SCOOP: Largest Cryobank in the U.S. to Offer Ancestry Testing
Sharon Kochlany and Vanessa Colimorio's four-year-old twin girls had a classic school assignment recently: make a family tree. They drew themselves and their one-year-old brother branching off from their moms, with aunts, uncles, and grandparents forking off to the sides.
The recently-gained sovereignty of queer families stands to be lost if a consumer DNA test brings a stranger's identity out of the woodwork.
What you don't see in the invisible space between Kochlany and Colimorio, however, is the sperm donor they used to conceive all three children.
To look at a family tree like this is to see in its purest form that kinship can supersede biology—the boundaries of where this family starts and stops are clear to everyone in it, in spite of a third party's genetic involvement. This kind of self-definition has always been synonymous with LGBTQ families, especially those that rely on donor gametes (sperm or eggs) to exist.
But the world around them has changed quite suddenly: The recent consumer DNA testing boom has made it more complicated than ever for families built through reproductive technology—openly, not secretively—to maintain the strong sense of autonomy and privacy that can be crucial for their emotional security. Prospective parents and cryobanks are now mulling how best to bring a new generation of donor-conceived people into this world in a way that leaves open the choice to know more about their ancestry without obliterating an equally important choice: the right not to know about biological relatives.
For queer parents who have long fought for social acceptance, having a biological relationship to their children has been revolutionary, and using an unknown donor as a means to this end especially so. Getting help from a friend often comes with the expectation that the friend will also have social involvement in the family, which some people are comfortable with, but being able to access sperm from an unknown donor—which queer parents have only been able to openly do since the early 1980s—grants them the reproductive autonomy to create families seemingly on their own. That recently-gained sovereignty stands to be lost if a consumer DNA test brings a stranger's identity out of the woodwork.
At the same time, it's natural for donor-conceived people to want to know more about where they come from ethnically, even if they don't want to know the identity of their donor. As a donor-conceived person myself, I know my donor's self-reported ethnicity, but have often wondered how accurate it is.
Opening the Pandora's box of a consumer DNA test as a way to find out has always felt profoundly unappealing to me, however. Many people have accidentally learned they're donor-conceived by unwittingly using these tools, but I already know that about myself going in, and subsequently know I'll be connected to a large web of people whose existence I'm not interested in learning about. In addition to possibly identifying my anonymous donor, his family could also show up, along with any donor-siblings—other people with whom I share a donor. My single lesbian mom is enough for me, and the trade off to learn more about my ethnic ancestry has never seemed worth it.
In 1992, when I was born, no one was planning for how consumer DNA tests might upend or illuminate one's sense of self. But the donor community has always had to stay nimble with balancing privacy concerns and psychological well-being, so it should come as no surprise that figuring out how to do so in 2020 includes finding a way to offer ancestry insight while circumventing consumer DNA tests.
A New Paradigm
This is the rationale behind unprecedented industry news that LeapsMag can exclusively break: Within the next few weeks, California Cryobank, the largest cryobank in the country, will begin offering genetically-verified ancestry information on the free public part of every donor's anonymous profile in its database, something no other cryobanks yet offer (an exact launch date was not available at the time of publication). Currently, California Cryobank's donor profiles include a short self-reported list that might merely say, "Ancestry: German, Lebanese, Scottish."
The new information will be a report in pie chart form that details exactly what percentages of a donor's DNA come from up to 26 ethnicities—it's analogous to, but on a smaller scale than, the format offered by consumer DNA testing companies, and uses the same base technology that looks for single nucleotide polymorphisms in DNA that are associated with specific ethnicities. But crucially, because the donor takes the DNA test through California Cryobank, not a consumer-facing service, the information is not connected in a network to anyone else's DNA test. It's also taken before any offspring exist so there's no chance of revealing a donor-conceived person's identity this way.
Later, when a donor-conceived person is born, grows up, and wants information about their ethnicity from the donor side, all they need is their donor's anonymous ID number to look it up. The donor-conceived person never takes a genetic test, and therefore also can't accidentally find donor siblings this way. People who want to be connected to donor siblings can use a sibling registry where other people who want to be found share donor ID numbers and look for matches (this is something that's been available for decades, and remains so).
