The BRCA Gene and the Women Who Lost Their Breasts to a Hypothesis

An Essay on the Distance Between Association and Causation

In every family studied in the foundational BRCA1 paper, at least one woman carried the “cancer-causing mutation” and lived to age 80 without developing cancer.

This is not buried in an appendix. It appears in the 1994 Science paper that announced BRCA1 to the world—the paper that launched genetic testing, preventive surgeries, and a billion-dollar industry. The authors state it plainly: carriers of clearly deleterious mutations, mutations “causing breast cancer in women at very young ages,” included individuals who carried those same mutations for eight decades without ever developing malignancy.

Thirty-five to fifty-five percent of those who test positive for a BRCA variant never develop breast cancer. This figure comes from the research itself. It means the variant, by itself, does not determine who gets cancer.

The public received a different message.

A note on method: The critique that follows engages this research within its own framework—using the language of genes, mutations, and carriers that the papers employ. This is not an endorsement of that framework. Whether DNA theory accurately describes biological reality is a separate question, addressed elsewhere. Here, the goal is narrower: to show that even accepting the premises of genetic medicine, the BRCA causation claim does not follow from the evidence presented.

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What the Papers Actually Found

The story begins in 1990, when Mary-Claire King’s laboratory published a landmark paper in Science announcing that early-onset familial breast cancer was linked to a region on chromosome 17. Four years later, a team led by Yoshio Miki claimed to identify the gene responsible: BRCA1. A second gene, BRCA2, followed shortly after.

The methodology was straightforward. Researchers identified families with unusual clustering of breast cancer—multiple cases across generations, often diagnosed young. They looked for genetic markers that segregated with the disease: markers present in family members who got cancer, absent in those who didn’t.

In families where the mean age of breast cancer diagnosis was 45 or younger, a marker called D17S74 showed strong statistical linkage to the disease. The lod score—a measure of how likely the linkage is to be real versus coincidental—reached +5.98 in these families. Anything above +3 is considered significant.

The 1994 Miki paper went further. The researchers sequenced what they identified as the gene in these high-risk families and reported specific variations: deletions, insertions, substitutions that they interpreted as producing truncated proteins or no protein at all. These variations tracked perfectly with affected status within the families they studied. Those with the variant got cancer. Those without it didn’t. The variations were rare in control populations.

This is real science in the technical sense. The statistics are sound. The methodology follows established protocols. What it does not do is prove what the public was told it proves.

But what does it prove?

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The Problem of Ascertainment

The families in these studies were not randomly selected. They were identified precisely because they had abnormal cancer clustering—six, eight, ten cases across generations, often diagnosed before age 50. This is called ascertainment bias, and it matters enormously for interpreting results.

When you select families because they have extreme disease clustering, you’ve pre-selected for whatever factors cause that clustering. Finding a genetic marker that tracks with disease in such families tells you the marker is associated with disease in families that were already unusual.

It does not tell you what that marker means in the general population.

Consider an analogy. Suppose you wanted to study whether red hair causes sunburn. You select families where multiple members have experienced severe sunburns. You find that red hair segregates with sunburn in these families. Redheads burn, non-redheads don’t.

Have you proven that red hair causes sunburn? Or have you demonstrated that red hair is associated with sunburn in families selected because they burn easily—families that might share not just hair color but also fair skin, outdoor occupations, geographic location, and sun exposure habits?

The BRCA families share more than genetic markers. They share environments, dietary patterns, household toxins, water supplies, stress patterns, and exposure histories. Finding a genetic marker that tracks with cancer in such families does not rule out shared environmental causes. It establishes association within a pre-selected group. The leap to causation is not supported by the data.

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The Word That Smuggles In the Conclusion

When the researchers found DNA sequence variations in cancer-prone families, they called them “mutations.” This word choice is not neutral.

A mutation implies something broken, damaged, pathological. It carries causal weight. But what the researchers actually observed were sequence variations—DNA that differs from an arbitrarily defined reference standard.

