GLP-1 Therapies Linked to Lower Fragility Fracture Risk in Adults Living With Type 2 Diabetes
Key Takeaways:
- Adults aged 50 and over living with type 2 diabetes who started a GLP-1 receptor agonist had a 21% lower three-year risk of fragility fracture than those starting a DPP-4 inhibitor (HR 0.79).
- Reductions were strongest for vertebral (HR 0.68) and hip or femur fractures (HR 0.70), and appeared independent of changes in BMI and HbA1c – pointing to a possible direct skeletal effect.
- The findings do not extend to younger people using GLP-1 medications for weight management alone, or to those with osteoporosis; among adults without diabetes, fracture risk was higher (HR 1.13).
A large-scale look at bone health during GLP-1 treatment
Initiating a GLP-1 receptor agonist for type 2 diabetes was associated with a lower risk of fragility fractures in adults aged 50 and over, including fractures of the hip and spine, according to a large target trial emulation study published in JAMA Network Open.
Over three years of follow-up, adults who newly started a GLP-1 medication had a 21% lower risk of fragility fracture than those who newly started a DPP-4 inhibitor (HR 0.79, 95% CI 0.76–0.83), reported Christopher Hamad, MD, of the University of California Los Angeles, and colleagues.
The authors were careful to frame the size of the effect in context rather than overstate it.
“Although the absolute risk reduction at 3 years was modest (0.79%), this magnitude is clinically relevant given a baseline 3-year major osteoporotic fracture risk of approximately 3% to 4% in comparable populations and the substantial morbidity and mortality associated with hip and vertebral fractures,” the authors wrote.
Why a modest absolute reduction still matters
The clinical weight of these numbers rests on how serious the events being prevented are. Hip fractures, for example, are associated with one-year mortality rates of up to 25% in women and up to 36% in men.
Given the potential for such severe outcomes, Hamad’s group emphasised that even modest absolute reductions in fragility fractures – which stem from low-energy trauma, such as a fall from standing height – can prevent a meaningful number of events at population level.
The findings build on several smaller observational studies in people living with diabetes that have similarly linked the use of GLP-1 medications such as semaglutide (Ozempic, Wegovy) to a reduced fracture risk. Hamad’s team noted that their analysis drew on the largest dataset assembled on this question to date.
Which fractures showed the strongest signal
The protective association was most pronounced at precisely the sites that carry the highest morbidity and mortality:
- Vertebral fractures: HR 0.68, 95% CI 0.63–0.73
- Hip or femur fractures: HR 0.70, 95% CI 0.63–0.79
- Rib fractures: HR 0.83, 95% CI 0.77–0.91
No significant associations were identified for fractures of the distal radius or ulna, or of the proximal humerus.
Weight loss, glycaemic control and the question of a direct skeletal effect
One of the more striking elements of the analysis concerns the mechanism. Mediation analyses indicated that the associations were independent of changes in BMI and HbA1c, a pattern consistent with a potential direct skeletal effect of GLP-1 medications.
That matters because weight loss itself is associated with reduced bone mineral density and a higher fracture risk – a relationship reflected in the study’s own data, which found that cumulative BMI loss was tied to a 2% increase in fracture risk. In other words, the expected consequence of the weight reduction these medications produce would be a rise in fracture risk, not a fall.
“Yet, GLP-1 RA [receptor agonist] use was associated with lower fracture risk despite these changes, suggesting that potential direct skeletal effects may outweigh the adverse consequences of weight loss,” the authors wrote.
Reassessing the assumption of neutral skeletal effects
Current American Diabetes Association Standards of Care classify GLP-1 medications as having neutral effects on the skeleton. The researchers argued that their results suggest this assumption warrants reevaluation.
They also acknowledged the limits of what an observational design can establish, noting that the findings could still reflect unmeasured factors such as improved balance or greater physical activity among people taking these medications. Making sense of evidence like this – and of the mechanistic arguments used to interpret it – is the focus of professional training such as the College of Contemporary Health’s GLP-1RAs in Focus, a CPD-accredited online short course that grounds healthcare professionals in how these medications act on the body.
How the study was conducted
For this comparative effectiveness study, the researchers drew data from the TriNetX Research Network, analysing 66,803 matched pairs, or 133,606 people in total, aged between 50 and 90 years.
Mean age was approximately 63 years, roughly 53% of participants were male, 58% were White, and average baseline BMI was around 33.
