 11, Pages: 768-782

Type 2 diabetes diagnosed in childhood or early adulthood is termed early-onset type 2 diabetes. Cases of early-onset type 2 diabetes are increasing rapidly globally, alongside rising obesity. Compared with a diagnosis later in life, an earlier-onset diagnosis carries an unexplained excess risk of microvascular complications, adverse cardiovascular outcomes, and earlier death. Women with early-onset type 2 diabetes also have a higher risk of adverse pregnancy outcomes. The high burden of complications renders individuals with early-onset type 2 diabetes at future risk of multimorbidity and interventions to reverse these concerning trends should be a priority. Within the early-onset cohort, disease pathophysiology and interventions have been better studied in paediatric-onset (<19 years) type 2 diabetes compared to adults; however, young adults aged 19-39 years (a larger number proportionally) are not well characterised and are also invisible in the current evidence base supporting management, which is derived from trials in later-onset type 2 diabetes. Young adults with type 2 diabetes face challenges in self-management that older individuals are less likely to experience (being in education or of working age, higher diabetes distress, and possible obesity-related stigma and diabetes-related stigma). There is a major research gap as to the optimal strategies to deploy in managing type 2 diabetes in adolescents and young adults, given that current models of care appear to not work as well in this age group. In the face of manifold risk factors (obesity, female sex, social deprivation, non-White European ethnicity, and genetic risk factors) prevention strategies with tailored lifestyle interventions, where needed, are likely to have greater success, but more evidence is needed. In this Review, we draw on evidence from both adolescents and young adults to provide a contemporary update on the current insights and emerging trends in early-onset type 2 diabetes.

Journal article

Hirani D, Salem V, Khunti K, Misra Set al., 2023, Newly detected diabetes during the COVID-19 pandemic: What have we learnt?, BEST PRACTICE & RESEARCH CLINICAL ENDOCRINOLOGY & METABOLISM, Vol: 37, ISSN: 1521-690X

Journal article

Conrad N, Misra S, Verbakel JY, Verbeke G, Molenberghs G, Taylor PN, Mason J, Sattar N, McMurray JJV, McInnes IB, Khunti K, Cambridge Get al., 2023, Incidence, prevalence, and co-occurrence of autoimmune disorders over time and by age, sex, and socioeconomic status: a population-based cohort study of 22 million individuals in the UK., Lancet, Vol: 401, Pages: 1878-1890

BACKGROUND: A rise in the incidence of some autoimmune disorders has been described. However, contemporary estimates of the overall incidence of autoimmune diseases and trends over time are scarce and inconsistent. We aimed to investigate the incidence and prevalence of 19 of the most common autoimmune diseases in the UK, assess trends over time, and by sex, age, socioeconomic status, season, and region, and we examine rates of co-occurrence among autoimmune diseases. METHODS: In this UK population-based study, we used linked primary and secondary electronic health records from the Clinical Practice Research Datalink (CPRD), a cohort that is representative of the UK population in terms of age and sex and ethnicity. Eligible participants were men and women (no age restriction) with acceptable records, approved for Hospital Episodes Statistics and Office of National Statistics linkage, and registered with their general practice for at least 12 months during the study period. We calculated age and sex standardised incidence and prevalence of 19 autoimmune disorders from 2000 to 2019 and used negative binomial regression models to investigate temporal trends and variation by age, sex, socioeconomic status, season of onset, and geographical region in England. To characterise co-occurrence of autoimmune diseases, we calculated incidence rate ratios (IRRs), comparing incidence rates of comorbid autoimmune disease among individuals with a first (index) autoimmune disease with incidence rates in the general population, using negative binomial regression models, adjusted for age and sex. FINDINGS: Among the 22 009 375 individuals included in the study, 978 872 had a new diagnosis of at least one autoimmune disease between Jan 1, 2000, and June 30, 2019 (mean age 54·0 years [SD 21·4]). 625 879 (63·9%) of these diagnosed individuals were female and 352 993 (36·1%) were male. Over the study period, age and sex standa

