HbA1c-based diagnosis of type 2 diabetes and complication risk are distorted in British south Asians due to HbE thalassaemia trait

This study reveals that the HbE thalassaemia trait, which is prevalent but often undiagnosed among British South Asians, artificially elevates HbA1c levels without increasing blood glucose, leading to the overdiagnosis and overtreatment of type 2 diabetes and a distorted assessment of complication risks.

The Gist

Imagine your body has a "report card" that doctors use to check if you have diabetes. For decades, this report card has been a test called HbA1c. Think of HbA1c like a sticky note that gets stuck to your red blood cells. The stickier the note, the higher your blood sugar has been over the last few months. Doctors look at how many sticky notes are on the cells to decide if you have diabetes and how to treat it.

However, a new study suggests that for a huge number of people—specifically those of South Asian descent (from places like Pakistan and Bangladesh)—this "sticky note" system is broken. It's not just a bad note; it's a glitch in the system.

Here is the story of what the researchers found, explained simply:

1. The Hidden Glitch: The "HbE" Trait

About 350 million people worldwide carry a genetic trait called Thalassaemia (specifically a type called HbE). It's like having a slightly different engine in your car. Most of the time, this engine runs fine, and the driver (the person) doesn't even know they have it. In fact, the study found that 3 out of 4 people with this trait in the UK didn't even know they had it because it wasn't written in their medical records.

2. The Broken Sticky Note

The problem is that this "different engine" changes how the sticky note (HbA1c) behaves.

• In most people: The sticky note accurately reflects the sugar in the blood.
• In people with HbE: The sticky note gets extra sticky even if the sugar level is normal. It's like a magnet that attracts more notes than it should.

Because of this, the test says, "Wow, your sugar is high!" when it's actually fine. The test is lying by making the sugar look higher than it really is.

3. The False Alarm: Over-Diagnosis

Because the test lies and shows high sugar, doctors get worried. They tell patients, "You have pre-diabetes" or "You have diabetes," even though their actual blood sugar is normal.

• The Result: People are over-diagnosed. They are told they are sick when they aren't.
• The Consequence: They start taking medicine they don't need. They worry about their health unnecessarily. It's like being told your car is overheating when the engine is actually cool, so you keep pouring water on it for no reason.

4. The Strange Twist: Fewer Complications?

Here is the weird part. Usually, if you have diabetes, you risk getting eye problems or stroke. But in this study, people with the HbE trait who were diagnosed with diabetes actually had fewer of these complications.

Why?
It wasn't because they were healthier. It was because they were over-treated.

• Because the test lied and said they were sick, doctors gave them strong medicine to lower their sugar.
• This medicine accidentally kept their real sugar levels very low and safe.
• So, the "glitch" that caused a false alarm actually led to them getting extra treatment, which protected them from complications.

It's a bit like a smoke detector that is too sensitive. It screams "Fire!" when there is only toast burning. Because it screams so loudly, the fire department comes immediately and sprays water everywhere. The house never burns down, but you've wasted a lot of water and caused a mess!

5. The Big Takeaway

The researchers are saying: "Stop trusting the sticky note for everyone."

For millions of people with this genetic trait, the standard diabetes test is unreliable. It is causing:

• Confusion: People are told they are sick when they aren't.
• Inequality: This mostly affects South Asian communities, who already face higher risks of diabetes.
• Wasted Resources: People are taking medicine they don't need.

The Solution:
Doctors need to use different tools for these patients. Instead of just looking at the "sticky note" (HbA1c), they should look at the actual blood sugar levels directly, or use other tests that aren't fooled by this genetic trait. We need a personalized approach so that everyone gets the right diagnosis, not a "one-size-fits-all" test that breaks for certain groups.

In short: The ruler we use to measure diabetes is bent for millions of people. We need to find a straight ruler so we don't accidentally tell healthy people they are sick, or sick people they are healthy.

Technical Summary

1. Problem Statement

The diagnosis and management of Type 2 Diabetes (T2D) globally rely heavily on Glycated Haemoglobin (HbA1c) as a proxy for average blood glucose. However, genetic variants affecting red blood cell (RBC) biology can distort the relationship between HbA1c and actual glycaemia.

• Context: While variants like G6PD deficiency and PIEZO1 mutations are known to lower HbA1c (leading to under-diagnosis), the impact of HbE thalassaemia trait (a common beta-thalassaemia variant in South Asia) on HbA1c and clinical outcomes remains poorly understood.
• The Gap: HbE trait is estimated to affect millions globally but is frequently undiagnosed in clinical practice. It is unclear whether HbE trait causes HbA1c overestimation or underestimation, and how this distortion impacts T2D diagnosis rates and long-term complication risks.
• Clinical Risk: If HbA1c is falsely elevated due to HbE trait, patients may be over-diagnosed with pre-diabetes or T2D and subjected to unnecessary treatment, potentially altering their complication profiles.

2. Methodology

The study utilized the Genes & Health cohort, a large-scale population study of British Bangladeshi and British Pakistani individuals.

