Should Genetic Information About Mental Health Affect Civil Court Cases?
Imagine this scenario: A couple is involved in a heated custody dispute over their only child. As part of the effort to make the case of being a better guardian, one parent goes on a "genetic fishing expedition": this parent obtains a DNA sample from the other parent with the hope that such data will identify some genetic predisposition to a psychiatric condition (e.g., schizophrenia) and tilt the judge's custody decision in his or her favor.
As knowledge of psychiatric genetics is growing, it is likely to be introduced in civil cases, such as child custody disputes and education-related cases, raising a tangle of ethical and legal questions.
This is an example of how "behavioral genetic evidence" -- an umbrella term for information gathered from family history and genetic testing about pathological behaviors, including psychiatric conditions—may in the future be brought by litigants in court proceedings. Such evidence has been discussed primarily when criminal defendants sought to introduce it to make the claim that they are not responsible for their behavior or to justify their request for reduced sentencing and more lenient punishment.
However, civil cases are an emerging frontier for behavioral genetic evidence. It has already been introduced in tort litigation, such as personal injury claims, and as knowledge of psychiatric genetics is growing, it is further likely to be introduced in other civil cases, such as child custody disputes and education-related cases. But the introduction of such evidence raises a tangle of ethical and legal questions that civil courts will need to address. For example: how should such data be obtained? Who should get to present it and under what circumstances? And does the use of such evidence fit with the purposes of administering justice?
How Did We Get Here?
That behavioral genetic evidence is entering courts is unsurprising. Scientific evidence is a common feature of judicial proceedings, and genetic information may reveal relevant findings. For example, genetic evidence may elucidate whether a child's medical condition is due to genetic causes or medical malpractice, and it has been routinely used to identify alleged offenders or putative fathers. But behavioral genetic evidence is different from such other genetic data – it is shades of gray, instead of black and white.
Although efforts to understand the nature and origins of human behavior are ongoing, existing and likely future knowledge about behavioral genetics is limited. Behavioral disorders are highly complex and diverse. They commonly involve not one but multiple genes, each with a relatively small effect. They are impacted by many, yet unknown, interactions between genes, familial, and environmental factors such as poverty and childhood adversity.
And a specific gene variant may be associated with more than one behavioral disorder and be manifested with significantly different symptoms. Thus, biomarkers about "predispositions" for behavioral disorders cannot generally provide a diagnosis or an accurate estimate of whether, when, and at what severity a behavioral disorder will occur. And, unlike genetic testing that can confirm litigants' identity with 99.99% probability, behavioral genetic evidence is far more speculative.
Genetic theft raises questions about whose behavioral data are being obtained, by whom, and with what authority.
Whether judges, jurors, and other experts understand the nuances of behavioral genetics is unclear. Many people over-estimate the deterministic nature of genetics, and under-estimate the role of environments, especially with regards to mental health status. The U.S. individualistic culture of self-reliance and independence may further tilt the judicial scales because litigants in civil courts may be unjustly blamed for their "bad genes" while structural and societal determinants that lead to poor behavioral outcomes are ignored.
These concerns were recently captured in the Netflix series "13 Reasons Why," depicting a negligence lawsuit against a school brought by parents of a high-school student there (Hannah) who committed suicide. The legal tides shifted from the school's negligence in tolerating a culture of bullying to parental responsibility once cross-examination of Hannah's mother revealed a family history of anxiety, and the possibility that Hannah had a predisposition for mental illness, which (arguably) required therapy even in the absence of clear symptoms.
Where Is This Going?
The concerns are exacerbated given the ways in which behavioral genetic evidence may come to court in the future. One way is through "genetic theft," where genetic evidence is obtained from deserted property, such as soft-drink cans. This method is often used for identification purposes such as criminal and paternity proceedings, and it will likely expand to behavioral genetic data once available through "home kits" that are offered by direct-to-consumer companies.