"With genetic testing, you have no control over who reaches out to you, and at what point in your life."
California Cryobank will require all new donors to consent to this extra level of genetic testing, setting a new standard for what information prospective parents and donor-conceived people can expect to have. In the immediate, this information will be most useful for prospective parents looking for donors with specific backgrounds, possibly ones similar to their own.
It's a solution that was actually hiding in plain sight. Two years ago, California Cryobank's partner Sema4, the company handling the genetic carrier testing that's used to screen for heritable diseases, started analyzing ethnic data in its samples. That extra information was being collected because it can help calculate a more accurate assessment of genetic risks that run in certain populations—like Ashkenazi Jews and Tay Sachs disease—than relying on oral family histories. Shortly after a plan to start collecting these extra data, Jamie Shamonki, chief medical officer of California Cryobank, realized the companies would be sitting on a goldmine for a different reason.
"I didn't want to use one of these genetic testing companies like Ancestry to accomplish this," says Shamonki. "The whole thing we're trying to accomplish is also privacy."
Consumer-facing DNA testing companies are not HIPAA compliant (whereas Sema4, which isn't direct-to-consumer, is HIPAA compliant), which means there are no legal privacy protections covering people who add their DNA to these databases. Although some companies, like 23andMe, allow users to opt-out of being connected with genetic relatives, the language can be confusing to navigate, requires a high level of knowledge and self-advocacy on the user's part, and, as an opt-out system, is not set up to protect the user from unwanted information by default; many unwittingly walk right into such information as a result.
Additionally, because consumer-facing DNA testing companies operate outside the legal purview that applies to other health care entities, like hospitals, even a person who does opt-out of being linked to genetic relatives is not protected in perpetuity from being re-identified in the future by a change in company policy. The safest option for people with privacy concerns is to stay out of these databases altogether.
For California Cryobank, the new information about donor heritage won't retroactively be added to older profiles in the system, so donor-conceived people who already exist won't benefit from the ancestry tool, but it'll be the new standard going forward. The company has about 500 available donors right now, many of which have been in their registry for a while; about 100 of those donors, all new, will have this ancestry data on their profiles.
Shamonki says it has taken about two years to get to the point of publicly including ancestry information on a donor's profile because it takes about nine months of medical and psychological screening for a donor to go from walking through the door to being added to their registry. The company wanted to wait to launch until it could offer this information for a significant number of donors. As more new donors come online under the new protocol, the number with ancestry information on their profiles will go up.
For Parents: An Unexpected Complication
While this change will no doubt be welcome progress for LGBTQ families contemplating parenthood, it'll never be possible to put this entire new order back in the box. What are such families who already have donor-conceived children losing in today's world of widespread consumer genetic testing?
Kochlany and Colimorio's twins aren't themselves much older than the moment at-home DNA testing really started to take off. They were born in 2015, and two years later the industry saw its most significant spike. By now, more than 26 million people's DNA is in databases like 23andMe and Ancestry; as a result, it's estimated that within a year, 90 percent of Americans of European descent will be identifiable through these consumer databases, by way of genetic third cousins, even if they didn't want to be found and never took the test themselves. This was the principle behind solving the Golden State Killer cold case.
The waning of privacy through consumer DNA testing fundamentally clashes with the priorities of the cyrobank industry, which has long sought to protect the privacy of donor-conceived people, even as open identification became standard. Since the 1980s, donors have been able to allow their identity to be released to any offspring who is at least 18 and wants the information. Lesbian moms pushed for this option early on so their children—who would obviously know they couldn't possibly be the biological product of both parents—would never feel cut off from the chance to know more about themselves. But importantly, the openness is not a two-way street: the donors can't ever ask for the identities of their offspring. It's the latter that consumer DNA testing really puts at stake.
"23andMe basically created the possibility that there will be donors who will have contact with their donor-conceived children, and that's not something that I think the donor community is comfortable with," says I. Glenn Cohen, director of Harvard Law School's Center for Health Law Policy, Biotechnology & Bioethics. "That's about the donor's autonomy, not the rearing parents' autonomy, or the donor-conceived child's autonomy."