Journal article

Cherkaoui I, Du Q, Dion C, Leitch H, Chabosseau PL, Egli DM, Sachedina D, Wastin J, Misra S, Rutter GAet al., 2023, Differential Impacts of Two Novel HNF1A Variants Associated with Familial Young-Onset Diabetes on Protein Function and Insulin Secretion In Vitro, 83rd Annual Scientific Sessions of the American-Diabetes-Association (ADA), Publisher: AMER DIABETES ASSOC, ISSN: 0012-1797

Conference paper

Avari P, Lumb A, Flanagan D, Rayman G, Misra S, Choudhary P, Dhatariya Ket al., 2023, Insulin Pumps and Hybrid Close Loop Systems Within Hospital: A Scoping Review and Practical Guidance From the Joint British Diabetes Societies for Inpatient Care., J Diabetes Sci Technol, Vol: 17, Pages: 625-634

This article is the second of a two-part series providing a scoping review and summary of the Joint British Diabetes Societies for Inpatient Care (JBDS-IP) guidelines on the use of diabetes technology in people with diabetes admitted to hospital. The first part reviewed the use of continuous glucose monitoring (CGM) in hospital. In this article, we focus on the use of continuous subcutaneous insulin infusion (CSII; insulin pumps) and hybrid closed-loop systems in hospital. JBDS-IP advocates enabling people who can self-manage and are willing and capable of using CSII to continue doing so as they would do out of hospital. CSII should be discontinued if the individual is critically ill or hemodynamically unstable. For individuals on hybrid closed-loop systems, the system should be discontinued from auto-mode, and may be used individually (as CGM only or CSII only, if criteria are met). Continuing in closed-loop mode may only be done so under specialist guidance from the Diabetes Team, where the diabetes teams are comfortable and knowledgeable about the specific devices used. Health care organizations need to have clear local policies and guidance to support individuals using these wearable technologies, and ensure the relevant workforce is capable and skilled enough to ensure their safe use within the hospital setting.

Journal article

Avari P, Lumb A, Flanagan D, Rayman G, Misra S, Dhatariya K, Choudhary Pet al., 2023, Continuous Glucose Monitoring Within Hospital: A Scoping Review and Summary of Guidelines From the Joint British Diabetes Societies for Inpatient Care., J Diabetes Sci Technol, Vol: 17, Pages: 611-624

Increasing numbers of people, particularly with type 1 diabetes (T1D), are using wearable technologies. That is, continuous subcutaneous insulin infusion (CSII) pumps, continuous glucose monitoring (CGM) systems, and hybrid closed-loop systems, which combine both these elements. Given over a quarter of all people admitted to hospital have diabetes, there is a need for clinical guidelines for when people using them are admitted to hospital. The Joint British Diabetes Societies for Inpatient Care (JBDS-IP) provide a scoping review and summary of guidelines on the use of diabetes technology in people with diabetes admitted to hospital.JBDS-IP advocates enabling people who can self-manage and use their own diabetes technology to continue doing so as they would do out of hospital. Whilst people with diabetes are recommended to achieve a target of 70% time within range (3.9-10.0 mmol/L [70-180 mg/dL]), this can be very difficult to achieve whilst unwell. We therefore recommend targeting hypoglycemia prevention as a priority, keeping time below 3.9 mmol/L (70 mg/dL) at < 1%, being aware of looming hypoglycemia if glucose is between 4.0 and 5.9 mmol/L (72-106 mg/dL), and consider intervening, particularly if there is a downward CGM trend arrow.Health care organizations need clear local policies and guidance to support individuals using diabetes technologies, and ensure the relevant workforce is capable and skilled enough to ensure their safe use within the hospital setting. The current set of guidelines is divided into two parts. Part 1, which follows below, outlines the guidance for use of CGM in hospital. The second part outlines guidance for use of CSII and hybrid closed-loop in hospital.

