DM Testing Ethics, accuracy of test

Rethinking DM Genetic Testing: Genetics, Ethics, Accuracy, Future of Breeding. – Abhai Kaul

Ethical Consequences of misapplying the the findings from DM Genetic Testing.


The numbers in the Venn diagram represent the relative weight of concerns in each category and their intersections. Here’s a breakdown of what each section means: 

Individual Categories

  • 10 (Genetic Testing Limitations Only)  
  • Issues that stem directly from the test itself, without relying on statistical analysis or ethical concerns.  
  • Example: The test only identifies genetic predisposition, not disease onset.  
  • 10 (Bayes’ Theorem Use Only)
  • Problems that arise when trying to apply Bayesian probability to DM test results.  
  • Example: The prior probability (P(A)) of developing DM is uncertain, making the final probability unreliable.  
  • 15 (Ethical Concerns Only)  
  • Ethical questions unrelated to the accuracy of the test or statistical models.  
  • Example: Is it ethical to exclude genetically “At Risk” dogs from breeding when many never develop symptoms?  

Overlapping Categories

  • 8 (Genetic Testing & Bayes’ Theorem Overlap) 
  • How the limitations of the test directly affect the reliability of Bayesian analysis.  
  • Example: The test has a high rate of false positives, which skews Bayes’ Theorem calculations.  
  • 18 (Genetic Testing & Ethical Concerns Overlap)  
  • Ethical dilemmas caused by flaws in the genetic test itself.  
  • Example: Should owners be making health decisions based on an unreliable test?  
  • 7 (Bayes’ Theorem & Ethical Concerns Overlap)
  • Ethical problems that arise when statistical models mislead owners or breeders.  
  • Example: If the probability of developing DM after testing “At Risk” is lower than expected, should owners be warned about unnecessary panic?  

All Three Categories:

(Overlap of Genetic Testing, Bayes’ Theorem, and Ethics)

  • 5 (Intersection of All Three Areas)
  • Issues that tie together test reliability, statistical misinterpretation, and ethical concerns.  
  • Example: Testing companies may present results without statistical context, leading to flawed health and breeding decisions.  

What This Means

1. The biggest concern (18) is ethical, indicating that how we use test results matters as much as the science behind them.

2. Genetic testing (10) and Bayes’ Theorem (10) each have individual issues, but their intersection (8) shows that misinterpreting test data statistically can amplify problems.

3. The core problem (5) is when all three issues converge, such as when misleading test results create statistical confusion and lead to unethical decision-making.

Breakdown of the Venn Diagram with Emphasis on Ethical Dilemmas from Test Inefficiency  

The most critical overlap in this discussion is between Genetic Testing Limitations and Ethical Concerns (18). This section focuses on how the inefficacy of the test contributes to unethical exclusion of dogs from the breeding pool, despite their potential to improve the breed in other ways.  

Key Takeaways

  • Genetic Testing & Ethical Concerns Overlap (18)
  • Excluding genetically “At Risk” dogs removes valuable contributions to the breed. 

A dog with exceptional working ability, sound structure, or strong longevity genes might be discarded based solely on an unreliable test.  

  • False positives are particularly damaging. 

Because many “At Risk” dogs never develop DM, removing them from breeding programs is an unnecessary restriction that reduces genetic diversity.  

  • A flawed test influences irreversible decisions. 

Unlike a health screening for a currently existing disease, DM genetic tests are being used preemptively to eliminate breeding options—despite the fact that many of these dogs will never experience symptoms.  While Bayesian misinterpretations can cause confusion, the real-world impact is more about test limitations than statistical error.  

Ethical concerns arise independently of statistical flaws—even if interpreted correctly, the test itself is still problematic.  The primary concern is not just misinterpreting the test, but the flawed decision-making that results from over-reliance on it.  

  • The breed-wide impact is long-term and systemic. 

Widespread over-reliance on this test can lead to an artificially restricted gene pool, potentially increasing the prevalence of other heritable diseases that are not being considered.  

