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Translational medicine for cardiometabolic disorders

Krentz, A. J. (2025) Translational medicine for cardiometabolic disorders. PhD thesis, University of Reading

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To link to this item DOI: 10.48683/1926.00123732

Abstract/Summary

Personalised precision medicine, including sex-specific considerations, is gaining momentum in the management of complex cardiometabolic disorders. This thesis explores aspects of disease pathophysiology and the development and clinical implementation of relevant pharmacotherapies in men and women. A series of clinical studies published in peer reviewed journals is presented. Each study tested a specific hypothesis relevant to this overarching aim. To investigate the life-long health implications of polycystic ovary syndrome a novel phenotype of the disorder was modelled in postmenopausal women. Dose-response associations were observed with (a) prevalent cardiovascular disease and (b) circulating adipocytokines – positive for leptin, negative for adiponectin – that mirrored the classic syndrome in younger women. A novel glucose-lowering drug – the glucokinase activator AZD1656 – with theoretical potential to impair recovery from hypoglycaemia was studied in a phase 1b clinical trial in adults with type 2 diabetes receiving metformin. Counter-regulatory hormone responses to experimental hypoglycaemia were quantified using precision automated stepped hypoglycaemic clamps. Exogenous glucagon was effective in reversing hypoglycaemia during AZD1656 therapy. New-onset diabetes is an adverse effect of statin therapy in which insulin resistance is implicated. In a phase 4 investigator-initiated study, non-classic effects of atorvastatin 40 mg daily were quantified in abdominally obese middle-aged adults. No effect was observed on whole-body insulin sensitivity as assessed using hyperinsulinaemic euglycaemic clamps. Microvascular function and adipocytokines were also unaffected by the high-intensity statin. Statins are the most commonly prescribed cholesterol-lowering drugs. However, their use in clinical practice is frequently suboptimal. In a proof-of-concept real-world study novel machine learning methodology, trained on national clinical guidelines, was able to identify individuals failing to reach cholesterol goals and recommend personalised therapeutic options. Collectively, the original papers illustrate steps along the translational medicine pathway. The studies also emphasise (a) metabolic-vascular disease intersections (b) the importance of detailed phenotyping and use of appropriate research methodologies and (c) novel strategies to promote personalised precision medicine. It is proposed that reversing the conventional translational pathway may usefully inform earlier stages of target identification and clinical drug development.

Item Type:Thesis (PhD)
Thesis Supervisor:Gibbins, J.
Thesis/Report Department:School Biological Sciences
Identification Number/DOI:10.48683/1926.00123732
Divisions:Life Sciences > School of Biological Sciences
ID Code:123732

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