All participants were living with type 2 diabetes and had newly initiated either a GLP-1 receptor agonist or a DPP-4 inhibitor between 2015 and 2022. Dulaglutide (Trulicity), semaglutide and liraglutide (Victoza) together accounted for 91% of index prescriptions in the GLP-1 group. Exclusion criteria included fractures resulting from high-energy trauma, as well as osteoporosis and osteopenia.
Where the protective association held – and where it did not
In subgroup analyses, the lower fracture risk was consistent across age groups, across sexes and across levels of frailty.
A separate matched cohort, however, evaluated participants according to diabetes status and produced a notably different picture. Among adults living with type 2 diabetes, GLP-1 use retained a protective association (three-year HR 0.91, 95% CI 0.88–0.95). Among adults without diabetes, it was associated with an increased fracture risk (HR 1.13, 95% CI 1.04–1.23, P<0.001 for interaction).
Consequently, the authors emphasised that the findings cannot be generalised to younger people using GLP-1 medications solely for weight management, nor to those with known osteoporosis or a previous fragility fracture, who were excluded from the study altogether.
What this means for practice
Overall, “the findings do not argue against GLP-1 RA use on the basis of fracture risk, though bone health monitoring remains prudent,” according to the researchers.
They called for prospective randomised trials to evaluate the associations observed, including among people with osteopenia or early osteoporosis, alongside preclinical work to understand the potential mechanisms involved.
CCH insight
For healthcare professionals, this study is a useful reminder that the skeletal consequences of GLP-1 treatment are not yet settled science – and that the answer appears to differ depending on who is being treated and why. Interpreting findings of this kind with confidence depends on a firm grasp of how these medications act in the first place, from gut hormones and appetite regulation through to their wider effects beyond glycaemic control. That is exactly what CCH’s GLP-1RAs in Focus – Why Drugs Like Ozempic Work CPD short course (2 CPD hours, fully online, CPD-accredited) is built to provide, giving clinicians a clear grounding in the mechanisms behind these therapies and the ability to appraise emerging evidence critically, whether or not they prescribe.
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Ozempic and Mounjaro Linked to Modest Rise in Hair Loss Risk, BMJ Study Finds
Key Takeaways:
- Adults living with type 2 diabetes taking GLP-1 receptor agonists developed alopecia more often than those taking SGLT-2 inhibitors (37% higher risk) or DPP-4 inhibitors (68% higher risk), a BMJ study reports.
- Absolute risk stayed low, at 6.91 cases per 1,000 person years for GLP-1 receptor agonists against 5.04 for SGLT-2 inhibitors and 3.89 for DPP-4 inhibitors.
- The association was confined to non-scarring alopecia, where the follicle stays intact and regrowth remains possible.
A modest signal, but one worth discussing in the consultation
Medications from the GLP-1 receptor agonist class, now widely used in the management of type 2 diabetes and obesity, may be associated with a modest increase in hair loss. The finding comes from a study published by The BMJ on 22 July 2026.
The class includes semaglutide, marketed under brand names such as Ozempic and Wegovy, and tirzepatide, marketed as Mounjaro and Zepbound. Researchers found that adults living with type 2 diabetes who were treated with GLP-1 receptor agonists went on to develop alopecia more frequently than people prescribed two other commonly used classes of diabetes medication.
Although the relative increase was significant, the researchers emphasised that the absolute risk of hair loss remained low. Even so, awareness of the possible adverse effect could help people and their clinicians reach better informed treatment decisions together.
Reports of hair loss with semaglutide and tirzepatide
Hair loss has been reported before as a possible adverse effect of GLP-1 receptor agonists, particularly with medications containing semaglutide or tirzepatide. What has been missing is research that directly compares the risk among people taking these medicines with the risk among people taking alternative diabetes treatments.
To address that gap, the research team analysed electronic health records from the University of Pennsylvania Health System (Penn Medicine). They compared rates of alopecia among adults living with type 2 diabetes who began treatment with GLP-1 receptor agonists, SGLT-2 inhibitors or DPP-4 inhibitors.
The analysis covered people treated between January 2019 and September 2024. One comparison included 12,004 people taking GLP-1 receptor agonists and 15,221 taking SGLT-2 inhibitors. A second, separate comparison included 11,964 people taking GLP-1 receptor agonists and 11,233 taking DPP-4 inhibitors.
Accounting for differences between the treatment groups
The groups differed in several important respects before the researchers adjusted their results.
Compared with people taking SGLT-2 inhibitors, those taking GLP-1 receptor agonists were younger (mean age 58 v 65), had a higher body mass index (36.2 v 32.3), and had lower rates of cardiovascular disease and chronic kidney disease.