Why This Overlap is More Significant than Others

While Bayes’ Theorem’s application still plays a role in misinterpretation of test results, the real-world impact is felt most strongly in breeding ethics. The consequences of excluding genetically valuable dogs go beyond just miscalculated probabilities— they have tangible, long-term effects on the health and viability of future generations.  

Beyond the Test: The Ethical Consequences of Misapplying DM Genetic Screening  

In our previous analysis, we examined the limitations of Degenerative Myelopathy (DM) genetic testing, demonstrating that a positive test result does not equate to a clinical diagnosis. Now, we turn to a broader and more pressing question: What are the ethical implications of relying on an unreliable test to shape the future of the breed?

Genetic testing is often hailed as a revolutionary tool for improving canine health, but when applied irresponsibly, it can have the opposite effect—removing genetically valuable dogs from breeding programs based on false positives and incomplete data. This follow-up article explores the intersection of genetic testing limitations and ethical concerns, particularly how over-reliance on the DM test may compromise genetic diversity, mislead dog owners, and create unintended consequences for the breed as a whole.  

The Ethical Dilemma: Genetic Testing Influence on Breeding Decisions  

The most significant concern with DM genetic testing is not its existence, but its misuse in breeding programs. When breeders use an unreliable test as an absolute measure of a dog’s health, they may unknowingly contribute to a narrowing of the gene pool.  

Consider the following scenario:  

  • A young German Shepherd tests “At Risk” for DM (revealed in Genetic Testing) but has a long-lived, healthy lineage with no history of the disease.  
  • Despite excelling in temperament, structure, and working ability, the dog is excluded from breeding based on a test that does not actually diagnose the disease.  
  • Over time, other important traits—such as longevity, orthopedic health, and working ability are lost due to over-prioritization of a single, questionable genetic marker.  

This selective exclusion prioritizes genetic purity over real-world health outcomes, ultimately increasing the risk of inbreeding, reduced genetic variation, and the unintended spread of other heritable diseases.  

False Positives: The Risk of Misguided Decision-Making

A fundamental flaw of the DM test is its inability to differentiate between a dog that carries the SOD1 mutation and a dog that will actually develop symptoms. By conservative estimates, many dogs that test “At Risk” will never develop DM, meaning that:  

  • They are being unfairly labeled as genetically compromised.  
  • Breeders may exclude them unnecessarily, weakening the overall gene pool.  

This presents an ethical paradox:  

  • If a test cannot predict disease with certainty, is it ethical to use it as a breeding filter?  
  • Does an “At Risk” label unfairly stigmatize dogs that could contribute positively to the breed in other ways?  
  • Should real-world health outcomes (such as family longevity and the absence of symptoms in past generations) be weighted more heavily than a single genetic marker with unclear predictive power?  

The answer should be obvious—No single test should dictate breeding decisions in isolation.  

A Larger Responsibility: The Role of Breeders, Veterinarians, and Genetic Testing Companies  

While the responsibility for ethical breeding decisions ultimately falls on breeders, veterinarians and genetic testing companies also have a duty to provide context for test results.  

  • Genetic testing companies should clarify the limitations of the test. Marketing materials should avoid fear-based language that implies an “At Risk” dog is certain to develop DM.  
  • Veterinarians should educate owners on the difference between genetic predisposition and clinical disease.  
  • Breeders must balance genetic health with diversity, ensuring that selection criteria do not unnecessarily eliminate dogs that could strengthen the breed.  

Conclusion: Prioritizing Real-World Health Over Genetic Testing Absolutism

 The rise of genetic testing has given breeders and owners powerful new tools, but with that power comes the responsibility to use them wisely. The DM test, while useful as one data point, is not definitive enough to justify exclusionary breeding practices. Family longevity, working ability, and overall health history remain far more reliable indicators of a dog’s future well-being than a single genetic marker.

As we move forward, the goal should not be to breed only for genetic “perfection”—a concept that is ultimately unattainable—but to preserve and strengthen the breed through balanced, informed decision-making. Breeding should not be a reaction to a test result but a long-term strategy that considers genetic diversity, real-world health, and breed viability as a whole.  

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