Precision medicine in diabetes – are we there yet?

30th October 2023, Dr Chee L Khoo


When we think about precision medicine, we usually think about some fancy, expensive genetic tests that can help us determine ahead of time who is at risk of some serious diseases. This may allow us to target these patients early and reduce morbidity and mortality. There is connotation that only the rich in rich countries can afford these tests and once again, patients in low and middle income countries (LMIC) will miss out on these state of the art expensive tests. Precision medicine is likely to benefit many more patients in LMIC than you think. Besides, we have pockets of disadvantaged patients that live in Australia, just like patients in LMIC. And Southwest Sydney many of these pockets.

Results from clinical trials are at best, an average of all the results of the intervention versus the comparator. Because we are looking at average results, there are some participants who don’t respond much while others do exceptionally well. While we could celebrate or cry depending on the final results, sometimes, it’s insightful to dive into the outliers to see which subgroup do better and why. We could learn from the original trial and re-design the next trial to look into the special subgroup who might benefit from the intervention.

Another problem with clinical trials is that they are often done in Caucasian populations. Ethnic minorities are often under-represented and when they are represented, often the numbers of the subgroups are so small that Asians, Hispanics and Blacks are lumped together as non-Caucasians. The results are then extrapolated and applied to all.

Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimise outcomes when making medical decisions and health recommendations. Although health-care practices have traditionally followed a one-size-fits-all method, precision medicine aims for a more tailored approach. However, despite much hype on the potential of precision medicine, until now there has been little consensus on its exact definition and clinical relevance.

Often, genomic research is seen as the predominant, if not only, component, which can lead to the assumption that precision medicine solely involves costly techniques and technologies that are not yet widely available. However, precision medicine can incorporate genetic, environmental, and clinical markers to improve accuracy at every stage of medical management—prevention, diagnosis, prediction, treatment and prognosis.

Let’s have a look at how far we have come with attempts in using precision medicine to improve every stage of medical management in diabetes. The second international consensus report from the Precision Medicine in Diabetes Initiative (PMDI) summarises the comprehensive systematic reviews and resulting consensus among the PMDI consortium for the pillars of precision medicine prevention, diagnosis, treatment and prognosis across monogenic diabetes mellitus (MDM), GDM, T1D and T2D.

Monogenic Diabetes Mellitus (or Mature onset diabetes of the young – MODY)

MDM results from a mutation in a single gene. It can be diagnosed in the neonatal period (neonatal diabetes) or typically, but not exclusively, before the age of 45 years. Despite the clinical benefits of making a diagnosis of MDM, many patients are misdiagnosed with T1D or T2D owing to overlapping clinical features. Suspicion is raised in patients who developed diabetes at a young age but current screening is designed to exclude T1D. This is particularly tricky when you now have increasing number of non-Europeans with diabetes and have negative auto-antibodies. They are automatically put in the T2D basket. The limited access to genetic testing outside of the UK means we may be missing many MDMs. Precision treatment of MDM can potentially optimised by characterising an individual’s molecular genetic subtype and pathophysiology. At the end of the day, increasing access to genetic testing will lead to more MDM being diagnosed and receive correct treatment.

Gestational diabetes mellitus (GDM)

Currently, screening and treatment appears to be one-size-fit-all based on criteria designed for late (24-28 weeks) GDM. We all know that women with GDM and overweight/obesity have much higher risks of poor maternal and foetal outcomes. Systematic review and meta-analysis have focused on observational studies evaluating maternal and fetal anthropometry, clinical and sociocultural and environmental risk factors, genetics, omics and nonglycaemic biomarkers that could identify subgroups of individuals with diagnosed GDM at differentially higher risk of adverse pregnancy outcomes.

For most of the precision markers (other than BMI), it will be necessary to conduct validation and replication studies in adequately powered studies of people representing the diversity of target populations. For precision biomarkers, validated, standardized and affordable assays are required for broad adoption by clinical laboratories. There is a need to identify and test different clinical decision and management strategies if a precision diagnostic identifies a woman at high risk of perinatal complications. Finally, for modifiable precision markers (for example, lipid levels, insulin sensitivity), novel interventions should be developed and validated that specifically target these markers during pregnancy. This is where precision medicine can make great impact in targeting the right subgroup of pregnant women so that we can diagnosed GDM early before harm is done to both mother and baby.