A similar pattern was seen in the comparison with DPP-4 inhibitors. People taking GLP-1 receptor agonists were again younger (mean age 58 v 67) and had a higher body mass index (36.2 v 31.3).
To limit the influence of these imbalances, the researchers adjusted for factors that might otherwise have shaped the findings, including age, sex, ethnicity, pre-existing conditions, use of other medications, and body mass index.
Higher rates of alopecia after adjustment
Once those adjustments were made, use of a GLP-1 receptor agonist was associated with a 37% higher risk of alopecia than use of an SGLT-2 inhibitor (6.91 v 5.04 per 1,000 person years).
The difference was larger in the second comparison. Risk was 68% higher among people taking GLP-1 receptor agonists than among those taking DPP-4 inhibitors (6.53 v 3.89 per 1,000 person years).
Further analysis indicated that the association was limited to non-scarring alopecia, the form in which hair follicles remain intact and the potential for regrowth is preserved. For this type of hair loss, risk was 53% higher among people taking GLP-1 receptor agonists than among those taking SGLT-2 inhibitors, and 72% higher than among those taking DPP-4 inhibitors.
Why rapid weight loss might disturb the hair cycle
The study did not establish why GLP-1 medications might be connected to hair loss, but the authors set out several plausible explanations.
Rapid weight loss is a well established cause of increased hair shedding. It may also contribute to iron or zinc deficiency, either of which can interfere with the normal hair growth cycle. Hormonal changes related to weight loss or to treatment itself could play a part as well, although further research will be needed to identify the mechanisms at work.
Important questions that remain open
The researchers acknowledged a number of limitations. The available clinical records did not contain enough detail to determine the severity, extent or duration of the alopecia. Nor could the team assess whether hair grew back after people stopped taking the medication.
Because the study was observational, it cannot demonstrate that GLP-1 medications directly caused the hair loss. Other factors that were not measured may have influenced the results.
Set against that, the authors described their work as rigorous, drawing on high quality data from a large and representative group of patients. The findings also held up across additional analyses, which supports their reliability.
What the findings mean for practice
For clinicians, the practical value of a study like this lies less in the headline percentages than in what it adds to the conversation before and during treatment. Anticipating adverse effects, recognising them early and folding them into shared decision-making are core parts of the GLP-1 consultation – the ground covered by CPD courses such as the College of Contemporary Health’s GLP-1RAs in Practice: How to Safely Prescribe Ozempic, Wegovy & Mounjaro, which works through initiation, titration and the avoidance of adverse reactions.
The researchers concluded: “Our findings extend previous anecdotal safety signals and provide more systematic evidence to inform clinical awareness of this potential adverse effect.”
CCH insight
This may seem like an odd perspective, but this could be a good thing if it means that people considering taking GLP-1 medications for vanity reasons (to slim down to their perfect weight when they do not have obesity or type 2 diabetes) are put off, leaving better availability for those who genuinely need it. I am sure that for most people living with obesity or diabetes, a small increased risk of alopecia is worth taking when balanced against the huge health benefits that these drugs usually bring.
Hair loss is unlikely to change prescribing decisions on its own, but it is exactly the kind of adverse effect that patients notice, worry about and sometimes stop treatment over. Knowing how to raise it, put the absolute risk in context and respond if it appears is part of delivering GLP-1 therapy well. CCH’s GLP-1RAs in Practice: How to Safely Prescribe Ozempic, Wegovy & Mounjaro (Or Any Other Weight Loss Drug) is a two-hour, CPD-accredited online course covering every stage of the consultation, from patient selection and titration through to managing adverse reactions, grounded in current NICE guidance and the ADA 2026 Standards of Care.
Find out more about GLP-1RAs in Practice →
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Telehealth Strengthens Diabetes Self-Care but Delivers Only Modest Glycaemic Gains
Key Takeaways:
- Comprehensive telehealth produced modest, non-significant improvements in glycaemic control compared with self-monitoring alone.
- Diabetes self-care was the only outcome to improve significantly, pointing to better self-management rather than better clinical numbers.
- Uptake was low, with relatively few participants completing the intended number of telehealth encounters.
Why self-management sits at the centre of type 2 diabetes care
People living with type 2 diabetes carry much of the day-to-day work of managing their condition. Self-monitoring, medication adherence, lifestyle modification and psychosocial coping all fall largely to the individual, supported at intervals by their clinical team. Comprehensive telehealth has been proposed as a way of closing the gaps between those intervals – enabling more regular contact with health care providers, structured review of patient-generated data, and input from a multidisciplinary team without requiring people to attend in person.