• Study Population: 43,088 participants with linked Whole Exome Sequencing (WES) data and longitudinal Electronic Health Records (EHR) from the UK National Health Service (NHS).
• Genetic Definition:
  • Identified heterozygous carriers of ClinVar "Pathogenic" or "Likely Pathogenic" variants in the HBB gene (beta-thalassaemia).
  • Focused specifically on rs33950507, the common variant causing HbE trait (Minor Allele Frequency >1%).
  • Analyzed rare variants (MAF <1%) in an aggregated "mask" to boost statistical power.
• Exclusion Criteria: Individuals with homozygous/compound heterozygous thalassaemia (disease state), sickle cell disease, blood transfusions, or existing Type 1/MODY/secondary diabetes.
• Data Sources:
  • Genetic: WES data for variant calling.
  • Clinical: NHS EHRs for HbA1c, glucose, T2D diagnosis codes, and complication codes (eye disease, cerebrovascular disease, etc.).
  • Prediction Tool: Evaluated the performance of "ThalPred," a clinical algorithm using routine blood tests (MCV, MCH, RBC count) to detect thalassaemia trait.
• Statistical Analysis:
  • Association Testing: Multivariable regression (REGENIE) for quantitative traits (HbA1c, glucose) adjusted for age, sex, ancestry, and principal components.
  • Survival Analysis: Cox proportional hazards models to assess time-to-event for T2D diagnosis and complications.
  • Mediation Analysis: Sensitivity analyses adjusting for HbA1c, T2D diagnosis status, and antidiabetic drug exposure to determine if the association between HbE and complications was mediated by over-diagnosis/treatment.
  • Meta-analysis: Combined results with external summary statistics (UK Biobank, AMP-T2D study) for replication.

3. Key Contributions

• First Large-Scale Evidence: This is the first study to systematically link genetically defined HbE thalassaemia trait to T2D diagnosis rates and specific complication risks in a large, real-world cohort.
• Directional Contrast: It demonstrates that HbE trait causes increased HbA1c (unlike G6PD or PIEZO1 which decrease it), leading to a distinct clinical phenotype of over-diagnosis.
• Under-diagnosis of Trait: Quantifies the massive gap between genetic prevalence and clinical diagnosis of thalassaemia trait in the UK South Asian population.
• Mediation Mechanism: Provides evidence that the reduced risk of complications in HbE carriers is likely a statistical artifact of over-diagnosis and subsequent over-treatment, rather than a biological protective effect.

4. Key Results

A. Prevalence and Under-diagnosis

• Genetic Prevalence: 5.8% (2,490/43,088) of participants were heterozygous carriers of pathogenic thalassaemia variants.
• Clinical Gap: Only 28.1% of these genetically confirmed carriers had a clinical diagnosis of thalassaemia in their NHS records.
• Prediction Tool Failure: The "ThalPred" algorithm, designed to identify trait via routine blood tests, had low specificity (22.1%) and identified only 34.3% of genetic carriers, failing to reliably distinguish them from iron deficiency anaemia.

B. Impact on Glycaemic Traits

• HbA1c: The HbE variant (rs33950507) was significantly associated with higher HbA1c ($\beta$ = 0.13, $p=7.8 \times 10^{-8}$).
• Glucose: There was no association between the HbE variant and actual blood glucose levels ($\beta$ = 0.01, $p=0.72$).
• Conclusion: The elevated HbA1c is an artifact of the assay (likely HPLC interference due to cationic charge changes in HbE) rather than true hyperglycaemia.
• Rare Variants: In contrast, rare HBB variants showed a trend toward lower HbA1c, suggesting mechanistic differences between common structural variants (HbE) and rare loss-of-function variants.

C. Impact on T2D Diagnosis

• Increased Hazard: HbE carriers had a significantly higher risk of being diagnosed with pre-diabetes (HR = 1.38) and T2D (HR = 1.11).
• Interpretation: This increase is attributed to the falsely elevated HbA1c triggering diagnostic thresholds, not an intrinsic increase in diabetogenic risk.

D. Impact on Complications

• Reduced Hazard: HbE carriers showed reduced hazards for diabetic eye disease (HR = 0.74) and cerebrovascular disease (HR = 0.44).
• Mediation: When models were adjusted for T2D diagnosis status and antidiabetic drug exposure, these protective associations disappeared (attenuated to non-significance).
• Mechanism: The "protective" effect is likely due to over-treatment. Because HbA1c is falsely high, carriers are diagnosed earlier and treated more aggressively, potentially preventing complications that would have occurred if they were undiagnosed.

5. Significance and Implications

• Clinical Practice: Relying solely on HbA1c for diagnosing and managing T2D in South Asian populations (and potentially other groups with high haemoglobinopathy prevalence) leads to systematic over-diagnosis and over-treatment.
• Precision Medicine: There is an urgent need for alternative diagnostic approaches (e.g., fructosamine, continuous glucose monitoring, or genetic screening) for individuals with suspected haemoglobinopathies.
• Health Equity: The current bias in HbA1c interpretation exacerbates health inequalities. South Asian populations, who already face higher T2D risks, are being subjected to unnecessary medicalization and the psychological/financial burden of over-diagnosis.
• Quality Assurance: The study highlights that research protocols (like UK Biobank) often exclude HbE samples due to "unreportable" flags, whereas clinical labs may report them as falsely elevated, leading to real-world diagnostic errors.
• Future Directions: Guidelines should explicitly address HbE trait, and clinicians should be aware that a high HbA1c in a South Asian patient without corresponding hyperglycaemia may indicate a haemoglobinopathy rather than diabetes.

Conclusion: The study concludes that HbE thalassaemia trait distorts HbA1c upwards, leading to a cascade of over-diagnosis and over-treatment. While this may inadvertently reduce complication rates through aggressive management, it represents a failure of precision medicine that requires immediate correction through better biomarkers and diagnostic algorithms.