The human genome is said to contain millions of such variations between individuals. Most are called “variants” or “polymorphisms.” The ones associated with disease get called “mutations.” The distinction is circular: we call it a mutation because it’s associated with disease, and we believe it causes disease because it’s a mutation.

The BRCA1 paper reported frameshift deletions, nonsense substitutions, and insertions that the authors interpreted as producing truncated proteins. They classified these as loss-of-function mutations in a tumor suppressor gene. The interpretation assumes that the protein’s normal function is to prevent cancer, and that without functional protein, cancer results.

But this is a hypothesis, not an observation. The papers demonstrate that certain sequence variations are more common in cancer-prone families. They do not demonstrate that these variations cause cancer. Calling them “mutations” performs the rhetorical work of establishing causation before it has been proven.

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The Logic Is Circular

The reasoning in the BRCA literature runs as follows: We found these variants in cancer families, so they are disease-causing mutations. Finding them in an individual means that individual will likely develop cancer. The test has predictive value because the mutations cause disease.

Each step depends on the previous step being true. But the first step—that presence in cancer families equals causation—is precisely what needs to be proven and hasn’t been.

The families were selected because they had cancer. Finding genetic commonalities within these families demonstrates only that family members share genetic markers. Since they also share environments, behaviors, and exposures, the marker could be:

• A cause of the cancer

• A passenger—inherited alongside the actual cause

• A marker of something else entirely

• An effect rather than a cause

The papers don’t distinguish between these possibilities. They assume the first and proceed accordingly.

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DNA Is Not Static

Standard genetics classifies BRCA variants as “germline” based on two observations: they appear in non-tumor tissue (like blood), and they segregate from parent to child within families. The researchers report that these variants track across generations—this is the co-segregation data they present as evidence for inheritance.

But even accepting this framework on its own terms, the observation does not settle the question of causation. It establishes inheritance of the variant. It does not establish that the variant produces the cancer.

There is a deeper complication. Within the standard model, DNA is said to change throughout life. Cells sustain tens of thousands of DNA lesions daily from normal metabolic processes, oxidative stress, and environmental exposures. Repair mechanisms fix most damage. Some changes persist.

The factors said to cause DNA damage include oxidative stress from toxicity and chronic inflammation, chemical exposures of all kinds, radiation including diagnostic imaging, chronic psychological stress (which measurably increases DNA damage markers), nutritional deficiencies (since certain nutrients are said to be required for DNA repair), and age itself—damage is said to accumulate over a lifetime.

Here is what this means for interpretation: even if a variant is inherited, additional factors are required for cancer to develop. The variant alone does not produce the disease—otherwise penetrance would approach 100%. Something else determines whether someone with the variant develops cancer or lives to 80 without incident.

That “something else” might be the actual cause. The inherited variant might be a marker of family membership—tracking alongside shared environmental exposures, dietary patterns, and toxic loads—rather than an independent causal agent.

The methodology presumes the variant drives the disease. The penetrance data suggests otherwise.

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Which Direction Does the Arrow Point?

If toxic exposures cause both DNA damage and cancer, then finding DNA variations in cancer patients tells you nothing about causation. The variation could be a consequence of the same process that produced the cancer, not its cause.

The papers treat this as a non-question. The arrow points from mutation to cancer. But consider an alternative model:

Environmental toxicity causes metabolic dysfunction. The body’s cells, under stress, accumulate DNA damage. Certain sequences are more vulnerable than others. The same toxic process that damages DNA also triggers the metabolic conditions that produce cancer.

In this model, the “mutation” and the cancer are both effects of a common cause. Finding them together demonstrates correlation, not causation. Family clustering occurs because families share environments, not because they share a broken gene.