What has remained uncertain is whether that model works in a fee-for-service setting, where reimbursement structures and service design differ markedly from the integrated systems in which much telehealth research has been conducted. A randomised trial published in Annals of Internal Medicine on 23 June 2026 set out to answer that question.
What the trial set out to test
The study, led by Crowley and colleagues, evaluated both the implementation and the effectiveness of a comprehensive telehealth intervention for people with uncontrolled type 2 diabetes and comorbid hypertension, delivered in a fee-for-service context. Participants were randomised either to the comprehensive telehealth programme or to self-monitoring alone, with the comparison designed to isolate the added value of regular provider contact and multidisciplinary review over and above the data-gathering that people were already doing themselves.
Outcomes spanned both the clinical and the behavioural: glycaemic control, blood pressure, weight, diabetes self-care, disease-related distress and self-efficacy, alongside safety monitoring for serious adverse events.
Uptake proved to be the sticking point
One of the clearest findings was not about physiology at all. Uptake of the intervention was limited, with relatively few participants completing the intended number of telehealth encounters. That matters for interpreting everything that follows: a programme that people do not fully engage with is being tested at less than full strength.
Engagement also appeared to shape the results. Improvements in glycaemic control were more evident among participants with greater engagement, suggesting a dose-response relationship that the trial as a whole was not positioned to demonstrate conclusively.
Modest clinical gains that did not reach significance
Compared with self-monitoring alone, comprehensive telehealth was associated with modest improvements in glycaemic control. Those improvements did not reach statistical significance.
The same pattern held across the other clinical measures. The telehealth group showed trends towards better blood pressure and weight outcomes, as well as towards reduced disease-related distress and improved self-efficacy – but again, these differences were not statistically significant. The direction of travel was consistent and favourable; the magnitude simply was not large enough to distinguish the intervention from the comparator.
Self-care was the one clear winner
The exception was diabetes self-care, which was the only outcome that improved significantly with telehealth. It is a result worth dwelling on. It suggests the intervention may strengthen people’s ability to manage their own condition even where clinical measures remain largely unchanged – a benefit that conventional endpoints are poorly designed to capture, and one that may accrue over a longer horizon than the trial allowed.
Whether that improved self-management eventually translates into better glycaemic, blood pressure or weight outcomes is a question the study cannot answer. What it does indicate is that the mechanism telehealth is meant to activate – supported, informed, confident self-management – did in fact activate.
That mechanism depends heavily on the quality of the conversation, not just its frequency. Practitioners looking to strengthen engagement and draw out patients’ own motivation to change are increasingly turning to structured behaviour change training; CCH’s two-hour CPD short course, Behaviour Change Skills: Enhancing Motivation, covers motivational interviewing techniques for exploring readiness, working with ambivalence and recognising change talk in everyday consultations.
Safety and adverse events
Serious adverse events were uncommon and occurred at similar rates in both groups, supporting the safety of the intervention. For a delivery model that reduces face-to-face contact, that reassurance carries weight.
Where the findings stop short
The authors are candid about generalisability. The study population was predominantly low-income with lower educational attainment, and baseline glycaemic control was relatively favourable – leaving less room for improvement than a more poorly controlled cohort would have offered. Digital literacy was not assessed at all, despite being an obvious determinant of who can engage with a telehealth programme and who cannot.
Each of these factors constrains how far the results can be extrapolated to other populations or other service settings.
What this means for practice
The overall picture is one of a promising model that did not, in this setting, demonstrate a clear clinical advantage over self-monitoring alone. Comprehensive telehealth appears capable of enhancing self-management and patient engagement. It did not, here, translate that into measurable clinical benefit.
Further research is needed to establish whether greater uptake of the intervention, or a different patient population, would yield larger benefits. In the meantime, the trial offers a practical reminder for anyone commissioning or delivering remote diabetes care: the technology is only as effective as the engagement it manages to sustain.
CCH insight
This trial found that telehealth improved self-care significantly while clinical measures barely moved – and that engagement was the limiting factor throughout. Motivational interviewing offers an evidence-based way to shift that dynamic, helping people find their own reasons to change rather than pushing against resistance.
Behaviour Change Skills: Enhancing Motivation is a two-hour online CPD course from the College of Contemporary Health, developed with behaviour change specialists at BCT and led by registered dietitians Dympna Pearson and Sam Howard. It carries 2 CPD hours and a Certificate of Completion, and costs £59.
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AI Blood Test Could Detect Early Eye Nerve Damage in People with Type 2 Diabetes
Key Takeaways:
- An AI tool called Pro-DRN uses a blood sample to flag people with type 2 diabetes at high risk of diabetic retinal neurodegeneration (DRN), before any damage shows on the retina.