Journal article

Misra S, Wagner R, Ozkan B, Schön M, Sevilla-Gonzalez M, Prystupa K, Wang CC, Kreienkamp RJ, Cromer SJ, Rooney MR, Duan D, Thuesen ACB, Wallace AS, Leong A, Deutsch AJ, Andersen MK, Billings LK, Eckel RH, Sheu WH-H, Hansen T, Stefan N, Goodarzi MO, Ray D, Selvin E, Florez JC, ADAEASD PMDI, Meigs JB, Udler MSet al., 2023, Systematic review of precision subclassification of type 2 diabetes., medRxiv

Heterogeneity in type 2 diabetes presentation, progression and treatment has the potential for precision medicine interventions that can enhance care and outcomes for affected individuals. We undertook a systematic review to ascertain whether strategies to subclassify type 2 diabetes are associated with improved clinical outcomes, show reproducibility and have high quality evidence. We reviewed publications that deployed 'simple subclassification' using clinical features, biomarkers, imaging or other routinely available parameters or 'complex subclassification' approaches that used machine learning and/or genomic data. We found that simple stratification approaches, for example, stratification based on age, body mass index or lipid profiles, had been widely used, but no strategy had been replicated and many lacked association with meaningful outcomes. Complex stratification using clustering of simple clinical data with and without genetic data did show reproducible subtypes of diabetes that had been associated with outcomes such as cardiovascular disease and/or mortality. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into meaningful groups. More studies are needed to test these subclassifications in more diverse ancestries and prove that they are amenable to interventions.

Journal article

Murphy R, Colclough K, Pollin TI, Ikle JM, Svalastoga P, Maloney KA, Saint-Martin C, Molnes J, ADAEASD Precision Medicine Diabetes Initiative, Misra S, Aukrust I, de Franco A, Flanagan SE, Njølstad PR, Billings LK, Owen KR, Gloyn ALet al., 2023, A Systematic Review of the use of Precision Diagnostics in Monogenic Diabetes., medRxiv

Monogenic forms of diabetes present opportunities for precision medicine as identification of the underlying genetic cause has implications for treatment and prognosis. However, genetic testing remains inconsistent across countries and health providers, often resulting in both missed diagnosis and misclassification of diabetes type. One of the barriers to deploying genetic testing is uncertainty over whom to test as the clinical features for monogenic diabetes overlap with those for both type 1 and type 2 diabetes. In this review, we perform a systematic evaluation of the evidence for the clinical and biochemical criteria used to guide selection of individuals with diabetes for genetic testing and review the evidence for the optimal methods for variant detection in genes involved in monogenic diabetes. In parallel we revisit the current clinical guidelines for genetic testing for monogenic diabetes and provide expert opinion on the interpretation and reporting of genetic tests. We provide a series of recommendations for the field informed by our systematic review, synthesizing evidence, and expert opinion. Finally, we identify major challenges for the field and highlight areas for future research and investment to support wider implementation of precision diagnostics for monogenic diabetes.

Journal article

Cherkaoui I, Du Q, Egli DM, Sachedina D, Dion C, Leitch HG, Chabosseau P, Wastin J, Misra S, Rutter GAet al., 2023, Impact on insulin secretion and CA<SUP>2+</SUP> dynamics of the homozygous P.A251T HNF1A variant in beta-like cells differentiated from patient-derived induced pluripotent cells, Publisher: WILEY, ISSN: 0742-3071

Conference paper

Chan J, Blane D, Choudhary P, Chowdhury TA, Goyal A, Hanif W, Jacca J, Mathur R, Misra S, Ocran N, Rutter MK, Studley R, Treweek S, Valabhji J, Khunti Ket al., 2023, Addressing health inequalities in diabetes through research: Recommendations from Diabetes UK's 2022 health inequalities in diabetes workshop, DIABETIC MEDICINE, Vol: 40, ISSN: 0742-3071

Journal article

Kaur A, Walkey HC, Wylie TAF, Godsland IF, Misra S, Gillespie K, Thomas NJ, Patel KA, Johnston DG, Oliver NSet al., 2023, Type 1 diabetes genetic risk scores do not impact partial remission status in autoantibody positive individuals within the first year of diagnosis: Data from ADDRESS-2, Publisher: WILEY, ISSN: 0742-3071

Conference paper

Lumb A, Misra S, Rayman G, Avari P, Flanagan D, Choudhary P, Dhatariya Ket al., 2023, Variation in the Current Use of Technology to Support Diabetes Management in UK Hospitals: Results of a Survey of Health Care Professionals, JOURNAL OF DIABETES SCIENCE AND TECHNOLOGY, ISSN: 1932-2968

