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The growing number of glucose-lowering drugs with different mechanisms of action calls for better patient
[22]
segmentation to prioritize treatment selection . Using HOMA indexes, GADA, age, BMI, and age of
diagnosis, researchers classified patients with type 2 diabetes into five subtypes. Patients with severe insulin
resistance had a high risk of chronic kidney disease, while those with autoimmune or severe insulin
deficiency required early insulin treatment . These studies had been replicated in other populations,
[129]
including Chinese, in whom severe insulin-deficient type was more common and mild age-related diabetes
was less common than their European counterparts. In all five subtypes of diabetes, Chinese patients had an
earlier age of diagnosis, lower BMI, HOMA-beta, and higher HbA1c [130,131] . In a cross-sectional analysis,
Chinese patients with YOD had lower beta-cell function with a steeper negative relationship between beta-
cell function and disease duration than that in their late-onset counterparts .
[81]

NEED FOR RANDOMIZED CONTROLLED TRIAL GUIDED BY PHENOTYPES TO INFORM
PRACTICE
Despite the organ-protective effects of SGLT2i and GLP1-RA, such evidence mainly came from high-risk
patients with complications. Optimal glycemic control remained the cornerstone in diabetes management,
and given the variable phenotypes suggestive of contribution from different etiologies, more studies are
[132]
needed to guide treatment based on phenotypes or genotypes . For example, in the Trimaster Study,
patients with type 2 diabetes and an estimated glomerular filtration rate of 60-90 mL/min/1.73m were more
2
2
responsive to DPP4i than SGLT2i. Patients with low BMI (< 30 kg/m ) were also more responsive to DPP4i
than thiazolidinediones . Apart from its proven benefits in preventing diabetes, metformin also reduces
[133]
the risk of vascular, renal, cancer, and pneumonia events and all-cause death in type 2 diabetes . There is
[134]
also evidence suggesting that patients with predominant insulin deficiency may benefit from the addition of
insulin secretagogues (e.g., SU), prandial insulin regulators (e.g., GLP1-RA, DPP4i, AGI), or insulin
treatment, while those with insulin resistance, often due to obesity, might benefit more from weight-neutral
or weight-reducing therapies such as GLP1-RA and SGLT2i [135,136] . In a proof-of-concept analysis, we
stratified patients with type 2 diabetes by CP and insulin treatment and reported that patients with low CP
and treated with insulin had the lowest mortality rate .
[137]
In the VERIFY Trial, newly diagnosed patients with type 2 diabetes treated with combination therapy of
metformin and DPP4i had more durable glycemic control and 30% reduced risk of progression to insulin
treatment compared to those treated with metformin monotherapy followed by DPP4i only with rising
[138]
[123]
HbA1c . These effects were particularly evident in patients with YOD . In a real-world database,
patients with type 2 diabetes, the majority of whom were on metformin and/or SU, those with additional
DPP4i within 2 years of diagnosis had a 30% reduced risk of insulin treatment compared to those with
[57]
additional DPP4 after 3-5 years of diagnosis . These findings highlight the importance of early diagnosis,
early intervention, and early control in preserving beta-cell function, especially in patients with
compromised beta-cell function. Against a backdrop of the declining use of SU, increasing popularity of
SGLT2i, and advocacy of using GLP1-RA to replace insulin, the importance of better classification cannot
be emphasized enough to ensure timely and appropriate treatment for maximizing efficacy (e.g., SU in
patients with HNF1α- and HNF4α-MODY) and reducing side-effects (e.g., insulin analogs in patients with
LADA or severe insulin insufficiency to avoid diabetic ketoacidosis and severe hypoglycemia). Despite their
heterogeneous phenotypes and treatment responses, there is a lack of RCT data to guide diagnosis and
treatment in these high-risk patients with YOD .
[12]
PSYCHOSOCIAL-BEHAVIORAL NEEDS AND LIFECOURSE MANAGEMENT
Perinatal development, environmental exposure, socioeconomic status, migration, education, and health
behaviors can interact in a complex manner to cause childhood obesity, which can track into adulthood
[139]