- It was trained on 1,218 participants and validated in 502 people from UK Biobank, identifying 71 proteins linked to DRN – with ACTA2, COL6A3 and HSPG2 the strongest predictors.
- As retinal nerves are among the first tissues affected by diabetes, the test could also hint at wider nerve damage and help target earlier monitoring and future treatments.
A simple blood test to catch nerve damage early
Scientists have developed an AI-assisted prediction tool that can identify people with type 2 diabetes who are at high risk of developing diabetic retinal neurodegeneration (DRN) before symptoms appear. The findings were published in the journal PLOS Medicine.
The work was led by Wei Wang, MD, PhD, associate professor at the Guangdong Provincial Clinical Research Center for Ocular Diseases. According to the authors, the damage that diabetes inflicts on the delicate nerves of the eye appears to leave a detectable molecular trail in the bloodstream long before it becomes visible in the eye itself.
“Our study suggests that early retinal nerve damage in diabetes leaves measurable signals in the blood,” write the authors. “These findings suggest that a simple blood test analyzed with artificial intelligence may help identify people with diabetes who are at highest risk of early retinal nerve damage, well before visible damage appears on the retina.”
Why the retinal nerves matter in diabetes
Type 2 diabetes affects more than half a billion people worldwide, and it carries an increased risk of long-term complications, including progressive neurodegeneration – the gradual deterioration of nerve tissue over time.
The nerves of the retina are among the earliest tissues to be affected. As this damage advances, it can eventually lead to severe visual impairment and the loss of sight. The difficulty for clinicians is one of timing: current diagnostic methods can only detect DRN once the retina has already sustained irreversible damage. By the time the problem is visible, the window for early, protective intervention has often closed.
How the Pro-DRN tool was built
To address this, Wang and colleagues developed a machine learning algorithm called Pro-DRN. They drew on data from 1,218 participants in the Guangzhou Diabetic Eye Study, all of whom had been diagnosed with type 2 diabetes but had not yet developed DRN at the point of enrolment.
The model combined two distinct streams of information. The first was proteomics data – a detailed read-out of the proteins circulating in participants’ blood samples. The second was a series of yearly retinal images, capturing the state of the eye over a six-year follow-up period. By matching the molecular signals in the blood against how each person’s retina changed year on year, the algorithm learned which blood-borne patterns preceded the onset of nerve damage.
The proteins behind the predictions
The analysis surfaced 71 proteins associated with the development of DRN. Of these, three stood out as the most consistent drivers of accurate prediction: ACTA2, COL6A3 and HSPG2. These are key structural components involved in maintaining the integrity of the nerve and muscle tissue in the eye, which helps explain why disturbances in their levels might signal nerve tissue under strain.
Crucially, the team did not rely on a single dataset. The results were validated in an independent cohort of 502 people from UK Biobank, where the core effects and protein signals were reproduced – an important check that the findings were not simply a quirk of the original group.
From research tool to clinical aid
Pro-DRN has been made available as an interactive, web-based risk assessment tool that clinicians can use to support early DRN screening and to monitor how a person’s risk evolves over time. People identified as being at high risk could then benefit from more frequent check-ups and from early interventions aimed at preventing or slowing progressive neurodegeneration, rather than waiting for damage to become apparent.
A window into the wider nervous system
The potential significance of the test reaches beyond the eye. Because DRN is one of the first signs of nerve degeneration brought on by diabetes, detecting it early could also signal the onset of nerve injury elsewhere in the body.
Such damage can contribute to cognitive impairment, dementia and peripheral neuropathy – the latter causing loss of sensation and motor control in the hands, feet and other extremities. Viewed this way, a single eye-focused test could offer valuable insight into the overall health of a person’s nervous system.
New possibilities for treatment and trials
The discoveries also open up two further avenues. The proteins identified as being involved in DRN progression could be investigated as potential targets for the development of new therapies. In addition, the AI-based tool could prove useful for selecting and stratifying participants in clinical trials that are evaluating neuroprotective strategies designed to prevent or delay nerve damage – helping ensure such studies enrol the people most likely to show a measurable benefit.
Looking ahead
For the researchers, the broader ambition is a shift in how diabetic eye care is approached – from reacting to damage that has already occurred towards anticipating who is most vulnerable.
“Pro-DRN may help move diabetic eye care from detecting established damage toward earlier, molecularly informed risk stratification, so that closer monitoring and future neuroprotective interventions can be directed to the people most likely to benefit,” Wang and colleagues write.