This is a plausible working hypothesis, not a proven alternative. But it would explain the incomplete penetrance data—why 35-55% of those with the variant never develop cancer despite carrying the “causative” variant for decades. It would explain why the original researchers called for investigation of environmental modifiers. And it points toward a research direction that was structurally neglected.

The papers themselves acknowledge that something other than the mutation determines who gets cancer—otherwise, penetrance would be 100%, not 45-65%. The authors call for research into “other genetic factors or environmental factors that may ameliorate the effects of BRCA1 mutations.”

Compared to the volume of work on testing, penetrance modeling, and surgical risk reduction, that research direction has been structurally under-funded and under-translated into clinical advice. For patients, the net effect is indistinguishable from abandonment.

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Loss of Heterozygosity: Evidence or Artifact?

The standard model holds that you carry two copies of each gene—one from each parent. In BRCA families, the argument goes, carriers inherit one “defective” copy and one functional copy. The functional copy serves as a backup. Cancer develops, the theory claims, when that backup is lost.

The papers point to tumor evidence: when researchers examine breast tumors from BRCA carriers, they often find the functional copy is missing while the variant copy remains. This is called “loss of heterozygosity.” The interpretation: the backup failed, and cancer resulted. The variant copy is therefore the cause.

A note on function: the standard account holds that BRCA proteins are involved in DNA repair. Laboratory studies are cited as confirmation—knock out BRCA in mice, the argument goes, and genomic instability increases.

Within this framework, what is in dispute is whether functional involvement equals disease determinism.

If a broken backup system caused cancer, penetrance should approach 100%. A cell that cannot repair damage should accumulate problems until cancer becomes inevitable. Yet 35-55% of those with the variant never develop disease. Some live to 80 with the variant and die of something else entirely. The “broken backup” model does not explain this. Something is either compensating for the loss, or the loss is not the primary driver.

There is another problem. Cancer cells are said to have chaotic genomes—losing and gaining genetic material constantly. This instability is described as a feature of cancer itself. Finding that tumors have lost a specific piece of genetic material doesn’t tell you whether that loss caused the tumor or resulted from it.

The question is one of direction. Did losing the backup cause the cancer? Or did the cancer, once established, produce the genetic chaos in which the backup was lost?

If cancer produces instability, and certain sequences are more vulnerable to loss, then finding those sequences missing in tumors is expected as a consequence of disease—not evidence for a cause.

The papers assume the loss caused the cancer. The alternative—that cancer caused the loss—isn’t considered.

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Explaining It to a Six-Year-Old

Imagine a neighborhood where several houses catch fire over the years. A scientist comes to study why.

She notices that all the houses that burned down had red front doors. The houses that didn’t burn had blue doors. She writes a paper: “Red doors are linked to house fires.”

Soon, people start calling it the “fire door mutation.” Insurance companies charge more for red doors. Some families, terrified, rip off their red doors and replace them—even though their houses are perfectly fine.

But nobody asked the obvious question: What if all the red-door houses were on the same street—the street next to the chemical factory?

The doors didn’t cause the fires. The doors and the fires had the same cause. The families shared a street, not just a door color.

The BRCA researchers found the red doors. They noted that red doors and fires cluster together in certain families. They called the red doors “mutations” and told women to remove their doors.

They never adequately investigated the street—the shared household chemicals, the pesticides, the dietary patterns, the water supply, the occupational exposures, the stress environments that families pass down as surely as they pass down genetic markers.

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The Penetrance Problem That Disappeared

The most significant finding in the BRCA research is the one that received the least attention: incomplete penetrance.

Fifty-five to sixty-five percent of those with a BRCA1 variant and approximately forty-five percent of those with a BRCA2 variant will develop breast cancer by age 70, according to combined analyses of the research. These numbers are substantially elevated over the general population.

They also mean that 35-55% of those with the variant never develop the disease.

