False positives in genetic testing are more common than you might think. Research shows that up to 40% of results from consumer DNA tests may be false positives, meaning the test flags a genetic variant you don’t actually have.
If you’re considering a DNA test — or you’ve already gotten results that concern you — we’ll walk you through the false positive rates across different types of genetic tests and what you can do about it.
How Often Do False Positives Happen?
False positive rates vary widely depending on the type of test. Here’s what the research tells us across consumer tests, prenatal screenings, and cancer detection.
Direct-to-Consumer Genetic Tests
At-home DNA tests you can buy online are convenient, but their accuracy isn’t always on par with clinical-grade testing. The false positive rates can be surprisingly high.
- 40% false positive rate: A study comparing DTC test results to clinical lab results found that 4 in 10 consumer results were false positives.
- Raw data concerns: An independent analysis found the same 40% false positive rate in genes with potential clinical impact when looking at raw genotyping data from DTC tests.
- BRCA screening gaps: For BRCA1/2 mutations specifically, one study found a clinical false-negative rate of 88.5% in screening cohorts. This means tests that only check specific variants can miss — or misidentify — important mutations.
- Unnecessary anxiety: Most people who get a “positive” result from a consumer test will never develop the flagged condition. That mismatch can cause real stress and worry.
Prenatal Screenings
Non-invasive prenatal testing (NIPT) screens for chromosomal abnormalities during pregnancy. These tests are widely used, but their accuracy depends heavily on what condition they’re screening for.
- Down syndrome: NIPT has a positive predictive value (PPV) of about 90% for Down syndrome. That means roughly 1 in 10 positive results may be false.
- Rare conditions are less reliable: For microdeletions like DiGeorge syndrome, the PPV drops to as low as 2% to 30%. That’s a very high false positive rate.
- 27:1 ratio: One study found 27 false positives for every false negative in NIPT results.
- More flags than actual cases: Another report found that NIPT detects 10.8 times more abnormal cases than are actually expected to be born, showing a big gap between positive results and real outcomes.
- Sex chromosome screening: The false positive rate for sex chromosome aneuploidies was 0.12% in one meta-analysis. However, 8.6% of positive results in another study were traced to abnormalities in the mother’s own chromosomes, not the baby’s.
Multi-Cancer Early Detection (Galleri Test)
The Galleri test screens for multiple cancers from a single blood draw, but it also has notable false positive rates.
The test initially reported a PPV of 44.6%, which later dropped to 38.0%. That means more than 6 in 10 positive Galleri results may not reflect actual cancer.
What Happens When You Get a False Positive
A false positive doesn’t just mean an incorrect test result. It can affect your life in real, tangible ways.
- Emotional toll: If you’re pregnant and a prenatal screening flags a disorder your baby doesn’t have, that false alarm can cause lasting anxiety throughout your pregnancy.
- Family tension: Genetic test results can reveal information about your relatives, too. Unexpected findings can strain family relationships, especially when other family members didn’t consent to or expect those revelations.
- Financial costs: Confirming whether a result is a true or false positive often requires follow-up testing, specialist visits, and additional procedures. Those costs add up.
- Unnecessary medical procedures: In one documented case, a woman was scheduled for surgery based on a false positive for a BRCA1 variant. The result was later found to be incorrect. False positives can lead to treatments and interventions you don’t actually need.
How Labs Are Reducing False Positives
Researchers and labs are actively working to bring these numbers down. Here are some of the approaches showing promise.
- Machine learning in newborn screening: Studies show that machine learning algorithms can reduce false positive cases in newborn screening for certain conditions.
- Second-tier and next-gen testing: Using second-tier tests and next-generation sequencing (NGS) can help filter out false positives, though these methods sometimes detect variants of unknown significance, which raises its own questions.
- Better lab practices: Strict laboratory hygiene, good pipetting technique, sterile labware, and dedicated PCR stations all reduce the chance of contamination-driven false positives.
- Adjusting screening thresholds: Changing the cut-off values in newborn screening can reduce false positives, but there’s a trade-off — it can also increase the risk of missing real positives (false negatives).
- CDC investigation toolkit: The CDC offers a toolkit for investigating suspected false positives, emphasizing genotyping results and epidemiological review to sort real from erroneous results.