Genetic theft raises questions about whose behavioral data are being obtained, by whom, and with what authority. In the scenario of child-custody dispute, for example, the sequencing of the other parent's DNA will necessarily intrude on the privacy of that parent, even as the scientific value of such information is limited. A parent on a "genetic fishing expedition" can also secretly sequence their child for psychiatric genetic predispositions, arguably, in order to take preventative measures to reduce the child's risk for developing a behavioral disorder. But should a parent be allowed to sequence the child without the other parent's consent, or regardless of whether the results will provide medical benefits to the child?
Similarly, although schools are required, and may be held accountable for failing to identify children with behavioral disabilities and to evaluate their educational needs, some parents may decline their child's evaluation by mental health professionals. Should schools secretly obtain a sample and sequence children for behavioral disorders, regardless of parental consent? My study of parents found that the overwhelming majority opposed imposed genetic testing by school authorities. But should parental preference or the child's best interests be the determinative factor? Alternatively, could schools use secretly obtained genetic data as a defense that they are fulfilling the child-find requirement under the law?
The stigma associated with behavioral disorders may intimidate some people enough that they back down from just claims.
In general, samples obtained through genetic theft may not meet the legal requirements for admissible evidence, and as these examples suggest, they also involve privacy infringement that may be unjustified in civil litigation. But their introduction in courts may influence judicial proceedings. It is hard to disregard such evidence even if decision-makers are told to ignore it.
The costs associated with genetic testing may further intensify power differences among litigants. Because not everyone can pay for DNA sequencing, there is a risk that those with more resources will be "better off" in court proceedings. Simultaneously, the stigma associated with behavioral disorders may intimidate some people enough that they back down from just claims. For example, a good parent may give up a custody claim to avoid disclosure of his or her genetic predispositions for psychiatric conditions. Regulating this area of law is necessary to prevent misuses of scientific technologies and to ensure that powerful actors do not have an unfair advantage over weaker litigants.
Behavioral genetic evidence may also enter the courts through subpoena of data obtained in clinical, research or other commercial genomic settings such as ancestry testing (similar to the genealogy database recently used to identify the Golden State Killer). Although court orders to testify or present evidence are common, their use for obtaining behavioral genetic evidence raises concerns.
One worry is that it may be over-intrusive. Because behavioral genetics are heritable, such data may reveal information not only about the individual litigant but also about other family members who may subsequently be stigmatized as well. And, even if we assume that many people may be willing for their data in genomic databases to be used to identify relatives who committed crimes (e.g., a rapist or a murderer), we can't assume the same for civil litigation, where the public interest in disclosure is far weaker.
Another worry is that it may deter people from participating in activities that society has an interest in advancing, including medical treatment involving genetic testing and genomic research. To address this concern, existing policy provides expanded privacy protections for NIH-funded genomic research by automatically issuing a Certificate of Confidentiality that prohibits disclosure of identifiable information in any Federal, State, or local civil, criminal, and other legal proceedings.
But this policy has limitations. It applies only to specific research settings and does not cover non-NIH funded research or clinical testing. The Certificate's protections can also be waived under certain circumstances. People who volunteer to participate in non-NIH-funded genomic research for the public good may thus find themselves worse-off if embroiled in legal proceedings.
Consider the following: if a parent in a child custody dispute had participated in a genetic study on schizophrenia years earlier, should the genetic results be subpoenaed by the court – and weaponized by the other parent? Public policy should aim to reduce the risks for such individuals. The end of obtaining behavioral genetic evidence cannot, and should not, always justify the means.
A new type of cancer therapy is shrinking deadly brain tumors with just one treatment
Few cancers are deadlier than glioblastomas—aggressive and lethal tumors that originate in the brain or spinal cord. Five years after diagnosis, less than five percent of glioblastoma patients are still alive—and more often, glioblastoma patients live just 14 months on average after receiving a diagnosis.