Compare this to what geneticists consider genuine genetic causation. Huntington’s disease, attributed to a mutation in the HTT gene, reportedly has penetrance approaching 100%. If you carry the expanded repeat, the standard account holds, you will develop the disease. There is no substantial population of Huntington’s carriers who live to old age unaffected. Within the genetic framework, the gene causes the disease in a way that BRCA demonstrably does not.

In a genetic model where the mutation causes cancer, 35-55% non-penetrance is a problem requiring explanation. What protects the substantial minority who carry the mutation but never get sick? The 1994 Miki paper explicitly called for research into modifying factors—genetic or environmental—that ameliorate the mutation’s effects.

That research direction implied that the mutation alone is insufficient. Something else determines outcomes. Identifying that something else might reveal the actual cause of the cancer—and might suggest interventions more targeted than removing healthy organs.

Some research has investigated modifiers of BRCA risk. But compared to the intensity with which the claimed gene was mapped, patented, tested, and linked to surgical protocols, investigation of what protects non-affected individuals has been marginal—and effectively absent from the story told to patients. The clinical direction was surgical.

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Angelina Jolie’s Breasts

In May 2013, Angelina Jolie published an op-ed in the New York Times announcing that she had undergone preventive double mastectomy after testing positive for a BRCA1 mutation. Her doctors had estimated her lifetime risk of breast cancer at 87%.

The essay was framed as empowerment—taking control of her health, refusing to live under a shadow. The response was overwhelmingly positive. BRCA testing referrals surged. The “Angelina Jolie effect” became a case study in celebrity health influence.

Jolie made her decision based on what she was told the science said. The science said she carried a mutation that causes breast cancer. Her doctors translated this into an 87% lifetime risk. Faced with those odds, removing the tissue at risk appeared rational.

But the science does not say what Jolie was told it says.

The 87% figure derives from the same ascertainment-biased family studies that established the gene association in the first place. Researchers studied families with extreme cancer clustering—six, eight, ten cases across generations—then used those families to calculate “risk” for anyone carrying the variant. The circularity is complete: families were selected because they had cancer, a marker was found, and the cancer rate in those families became the “risk” assigned to the marker.

Jolie’s family history was real. Her mother died of ovarian cancer. Her aunt died of breast cancer. But her family does not mirror the extreme multi-generation, high-density pedigrees used to derive the 80-87% figures. The models were built on statistical outliers. Applying those numbers to her situation required assuming the very thing that hasn’t been proven: that the variant, not the shared family environment, explains the clustering.

She is not alone. Thousands of women have made the same calculation based on the same reasoning. Many removed healthy breasts. Some removed healthy ovaries. The surgeries have consequences: chronic pain, loss of sensation, hormonal disruption, psychological effects, surgical complications.

To be clear: removing breast tissue does reduce breast cancer incidence. You cannot develop cancer in tissue that no longer exists. The question is not whether the surgery “works” in this mechanical sense. The question is whether the women who chose it were given accurate information—and whether the entire framework that produced the 87% figure rests on a causal claim the research does not support.

These women were told they carried a gene that causes cancer. The papers don’t prove that. They prove association in pre-selected families. The distance between those two claims is the distance between correlation and causation.

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The Science Confirms the Problem

The ascertainment bias we’ve described is not a fringe critique. The scientific literature acknowledges it directly.

Even the landmark 2017 JAMA study on BRCA penetrance—one of the most widely cited sources for risk figures—acknowledges that retrospective family-based studies are “prone to bias if analyses are not correctly adjusted for the ascertainment process.” The question is whether the adjustments are adequate, and whether the corrected estimates reached the women making surgical decisions.

A 2019 study in the European Journal of Human Genetics examined clinical pedigrees used for genetic testing and found pervasive, unexpected biases. Families sent for breast cancer genetic testing were enriched not only for breast cancer—as expected—but also for colorectal and endometrial cancers. The authors state plainly: “Clinically ascertained pedigrees may have unknown ascertainment biases for both patients and relatives.” Their conclusion: “Failure to assess for ascertainment bias increases the risk of false genetic associations.”