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New Triple-Hormone Injection Shows Major Weight Loss in People with Type 2 Diabetes and Obesity
Key Takeaways:
- In a phase 3 trial, retatrutide cut body weight more than four times as much as placebo and roughly doubled the reduction in long-term blood sugar.
- The once-weekly jab works through three hormone pathways at once – GLP-1, GIP and glucagon – the last of which may help raise energy expenditure.
- Experts called the results encouraging but stressed that head-to-head trials against existing drugs are still needed.
A new approach to managing type 2 diabetes
A once-weekly injection that works through three hormone pathways at the same time could deliver substantial reductions in both blood sugar and body weight for people with type 2 diabetes, according to phase 3 trial results.
People taking part in the trial who received weekly retatrutide injections over 40 weeks lost more than four times as much weight as those given a placebo, while their average reduction in long-term blood sugar (HbA1c) was more than twice that seen in the placebo group.
How retatrutide works
Retatrutide is described as a triple-hormone drug because it mimics three gut hormones that help regulate appetite, blood sugar and metabolism: GLP-1, GIP and glucagon.
This sets it apart from several medications already in use. Drugs such as Ozempic and Wegovy primarily target the GLP-1 pathway to suppress appetite, while Mounjaro combines GLP-1 with GIP to help control blood-sugar levels. Retatrutide goes a step further by also engaging the glucagon receptor, which is thought to help increase energy expenditure.
Inside the phase 3 trial
The trial, published in the Lancet, randomly assigned 930 adults with type 2 diabetes to receive either 4mg, 9mg or 12mg of retatrutide, or a placebo.
None of the participants were already taking diabetes medicines. All had inadequately controlled blood-sugar levels and a body mass index (BMI) of at least 23.
Throughout the trial, researchers monitored a range of health markers, including HbA1c, weight, cholesterol levels and other indicators, and recorded any side-effects that arose.
What the results showed
After 40 weeks, participants receiving retatrutide saw their HbA1c fall by an average of about 1.7–1.9 percentage points, compared with 0.8 in the placebo group.
The weight loss results were similarly marked. On average, participants taking retatrutide lost about 11.5%–15.3% of their body weight, against 2.6% for those on placebo. Cholesterol and blood pressure also improved among people taking the drug.
Safety and side-effects
Fourteen participants experienced serious adverse events during the trial, including two in the placebo group. For most people, however, side-effects were mild to moderate and eased over time, with gastrointestinal symptoms the most commonly reported.
What the findings could mean
The study authors say this triple-action medication has the potential to improve health outcomes for some people, including greater weight loss, particularly for those who may need more intensive treatment regimens to manage their type 2 diabetes. Further clinical trials are continuing.
The results follow earlier findings from the manufacturer, Eli Lilly, which suggested that retatrutide was highly effective at reducing weight among people with obesity.
What the experts say
Dr Kath McCullough, special adviser on obesity at the Royal College of Physicians, said the findings were very encouraging.
“For many people living with diabetes and obesity, treatments like this could be genuinely life-changing,” she said.
“However, medications are not a silver bullet. While they are proving to be effective, the long-term goal must be to prevent people from needing them in the first place.”
Dr Marie Spreckley, a specialist in prevention of diabetes and related metabolic disorders at IMS Epidemiology, University of Cambridge, said the results were striking: “The magnitude of weight loss observed is particularly notable. However, because this study compared retatrutide with placebo rather than semaglutide or tirzepatide, it is not possible to determine from this data whether retatrutide is superior, equivalent or inferior to currently available therapies. Direct head-to-head trials will be required before firm conclusions can be drawn regarding comparative effectiveness.”
She added that weight loss alone did not necessarily equate to optimal health outcomes, and that people needed support to maintain adequate nutritional intake, preserve muscle mass and maximise long-term health during treatment.
Dr Lucy Chambers, the head of research impact and communications at Diabetes UK, said: “These encouraging findings show that this new class of drug for type 2 diabetes could deliver dual benefits for both weight loss and blood-sugar management. We look forward to further research to understand its long-term effects and how it compares to treatments already available on the NHS.”
Source: The Guardian
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Algorithm-Guided Insulin Dosing Improves Blood Sugar Control in Type 2 Diabetes
Key Takeaways:
- An algorithm paired with continuous glucose monitoring significantly increased time in target glucose range compared with standard self-monitoring approaches
- The tool provides personalised weekly insulin dose recommendations based on recent glucose data, helping to simplify titration
- Early findings suggest strong patient acceptability and potential to enhance diabetes management at scale, though larger trials are needed
A data-driven approach to insulin adjustment
A novel algorithm developed by researchers at the University of Virginia Center for Diabetes Technology has demonstrated encouraging results in supporting people living with Type 2 Diabetes to better manage their blood glucose levels.
