Type 2 diabetes
Type 2 (T2D), formerly known as diabetes, is a form of diabetes that is characterized by high blood sugar, resistance, and relative lack of insulin. Common symptoms include increased thirst, frequent urination, and unexplained weight loss. Other symptoms include increased hunger, having a sensation of pins and needles, and sores (wounds) that heal slowly. Symptoms often develop slowly. Long-term from high blood sugar include heart disease; ; diabetic , which can result in blindness; kidney failure; and poor blood flow in the lower limbs, which may lead to . A sudden onset of hyperosmolar hyperglycemic state may occur; however, is uncommon.
Underlined words are explained — tap any of them.
Symptoms — what it feels like
- ·Increased thirst, frequent urination, unexplained weight loss, increased hunger
Causes — why it happens
- ·, lack of exercise,
How it's found
- ·Blood test
Prevention
- ·Maintaining normal weight, exercising, healthy diet
Treatment
- ·Dietary changes, exercise, medication such as metformin and , bariatric
Complications
- ·Hyperosmolar hyperglycemic state, diabetic , heart disease, , diabetic , kidney failure, lower-limb
Outlook
- ·10 year shorter life expectancy
Who a European-built risk score flags as “high-risk”
The score (PGS000033) was tuned so 10% of Europeanscross the “high-risk” line (the dashed mark). Bars reaching past it are over-flagged; bars well short are under-flagged — either way the ruler is mis-set for that group.
Share above the European top-10% cutoff. The All-India row is computed on GenomeIndia (≈10,000 genomes); the per-subpopulation rows on 1000 Genomes. Analytical mean-shift, not validated against Indian outcomes. See methods.
How common each gene variant is, by ancestry
The share of people carrying the effect version of each variant. South Asian is highlighted; where it differs from European, a risk model built on Europeans can misread it.
Effect-allele frequencies. All-India is the pooled large-sample number from GenomeIndia (≈10,000 Indian genomes); the South-Asian row is the smaller 1000 Genomes phase-3 panel, kept for finer per-subpopulation resolution.
The sections below are general education drawn from public guidelines (NHS, Mayo, CPIC, WHO, ICMR). They are not individually reviewed by a clinician and are not medical advice — always talk to a doctor about your own health.
When to see a doctor
If you feel well but have a family history or carry extra weight, a routine blood-sugar check at a clinic is a smart step.
See a doctor if you often feel very thirsty, pass urine a lot (especially at night), feel very tired, lose weight without trying, or notice blurry vision or slow-healing cuts.
Get urgent care if you become very drowsy or confused, breathe fast, or have belly pain with vomiting and fruity-smelling breath. These can be signs of a diabetes emergency.
General guidance, not a diagnosis. When in doubt, see a doctor.
Questions to ask your doctor
- ?Which blood test confirms this, and what do my numbers mean?
- ?Given my family history, am I at higher risk?
- ?What lifestyle and food changes help most for me?
- ?How often should I get my blood sugar checked?
- ?Do I need checks for my eyes, kidneys, or feet?
- ?What warning signs should bring me back to you quickly?
What to note before your visit
- ·when your symptoms started
- ·family history of diabetes
- ·your weight and any recent changes
- ·current medicines you take
Myths vs facts
Test yourself
0/4 answered4 quick questions on Type 2 diabetes. Tap an answer to check it.
A European-trained for type 2 flags 30.6% of Telugu (India) people as high-risk - vs the 10% it was designed for. That's a 3.1x : the score's 'average' is set to European , so it systematically mis-reads South Asians (a +0.80 SD ).
A study that would help: PGS000033 on an Indian (define the threshold on South-Asian, not European, risk) and quantify how many people get correctly . A concrete, fundable validation study once a + Indian sample is in hand.
A risk score that cries wolf: built for European bodies, it over-flags Indians
A is not a risk meter. It is a ranking ruler, and its 'high-risk' mark is painted at the line that catches the top 10% of Europeans, the group it was built on. Apply that same line to Telugu Indians and 30.6% cross it, three times too many (our analysis on South Asian samples). It raises the alarm for nearly one in three people when it was meant for one in ten. That is the crying wolf: too many alarms, not too few.
It is tempting to think 30% is simply correct, since Indians really do get more . That is not why the number is high. The whole South Asian score distribution is shifted to the right because the individual gene sit at different frequencies in different ancestries, an of about +0.80 SD for Telugu. That shift is bookkeeping, not a statement that each flagged person truly carries more risk. When a third of people clear a bar meant for a tenth, the flag stops sorting anyone: you can no longer tell who is genuinely highest-risk. A mis-set ruler, not a sharper one.
India has over 100 million adults with (ICMR-INDIAB national study, 2023), and South Asians develop it younger, at lower BMI, with more hidden belly fat, the '' . A tool that mis-ranks them is not an academic quibble: it mis-triages the largest diabetes population on Earth, sending the wrong people to the front of the queue and missing others.
The is real and measurable. What is missing is a South-Asian-calibrated score against actual Indian outcomes: the shift tells us the ruler is off, but only outcome data can say by how much and in which direction for real risk. The training cohorts barely include Indians, and effect sizes and linkage patterns may differ too, which frequency math alone cannot capture.
PGS000033 on an Indian and (even a few thousand people), set the high-risk threshold on South-Asian rather than European risk, and measure how many people get correctly . A clean, validation once a sample is in hand.
- Martin et al., 'Clinical use of current polygenic risk scores may exacerbate health disparities', Nature Genetics 2019
- Anjana et al. (ICMR-INDIAB), Lancet Diabetes & Endocrinology 2023 - ~101M Indians with diabetes
- D2I2 PRS-transferability analysis (1000 Genomes phase 3)