But an ongoing clinical trial at Mass General Cancer Center is giving new hope to glioblastoma patients and their families. The trial, called INCIPIENT, is meant to evaluate the effects of a special type of immune cell, called CAR-T cells, on patients with recurrent glioblastoma.
How CAR-T cell therapy works
CAR-T cell therapy is a type of cancer treatment called immunotherapy, where doctors modify a patient’s own immune system specifically to find and destroy cancer cells. In CAR-T cell therapy, doctors extract the patient’s T-cells, which are immune system cells that help fight off disease—particularly cancer. These T-cells are harvested from the patient and then genetically modified in a lab to produce proteins on their surface called chimeric antigen receptors (thus becoming CAR-T cells), which makes them able to bind to a specific protein on the patient’s cancer cells. Once modified, these CAR-T cells are grown in the lab for several weeks so that they can multiply into an army of millions. When enough cells have been grown, these super-charged T-cells are infused back into the patient where they can then seek out cancer cells, bind to them, and destroy them. CAR-T cell therapies have been approved by the US Food and Drug Administration (FDA) to treat certain types of lymphomas and leukemias, as well as multiple myeloma, but haven’t been approved to treat glioblastomas—yet.
CAR-T cell therapies don’t always work against solid tumors, such as glioblastomas. Because solid tumors contain different kinds of cancer cells, some cells can evade the immune system’s detection even after CAR-T cell therapy, according to a press release from Massachusetts General Hospital. For the INCIPIENT trial, researchers modified the CAR-T cells even further in hopes of making them more effective against solid tumors. These second-generation CAR-T cells (called CARv3-TEAM-E T cells) contain special antibodies that attack EFGR, a protein expressed in the majority of glioblastoma tumors. Unlike other CAR-T cell therapies, these particular CAR-T cells were designed to be directly injected into the patient’s brain.
The INCIPIENT trial results
The INCIPIENT trial involved three patients who were enrolled in the study between March and July 2023. All three patients—a 72-year-old man, a 74-year-old man, and a 57-year-old woman—were treated with chemo and radiation and enrolled in the trial with CAR-T cells after their glioblastoma tumors came back.
The results, which were published earlier this year in the New England Journal of Medicine (NEJM), were called “rapid” and “dramatic” by doctors involved in the trial. After just a single infusion of the CAR-T cells, each patient experienced a significant reduction in their tumor sizes. Just two days after receiving the infusion, the glioblastoma tumor of the 72-year-old man decreased by nearly twenty percent. Just two months later the tumor had shrunk by an astonishing 60 percent, and the change was maintained for more than six months. The most dramatic result was in the 57-year-old female patient, whose tumor shrank nearly completely after just one infusion of the CAR-T cells.
The results of the INCIPIENT trial were unexpected and astonishing—but unfortunately, they were also temporary. For all three patients, the tumors eventually began to grow back regardless of the CAR-T cell infusions. According to the press release from MGH, the medical team is now considering treating each patient with multiple infusions or prefacing each treatment with chemotherapy to prolong the response.
While there is still “more to do,” says co-author of the study neuro-oncologist Dr. Elizabeth Gerstner, the results are still promising. If nothing else, these second-generation CAR-T cell infusions may someday be able to give patients more time than traditional treatments would allow.
“These results are exciting but they are also just the beginning,” says Dr. Marcela Maus, a doctor and professor of medicine at Mass General who was involved in the clinical trial. “They tell us that we are on the right track in pursuing a therapy that has the potential to change the outlook for this intractable disease.”
Since the early 2000s, AI systems have eliminated more than 1.7 million jobs, and that number will only increase as AI improves. Some research estimates that by 2025, AI will eliminate more than 85 million jobs.
But for all the talk about job security, AI is also proving to be a powerful tool in healthcare—specifically, cancer detection. One recently published study has shown that, remarkably, artificial intelligence was able to detect 20 percent more cancers in imaging scans than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.