The strength of evidence for GDM risk reduction with the use of lifestyle modification, metformin and myoinositol/inositol is moderate to very low. Moreover, few data were available to determine which individual characteristics might predict who would benefit most from a given type of intervention. Precision markers for GDM treatment are usually available from routine clinical measures; however, it is unknown whether other precision markers could be identified (for example, genetics or omics) or whether these can be implemented in clinical practice. Future studies should be appropriately powered and designed to assess individual precision markers or algorithms incorporating multiple precision markers. Validation and replication in diverse populations are lacking and are also needed.

Type 1 diabetes (T1D)

Recent studies looking at different antibodies at different time points in children have enlighten us with who is most likely to develop T1D and who is likely to become antibody negative over time.  A key question in T1D is whether individual characteristics or biomarkers can be used to identify those most likely to respond to disease-modifying therapy before clinical T1D onset (stage 3). Multiple trials were identified that compared disease-modifying agents, mostly immunotherapies, to placebo. There is large interest in precision features associated with treatment response to disease-modifying therapy in T1D; however, most analyses were exploratory without follow-up with prespecified prospective analyses.

Islet autoantibodies are useful to define heterogeneity in T1D before stage 3 diagnosis, and that benefit will be gained by incorporating age and genetics into risk scores. After the Diabetes Control and Complications Trial, there has been little evidence from RCTs for evaluating the impact of tight glycaemic control in specific subgroups with respect to complications; however, clinical precision medicine is utilized in the prognosis and choice of therapy for people with T1D. More sophisticated decision tools, based on deeper genetic and phenotypic profiling in multi-ethnic cohorts are needed to improve personalized prognosis in T1D.

Type 2 diabetes (T2D)

When you think about it, the diagnosis of T2D is actually one of exclusion, occurring when other plausible explanations for chronically elevated blood glucose have been considered and dismissed. This high degree of uncertainty and potential heterogeneity presents major challenges for the prevention and treatment of T2D. Large-scale RCTs demonstrate that dietary or lifestyle interventions can delay the progression to T2D. However, there is large interindividual variability in response to preventive interventions because T2D is a heterogeneous group.

Current data on the clinical value of T2D subclassification come predominantly from populations of European ancestry. Though glycaemic measures are used to diagnose T2D, several non-glycaemic measures were consistently applied to subclassify disease, including BMI, homeostatic model assessment of insulin resistance, C-peptide and lipid profiles.

We looked at an attempt at subclassification of diabetes by Ahlqvist et al. which have been replicated in 22 studies. Subclassification strategies for T2D have been associated with meaningful clinical outcomes. However, evidence supporting the clinical application of these subclassification approaches is of moderate quality.

Subclassification can also lead to tailoring of treatment according to individual-level demographic, clinical or biological biomarkers associated with heterogeneous glycemia, CVD and renal outcome in individuals with T2D treated with SLGT2i or GLP1-RA.

Incorporating trials explicitly designed to test precision medicine hypotheses in the drug development pipeline will be important if treatment recommendations for these drugs are to be meaningfully optimized. For this to succeed, engagement with regulatory authorities will be required. These and other supporting studies should consider whether markers of treatment heterogeneity are part of causal process, or non-cause predictors of such effects.

At this point in time, precision diabetes medicine is still largely aspirational. It is a potentially highly practical and economically viable alternative to current practices for diabetes prevention, diagnosis, treatment and prognostics, encompassing wide-ranging data about exposures and outcomes.

A key finding of this consensus report is that trials explicitly designed to test precision medicine hypotheses are needed, particularly those that yield clinically translatable findings. Incorporating trials explicitly designed to test precision medicine hypotheses in the drug development pipeline will be important if treatment recommendations for these drugs are to be meaningfully optimized. For this to succeed, engagement with regulatory authorities will be required.

As much of the current precision diabetes medicine research has been conducted in people of European ancestry living in high-income settings, there is a pressing need to broaden the scope to include other ethnic, geographic and cultural groups, particularly those who are most vulnerable. Correspondingly, there is also a need to better understand the impact of precision medicine on disparities, to help ensure gaps are closed and not inadvertently widened.


Tobias, D.K., Merino, J., Ahmad, A. et al. Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine. Nat Med 29, 2438–2457 (2023).