Kochlany and Colimorio have an open identification donor and fully support their children reaching out to California Cryobank to get more information about him if they want to when they're 18, but having a singular name revealed isn't the same thing as having contact, nor is it the same thing as revealing a web of dozens of extended genetic relations. Their concern now is that if their kids participate in genetic testing, a stranger—someone they're careful to refer to as only "the donor" and never "dad"—will reach out to the children to begin some kind of relationship. They know other people who are contemplating giving their children DNA tests, and feel staunchly that it wouldn't be right for their family.
"With genetic testing, you have no control over who reaches out to you, and at what point in your life," Kochlany says. "[People] reaching out and trying to say, 'Hey I know who your dad is' throws a curveball. It's like, 'Wait, I never thought I had a dad.' It might put insecurities in their minds."
"We want them to have the opportunity to choose whether or not they want to reach out," Colimorio adds.
Kochlany says that when their twins are old enough to start asking questions, she and Colimorio plan to frame it like this: "The donor was kind of like a technology that helped us make you a person, and make sure that you exist," she says, role playing a conversation with their kids. "But it's not necessarily that you're looking to this person [for] support or love, or because you're missing a piece."
It's a line in the sand that's present even for couples still far off from conceiving. When Mallory Schwartz, a film and TV producer in Los Angeles, and Lauren Pietra, a marriage and family therapy associate (and Shamonki's step-daughter), talk about getting married someday, it's a package deal with talking about how they'll approach having kids. They feel there are too many variables and choices to make around family planning as a same-sex couple these days to not have those conversations simultaneously. Consumer DNA databases are already on their minds.
"It frustrates me that the DNA databases are just totally unregulated," says Schwartz. "I hope they are by the time we do this. I think everyone deserves a right to privacy when making your family [using a sperm donor]."
"I wouldn't want to create a world where people who are donor-conceived feel like they can't participate in this technology because they're trying to shut out [other] information."
On the prospect of having a donor relation pop up non-consensually for a future child, Pietra says, "I don't like it. It would be really disappointing if the child didn't want [contact], and unfortunately they're on the receiving end."
You can see how important preserving the right to keep this door closed is when you look at what's going on at The Sperm Bank of California. This pioneering cryobank was the first in the world to openly serve LGBTQ people and single women, and also the first to offer the open identification option when it opened in 1982, but not as many people are asking for their donor's identity as expected.
"We're finding a third of young people are coming forward for their donor's identity," says Alice Ruby, executive director. "We thought it would be a higher number." Viewed the other way, two-thirds of the donor-conceived people who could ethically get their donor's identity through The Sperm Bank of California are not asking the cryobank for it.
Ruby says that part of what historically made an open identification program appealing, rather than invasive or nerve-wracking, is how rigidly it's always been formatted around mutual consent, and protects against surprises for all parties. Those [donor-conceived people] who wanted more information were never barred from it, while those who wanted to remain in the dark could. No one group's wish eclipsed the other's. The potential breakdown of a system built around consent, expectations, and respect for privacy is why unregulated consumer DNA testing is most concerning to her as a path for connecting with genetic relatives.
For the last few decades in cryobanks around the world, the largest cohort of people seeking out donor sperm has been lesbian couples, followed by single women. For infertile heterosexual couples, the smallest client demographic, Ruby says donor sperm offers a solution to a medical problem, but in contrast, it historically "provided the ability for [lesbian] couples and single moms to have some reproductive autonomy." Yes, it was still a solution to a biological problem, but it was also a solution to a social one.
The Sperm Bank of California updated its registration forms to include language urging parents, donor-conceived people, and donors not to use consumer DNA tests, and to go through the cryobank if they, understandably, want to learn more about who they're connected to. But truthfully, there's not much else cryobanks can do to protect clients on any side of the donor transaction from surprise contact right now—especially not from relatives of the donor who may not even know someone in their family has donated sperm.