A 2007 analysis in the Journal of Medical Genetics used simulation studies to quantify the magnitude of this bias. The researchers found that risk estimates derived from clinically ascertained families are inflated by a factor of two to three. A five-fold risk estimate, run through proper bias correction, becomes a two-fold risk. The authors explicitly warned against using these inflated estimates for clinical recommendations: “We believe that it would be premature to recommend additional screening or chemoprevention for unaffected women who test negative for the BRCA mutation segregating in their family, other than that recommended for women in their age group in the general population.”

The warning was not heeded.

A 2002 study in the BMJ examined women who had already undergone prophylactic bilateral mastectomy. The findings were stark. Most women overestimated their risk of breast cancer by more than 90% compared to computer-generated risk estimates based on epidemiological data. Twenty-two of the 75 women studied believed their risk was 100%. The maximum risk assigned to anyone with a BRCA variant, according to the models, is 80%.

The most disturbing finding: the 18 women with the lowest computed risk—those with no or very limited family history of breast cancer—believed they were at the highest risk. On average, these women estimated their risk at 80%. Their computed risk, according to the models, was approximately 12%.

These women removed healthy breasts because they believed they faced near-certain cancer. Their belief was wrong by a factor of seven. The machinery that produced this belief—the testing, the counseling, the risk communication—failed them catastrophically.

The only women in the study who estimated their risk with any accuracy were those who tested positive for a BRCA variant and had received genetic counseling. Even then, their estimates were inflated. Everyone else was operating on fear, not data.

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Following the Money

The original BRCA papers include conflict of interest disclosures. Researchers are listed as holding patents on BRCA gene sequences and diagnostic methods. One author reports receiving royalties from a patent on the BRCA2 gene.

This was not incidental. The race to identify BRCA genes was explicitly a race to patent them. Myriad Genetics won. From the mid-1990s until 2013, they held exclusive patents on BRCA testing in the United States, charging approximately $3,000-4,000 per test. For nearly two decades, anyone who wanted to know their “BRCA status” had to pay Myriad. The company’s annual revenues from BRCA testing alone exceeded $500 million at their peak.

The test’s value depends entirely on the proposition that detecting the variant provides actionable medical information—that those who test positive face substantially elevated risk and should consider preventive measures. A test for a variant with unclear clinical significance has no market. A test for a “cancer-causing mutation” is worth billions.

But testing is only the first link in the revenue chain.

A positive test triggers genetic counseling—a profession that exists largely because of this narrative. Counseling leads to surveillance: annual MRIs, mammograms every six months, clinical breast exams, blood tests for ovarian cancer markers. Surveillance continues indefinitely, or until the woman opts for surgery.

Prophylactic bilateral mastectomy costs $15,000-50,000 or more, depending on the facility and whether reconstruction is included. Reconstruction—implants or tissue flap procedures—adds tens of thousands more and often requires multiple surgeries over years. Oophorectomy (ovary removal) is frequently recommended as well, with its own costs and consequences.

For those who develop cancer despite surveillance, or who are diagnosed with cancer and then tested, a new revenue stream emerged: PARP inhibitors. These drugs—olaparib (Lynparza), rucaparib, others—are marketed specifically for “BRCA-positive” cancers. They cost $10,000-15,000 per month. Global sales exceeded $2 billion annually by the early 2020s. The drugs’ market depends entirely on the concept of BRCA-driven cancer being a distinct biological entity requiring targeted treatment.

Every link in this chain—testing, counseling, surveillance, surgery, reconstruction, drugs—generates revenue. Every link depends on the foundational claim that BRCA variants cause cancer in a way that justifies intervention. Remove that claim, and the entire edifice loses its rationale.

This creates structural incentives against questioning the foundation.