The system works in combination with a continuous glucose monitor and provides tailored recommendations for insulin dose adjustments. Rather than relying solely on manual interpretation of glucose readings, the algorithm analyses patterns over time and offers structured, data-informed guidance.
In a clinical trial involving 30 participants, individuals were randomly assigned to one of two approaches over a 16-week period:
- Algorithm-guided insulin adjustment using continuous glucose monitoring data
- Traditional self-monitoring of blood glucose with independent dose adjustment
The results showed a marked improvement in glycaemic control among those using the algorithm. Participants in this group increased their average time spent within a safe blood glucose range from 54.1% to 75.3%. By contrast, those relying on self-monitoring alone saw a more modest increase from 50.2% to 55.3%.
Moving beyond traditional insulin management
The findings highlight the growing role of digital health tools in diabetes care. According to Marc D. Breton, the study’s lead author:
“These results clearly show that diabetes technology and advanced algorithms can be leveraged to great effects, well beyond the classical paradigm of automated insulin delivery. As continuous glucose monitoring and connected medical devices become ubiquitous, we have the opportunity to provide highly personalized advice and monitoring to people with diabetes and guide their use of insulin and medications. Showing the impact of these technologies in early insulin therapy (only one dose a day) opens the door to helping the vast majority of people using insulin, well beyond what we were able to achieve with automated insulin delivery.”
This perspective reflects a broader shift towards personalised, technology-enabled care. Rather than fully automated systems alone, there is increasing interest in decision-support tools that augment clinical judgement and patient self-management.
Addressing the challenges of insulin titration
For many people living with type 2 diabetes, treatment often begins with oral or non-insulin therapies. However, as the condition progresses, insulin may become necessary to maintain adequate glycaemic control.
Adjusting insulin doses – a process known as titration – can be complex and burdensome. It typically requires frequent monitoring, interpretation of glucose patterns, and iterative dose changes. Importantly, there is no universally standardised titration protocol, which can create variability in care and outcomes.
To address this, Anas El Fathi developed the algorithm with the aim of streamlining and improving this process. The system evaluates two weeks of continuous glucose monitoring data and generates weekly recommendations for insulin dose adjustments, offering a structured and personalised approach.
Strong acceptance and clinical potential
The study also explored how well the technology was received by participants. According to Ralf Nass:
“From a medical point of view, it was fascinating to see that the algorithm was not only better than the standardized insulin titration recommendations, but also how well the technology was accepted by the participants with type 2 diabetes. This type of technology has the potential to help physicians enable their patients to achieve better glycemic control faster by using a personalized approach.”
This combination of improved outcomes and user acceptability is particularly important, as adherence and engagement remain key challenges in long-term diabetes management.
Future directions – towards more personalised diabetes care
While the results are promising, the researchers emphasise that further validation is required. Larger and longer clinical trials will be needed to confirm the effectiveness of the algorithm across more diverse populations.
Looking ahead, the integration of more advanced data-driven approaches may further enhance personalisation. Breton noted:
“It is only the very beginning of these efforts. With early demonstration behind us, we can focus on robust approaches that will be effective with more varied populations. Integrating recently developed data-driven methodologies, especially digital twins, to further improve our capacity to tailor diabetes managements to individuals is likely to once more revolutionize diabetes care.”
Such developments could represent a significant step forward in precision medicine for people living with diabetes.
Study publication and funding
The findings have been published in the peer-reviewed journal Diabetes Technology & Therapeutics, with the article available as open access.
The research team included El Fathi, Nass, Carol J. Levy, Camilla Levister, Grenye O’Malley, Nirali A. Shah, Shaziah Hassan, Cheryl Quainoo, Chaitanya L.K. Koravi, Taylor N. Nguyen, Giulio Matteo Santini, Emma Emory, Carlene Alix, Dillon K. Flanagan, David Fulkerson, Mary Clancy Oliveri, Christian Laugesen, Jonas K. Lineolov, Peter W. Hansen and Breton.
The clinical trial was supported by a grant from Novo Nordisk.