Journal article

Misra S, Avari P, Lumb A, Flanagan D, Choudhary P, Rayman G, Dhatariya Ket al., 2023, How Can Point-of-Care Technologies Support In-Hospital Diabetes Care?, JOURNAL OF DIABETES SCIENCE AND TECHNOLOGY, Vol: 17, Pages: 509-516, ISSN: 1932-2968

Journal article

Flanagan D, Avari P, Choudhary P, Lumb A, Misra S, Rayman G, Dhatariya Ket al., 2023, Using Technology to Improve Diabetes Care in Hospital: The Challenge and the Opportunity, JOURNAL OF DIABETES SCIENCE AND TECHNOLOGY, Vol: 17, Pages: 503-508, ISSN: 1932-2968

Journal article

Khunti K, Valabhji J, Misra S, 2023, Diabetes and the COVID-19 pandemic, DIABETOLOGIA, Vol: 66, Pages: 255-266, ISSN: 0012-186X

Journal article

Misra S, Holman N, Barron E, Knighton P, Warner J, Kar P, Young B, Valabhji Jet al., 2023, Characteristics and care of young people with type 2 diabetes included in the national diabetes audit datasets for England, DIABETIC MEDICINE, Vol: 40, ISSN: 0742-3071

Journal article

Misra S, DiMeglio LA, 2022, COVID-19 and Incident Type 1 Diabetes: Deciphering the Associations, DIABETES, Vol: 71, Pages: 2480-2482, ISSN: 0012-1797

Journal article

Thomas NJ, Walkey HC, Kaur A, Misra S, Oliver NS, Colclough K, Weedon MN, Johnston DG, Hattersley AT, Patel KAet al., 2022, The relationship between islet autoantibody status and the genetic risk of type 1 diabetes in adult-onset type 1 diabetes, Diabetologia, Vol: 66, Pages: 310-320, ISSN: 0012-186X

Aims/hypothesisThe reason for the observed lower rate of islet autoantibody positivity in clinician-diagnosed adult-onset vs childhood-onset type 1 diabetes is not known. We aimed to explore this by assessing the genetic risk of type 1 diabetes in autoantibody-negative and -positive children and adults.MethodsWe analysed GAD autoantibodies, insulinoma-2 antigen autoantibodies and zinc transporter-8 autoantibodies (ZnT8A) and measured type 1 diabetes genetic risk by genotyping 30 type 1 diabetes-associated variants at diagnosis in 1814 individuals with clinician-diagnosed type 1 diabetes (1112 adult-onset, 702 childhood-onset). We compared the overall type 1 diabetes genetic risk score (T1DGRS) and non-HLA and HLA (DR3-DQ2, DR4-DQ8 and DR15-DQ6) components with autoantibody status in those with adult-onset and childhood-onset diabetes. We also measured the T1DGRS in 1924 individuals with type 2 diabetes from the Wellcome Trust Case Control Consortium to represent non-autoimmune diabetes control participants.ResultsThe T1DGRS was similar in autoantibody-negative and autoantibody-positive clinician-diagnosed childhood-onset type 1 diabetes (mean [SD] 0.274 [0.034] vs 0.277 [0.026], p=0.4). In contrast, the T1DGRS in autoantibody-negative adult-onset type 1 diabetes was lower than that in autoantibody-positive adult-onset type 1 diabetes (mean [SD] 0.243 [0.036] vs 0.271 [0.026], p<0.0001) but higher than that in type 2 diabetes (mean [SD] 0.229 [0.034], p<0.0001). Autoantibody-negative adults were more likely to have the more protective HLA DR15-DQ6 genotype (15% vs 3%, p<0.0001), were less likely to have the high-risk HLA DR3-DQ2/DR4-DQ8 genotype (6% vs 19%, p<0.0001) and had a lower non-HLA T1DGRS (p<0.0001) than autoantibody-positive adults. In contrast to children, autoantibody-negative adults were more likely to be male (75% vs 59%), had a higher BMI (27 vs 24 kg/m2) and were less likely to have other autoimmune conditions (2% vs 10%) than autoantib

Journal article

Misra S, 2022, Rise in diabetic ketoacidosis during the COVID-19 pandemic: several questions remain., Lancet Diabetes Endocrinol, Vol: 10, Pages: 763-765