Consider research funding. Who pays for studies on genetic risk? Often, the companies that profit from risk being high. Who pays for studies on environmental modifiers—the factors that might explain why most people with the variant never get cancer? No one with a financial interest, because you cannot patent advice to reduce toxic exposures, change dietary patterns, or address metabolic dysfunction. The research that might reveal the variant as a marker rather than a cause goes unfunded, while the research that reinforces the causal narrative attracts investment.

The Supreme Court eventually invalidated Myriad’s gene patents in 2013, ruling that naturally occurring DNA sequences cannot be patented. Testing prices dropped. Competition entered the market. But the ruling came too late to change the trajectory. By then, the BRCA narrative was institutionalized: embedded in clinical guidelines, insurance coverage policies, medical school curricula, surgical training programs, and public consciousness. The gene causes cancer. The test tells you if you have it. The surgeries prevent the cancer you would otherwise get.

Each link reinforces the others. Surgeons trained in prophylactic mastectomy need patients. Genetic counselors need a narrative that justifies their role. Testing companies need the test to mean something actionable. Drug companies need BRCA-positive cancer to exist as a category. Guidelines committees, often populated by researchers with industry ties, codify the standard of care. Insurance companies, following the guidelines, cover the interventions. The system perpetuates itself.

None of this requires conspiracy. It requires only that financial incentives align in a particular direction, and that no one with resources has reason to fund the questions that might disrupt the alignment. The result is a self-reinforcing loop that looks like scientific consensus but functions as market protection.

The claim that was never proven—that BRCA variants cause cancer—became the foundation for an industry worth billions annually. The women making decisions about their bodies were not told about the circular reasoning, the ascertainment bias, the inflated risk figures, or the financial interests behind the narrative they received.

They were told the science was settled.

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The Lesson

The BRCA story is a case study in how correlation becomes causation becomes settled science becomes surgery.

The papers establish that certain DNA sequence variations are more common in families with unusual breast cancer clustering. This is association within a pre-selected group. The papers do not establish that these variations cause cancer in the general population. They do not explain why 35-55% of those with the variant never develop disease. They do not rule out environmental confounding in families that share exposures as well as genetic markers. They do not address whether DNA variations found in middle-aged individuals were present at birth or acquired through decades of living. They do not consider whether the variations might be effects rather than causes.

Each of these gaps matters. Together, they constitute a chasm between what the research shows and what the public was told.

The word “mutation” did much of the rhetorical work. Calling a sequence variation a mutation implies it is broken, pathological, causative. The implication became the conclusion. The circular logic was obscured by technical language and statistical significance.

The capture was structural. Patents on testing and treatment created financial interests in maintaining the causation narrative. Research into environmental factors and incomplete penetrance—the questions that might have revealed the variant as marker rather than cause—went unfunded. The surgical solution, which generates revenue, displaced investigation into what actually protects those who test positive but never develop disease.

And women, told they carry a gene that causes cancer, made irreversible decisions about their bodies based on a claim the research does not support.

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Reading Gene-Disease Claims

The BRCA story offers a template for evaluating any claim that a gene causes a disease.

Ask how the study population was selected. If families were chosen because they had disease clustering, the findings apply to that unusual population, not the general public.

Ask what the penetrance is. If a substantial percentage of those with the variant never develop the disease, the claimed gene is not sufficient to cause it. Something else matters—and that something else might be the actual cause.

Ask whether the researchers distinguished correlation from causation. Association in affected families is not proof that the gene produces the disease.

Ask what the word “mutation” is doing. Is it describing an observation (sequence differs from reference) or smuggling in a conclusion (the difference causes pathology)?

Ask who funded the research and who profits from the findings. Not because financial interest automatically invalidates results, but because it shapes which questions get asked.

Ask what happened to the alternative hypotheses. Were environmental factors investigated? Was the possibility that DNA changes are effects rather than causes considered?

The answers to these questions, applied to BRCA, reveal a story very different from the one that reached the public.