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Genetic Risk Scores Offer Improved Prediction of Obesity, Type 2 Diabetes and Long-Term Health Outcomes
Key Takeaways:
- A new polygenic risk score integrates genetic data from over 8.5 million people to better predict obesity and type 2 diabetes risk
- The model goes beyond traditional measures such as body mass index by incorporating multiple aspects of metabolic function
- Individuals with higher genetic risk were more likely to develop complications and require interventions such as GLP-1 therapy or bariatric surgery
A more comprehensive approach to metabolic risk
Obesity and type 2 diabetes are complex metabolic conditions influenced by a combination of environmental, behavioural and genetic factors. While traditional clinical measures such as body mass index have long been used to assess risk, they do not fully capture the biological complexity underlying these conditions.
In a new study published in Cell Metabolism, researchers from Mass General Brigham have developed an advanced polygenic risk score designed to improve prediction of both obesity and type 2 diabetes, as well as their long-term health consequences. Polygenic risk scores work by aggregating the effects of many genetic variants across the genome, providing an estimate of an individual’s predisposition to developing a given condition.
“Our intention was to not only capture the risk of being diagnosed with obesity or diabetes, but also to better predict health consequences across the life course by integrating many aspects of metabolic function,” said co-first author Min Seo Kim, MD, MSc. “In the future, this genomic approach could complement established clinical risk factors to inform patient care and preventative strategies.”
Building a next-generation polygenic risk score
The research team constructed two distinct metabolic risk scores – one optimised for obesity and another for type 2 diabetes. Unlike conventional models, these scores incorporate genetic signals linked to 20 different traits associated with metabolic health. These include factors such as fat distribution, insulin regulation and glucose control.
To build these models, the investigators drew on genome-wide association studies conducted across some of the largest biobank datasets globally, encompassing more than 8.5 million individuals. This scale allowed the researchers to capture a broad and diverse range of genetic influences.
Importantly, the model moves beyond reliance on body mass index alone, reflecting a growing recognition that metabolic health cannot be fully understood through weight-based measures in isolation.
Predicting disease progression and clinical outcomes
Beyond predicting the likelihood of developing obesity or type 2 diabetes, the new polygenic risk scores demonstrated the ability to forecast downstream health outcomes.
The researchers found that individuals identified as high risk were more likely to go on to develop complications such as cardiovascular disease and stroke. Even among people who were initially healthy, those with a high genetic risk score were approximately twice as likely to require clinical interventions over time.
Specifically, individuals with higher polygenic risk scores were about twice as likely to receive GLP-1 receptor agonist medications or undergo bariatric surgery compared with those with average risk scores, over a median follow-up period of 5.5 years.
These findings suggest that genetic profiling could help identify people at risk earlier in the disease trajectory, potentially enabling more proactive and targeted care.
Improved performance across diverse populations
A notable strength of the study lies in its use of multi-ancestry genetic data. By incorporating genome-wide association studies from a wide range of populations, including African, East Asian, South Asian and Middle Eastern groups, the researchers were able to develop risk scores that performed better across diverse populations than earlier models.
Historically, many genetic prediction tools have been less accurate in non-European populations due to limited representation in genomic datasets. This study represents a step towards addressing that imbalance and improving equity in precision medicine.
Towards more personalised prevention and treatment
The research team emphasises that this work is part of a broader effort to refine understanding of the genetic subtypes of obesity and type 2 diabetes. Improved classification of these conditions could support more precise patient stratification in clinical trials and, ultimately, more tailored interventions in routine care.
“We want clinicians to be able to think about metabolic conditions in terms beyond body mass index, with a focus more broadly on underlying genetic susceptibility,” said co-senior author Akl Fahed, MD, MPH, of the Cardiovascular Research Center at Massachusetts General Hospital and an interventional cardiologist with the Mass General Brigham Heart and Vascular Institute. “Early identification of people who are likely to have a worse trajectory of poor metabolic health, before they even develop these conditions, can help us improve prevention and clinical interventions. That is how we can cure disease, and that is the bold mission that we are after.”
Implications for clinical practice
While further validation and implementation work will be required, the findings highlight the potential role of genomic tools in enhancing current approaches to metabolic disease prevention and management. By complementing existing clinical risk factors, polygenic risk scores could support earlier identification of people at risk and enable more personalised, proactive care pathways.
As healthcare systems increasingly move towards precision medicine, integrating genetic insights with clinical decision-making may become an important step in improving outcomes for people living with obesity and type 2 diabetes.
CCH insights:
This is exciting research, and a big step towards precision obesity prevention, as it gives us an individual risk score for obesity and diabetes for each patient. However, it is only half the story – ideally we’d also like to be able to determine what type of interventions will work best for each individual (in terms of diet, lifestyle and medicine) in order to optimise their chances of good metabolic health and achieving a healthy weight. Hopefully the ability to do this is not too far away.
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