Journal article

Misra S, Gable D, Khunti K, Barron E, Young B, Kar P, Valabhji Jet al., 2022, Developing services to support the delivery of care to people with early-onset type 2 diabetes, DIABETIC MEDICINE, Vol: 39, ISSN: 0742-3071

Journal article

Grace SL, Bowden J, Walkey HC, Kaur A, Misra S, Shields BM, McKinley TJ, Oliver NS, McDonald T, Johnston DG, Jones AG, Patel KAet al., 2022, Islet autoantibody level distribution in Type 1 diabetes and their association with genetic and clinical characteristics, Journal of Clinical Endocrinology and Metabolism, Vol: 107, Pages: E4341-E4349, ISSN: 0021-972X

ContextThe importance of the autoantibody level at diagnosis of type 1 diabetes (T1D) is not clear.ObjectiveWe aimed to assess the association of glutamate decarboxylase (GADA), islet antigen-2 (IA-2A), and zinc transporter 8 (ZnT8A) autoantibody levels with clinical and genetic characteristics at diagnosis of T1D.MethodsWe conducted a prospective, cross-sectional study. GADA, IA-2A, and ZnT8A were measured in 1644 individuals with T1D at diagnosis using radiobinding assays. Associations between autoantibody levels and the clinical and genetic characteristics for individuals were assessed in those positive for these autoantibodies. We performed replication in an independent cohort of 449 people with T1D.ResultsGADA and IA-2A levels exhibited a bimodal distribution at diagnosis. High GADA level was associated with older age at diagnosis (median 27 years vs 19 years, P = 9 × 10−17), female sex (52% vs 37%, P = 1 × 10−8), other autoimmune diseases (13% vs 6%, P = 3 × 10−6), and HLA-DR3-DQ2 (58% vs 51%, P = .006). High IA-2A level was associated with younger age of diagnosis (median 17 years vs 23 years, P = 3 × 10−7), HLA-DR4-DQ8 (66% vs 50%, P = 1 × 10−6), and ZnT8A positivity (77% vs 52%, P = 1 × 10−15). We replicated our findings in an independent cohort of 449 people with T1D where autoantibodies were measured using enzyme-linked immunosorbent assays.ConclusionIslet autoantibody levels provide additional information over positivity in T1D at diagnosis. Bimodality of GADA and IA-2A autoantibody levels highlights the novel aspect of heterogeneity of T1D. This may have implications for T1D prediction, treatment, and pathogenesis.

Journal article

Misra S, Florez JC, 2022, Extending precision medicine tools to populations at high risk of type 2 diabetes, PLOS MEDICINE, Vol: 19, ISSN: 1549-1277

Journal article

Eng PC, Distaso W, Durreshahwar H, Shaikhali Y, Narendranathan D, Cassin-Scott R, Misra S, Hill NE, Tharakan G, Oliver NS, Tan TM, Izzi-Engbeaya C, Salem Vet al., 2022, The benefit of dexamethasone in patients with COVID-19 infection is preserved in patients with diabetes., Diabetes, Obesity and Metabolism: a journal of pharmacology and therapeutics, Vol: 24, Pages: 1385-1389, ISSN: 1462-8902

Dexamethasone significantly reduces mortality1 and is now standard treatment for patients with COVID-19 who require supplemental oxygen and/or mechanical ventilation. However, supraphysiological doses of glucocorticoids may exacerbate dysglycaemia and precipitate hyperglycaemic complications, particularly in those with or at risk of Type 2 diabetes2. The RECOVERY trial1 reported a low incidence of hyperglycaemic complications (2/1996, 0.1%), although the real-world incidence is likely to be much higher3. Type 2 diabetes itself increases the risk of severe COVID-194, and hyperglycaemia independently predicts poor outcomes5. We investigated the possibility that patients with diabetes may derive less survival benefit from steroid therapy in the setting of severe COVID-19 infection

Journal article

Jones E, Avari P, Fallon C, Reddy M, Oliver N, Misra S, Gable D, Bravis Vet al., 2022, Dedicated type 1 diabetes technology educator improves clinical outcomes and equity of access to diabetes technologies, Publisher: WILEY, ISSN: 0742-3071

Conference paper

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