A marker was found that tracks with cancer in unusual families. The tracking was called causation. The causation justified testing. The testing justified surgery. The surgery removed healthy organs from women who might never have developed cancer—and who, even if they had, might have been protected by interventions less radical than amputation.

The women who made these decisions were not irrational. They were misinformed. They were told the science said something it does not say. They trusted institutions that had financial and ideological reasons to overstate the evidence.

They deserved better.

The question that should have been asked from the beginning—why do some people with the variant get cancer while others don’t?—remains unanswered. That question points toward the actual cause. The answer might involve environmental factors that cluster in families alongside genetic markers. It might involve metabolic conditions that precede and enable cancer. It might reveal the “mutation” as a marker of toxic damage rather than an inherited destiny.

We don’t know, because the research took a different path. It followed the gene, the test, and the knife.

The women who lost their breasts to this hypothesis are owed an accounting. So are the ones being counseled right now, today, to do the same.

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References

1. Hall JM, Lee MK, Newman B, et al. Linkage of early-onset familial breast cancer to chromosome 17q21. Science. 1990;250(4988):1684-1689.

2. Miki Y, Swensen J, Shattuck-Eidens D, et al. A strong candidate for the breast and ovarian cancer susceptibility gene BRCA1. Science. 1994;266(5182):66-71.

3. Wooster R, Neuhausen SL, Mangion J, et al. Localization of a breast cancer susceptibility gene, BRCA2, to chromosome 13q12-13. Science. 1994;265(5181):2088-2090.

4. Wooster R, Bignell G, Lancaster J, et al. Identification of the breast cancer susceptibility gene BRCA2. Nature. 1995;378(6559):789-792.

5. Rebbeck TR, Mitra N, Wan F, et al. Association of type and location of BRCA1 and BRCA2 mutations with risk of breast and ovarian cancer. JAMA. 2015;313(13):1347-1361.

6. Antoniou A, Pharoah PD, Narod S, et al. Average risks of breast and ovarian cancer associated with BRCA1 or BRCA2 mutations detected in case series unselected for family history: a combined analysis of 22 studies. Am J Hum Genet. 2003;72(5):1117-1130.

7. Kuchenbaecker KB, Hopper JL, Barnes DR, et al. Risks of breast, ovarian, and contralateral breast cancer for BRCA1 and BRCA2 mutation carriers. JAMA. 2017;317(23):2402-2416.

8. Ivanov VN, Ivanova SV, Shcheglov VS. BRCA1 and BRCA2 mutations and treatment perspectives. Journal of Cancer. 2019;10(10):2109-2127.

9. Jolie A. My medical choice. New York Times. May 14, 2013.

10. Association for Molecular Pathology v. Myriad Genetics, Inc., 569 U.S. 576 (2013).

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13. Thompson D, Easton D; Breast Cancer Linkage Consortium. Variation in BRCA1 cancer risks by mutation position. Cancer Epidemiol Biomarkers Prev. 2002;11(4):329-336.

14. Ranola JMO, Tsai GJ, Shirts BH. Exploring the effect of ascertainment bias on genetic studies that use clinical pedigrees. Eur J Hum Genet. 2019;27(12):1800-1807.

15. Goldgar D, Venne V, Conner T, Buys S. BRCA phenocopies or ascertainment bias? J Med Genet. 2007;44(8):e86.

16. Metcalfe K, et al. Women who undergo prophylactic bilateral mastectomy overstate risk of cancer. BMJ. 2002;325(7369):921.

17. Langbehn DR, Brinkman RR, Falush D, Paulsen JS, Hayden MR. A new model for prediction of the age of onset and penetrance for Huntington’s disease based on CAG length. Clin Genet. 2004;65(4):267-277.

18. Pal T, Mundt E, Richardson ME, et al. Reduced penetrance BRCA1 and BRCA2 pathogenic variants in clinical germline genetic testing. NPJ Precis Oncol. 2024;8:247.

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