A Tricky Position
Personally, I've known I was donor-conceived from day one. It has never been a source of confusion, angst, or curiosity, and in fact has never loomed particularly large for me in any way. I see it merely as a type of reproductive technology—on par with in vitro fertilization—that enabled me to exist, and, now that I do exist, is irrelevant. Being confronted with my donor's identity or any donor siblings would make this fact of my conception bigger than I need it to be, as an adult with a full-blown identity derived from all of my other life experiences. But I still wonder about the minutiae of my ethnicity in much the same way as anyone else who wonders, and feel there's no safe way for me to find out without relinquishing some of my existential independence.
The author and her mom in spring of 1998.
"People obviously want to participate in 23andMe and Ancestry because they're interested in knowing more about themselves," says Shamonki. "I wouldn't want to create a world where people who are donor-conceived feel like they can't participate in this technology because they're trying to shut out [other] information."
After all, it was the allure of that exact conceit—knowing more about oneself—that seemed to magnetically draw in millions of people to these tools in the first place. It's an experience that clearly taps into a population-wide psychic need, even—perhaps especially—if one's origins are a mystery.
Researchers probe extreme gene therapy for severe alcoholism
Story by Freethink
A single shot — a gene therapy injected into the brain — dramatically reduced alcohol consumption in monkeys that previously drank heavily. If the therapy is safe and effective in people, it might one day be a permanent treatment for alcoholism for people with no other options.
The challenge: Alcohol use disorder (AUD) means a person has trouble controlling their alcohol consumption, even when it is negatively affecting their life, job, or health.
In the U.S., more than 10 percent of people over the age of 12 are estimated to have AUD, and while medications, counseling, or sheer willpower can help some stop drinking, staying sober can be a huge struggle — an estimated 40-60 percent of people relapse at least once.
A team of U.S. researchers suspected that an in-development gene therapy for Parkinson’s disease might work as a dopamine-replenishing treatment for alcoholism, too.
According to the CDC, more than 140,000 Americans are dying each year from alcohol-related causes, and the rate of deaths has been rising for years, especially during the pandemic.
The idea: For occasional drinkers, alcohol causes the brain to release more dopamine, a chemical that makes you feel good. Chronic alcohol use, however, causes the brain to produce, and process, less dopamine, and this persistent dopamine deficit has been linked to alcohol relapse.
There is currently no way to reverse the changes in the brain brought about by AUD, but a team of U.S. researchers suspected that an in-development gene therapy for Parkinson’s disease might work as a dopamine-replenishing treatment for alcoholism, too.
To find out, they tested it in heavy-drinking monkeys — and the animals’ alcohol consumption dropped by 90% over the course of a year.
How it works: The treatment centers on the protein GDNF (“glial cell line-derived neurotrophic factor”), which supports the survival of certain neurons, including ones linked to dopamine.
For the new study, a harmless virus was used to deliver the gene that codes for GDNF into the brains of four monkeys that, when they had the option, drank heavily — the amount of ethanol-infused water they consumed would be equivalent to a person having nine drinks per day.
“We targeted the cell bodies that produce dopamine with this gene to increase dopamine synthesis, thereby replenishing or restoring what chronic drinking has taken away,” said co-lead researcher Kathleen Grant.
To serve as controls, another four heavy-drinking monkeys underwent the same procedure, but with a saline solution delivered instead of the gene therapy.
The results: All of the monkeys had their access to alcohol removed for two months following the surgery. When it was then reintroduced for four weeks, the heavy drinkers consumed 50 percent less compared to the control group.
When the researchers examined the monkeys’ brains at the end of the study, they were able to confirm that dopamine levels had been replenished in the treated animals, but remained low in the controls.
The researchers then took the alcohol away for another four weeks, before giving it back for four. They repeated this cycle for a year, and by the end of it, the treated monkeys’ consumption had fallen by more than 90 percent compared to the controls.
“Drinking went down to almost zero,” said Grant. “For months on end, these animals would choose to drink water and just avoid drinking alcohol altogether. They decreased their drinking to the point that it was so low we didn’t record a blood-alcohol level.”
When the researchers examined the monkeys’ brains at the end of the study, they were able to confirm that dopamine levels had been replenished in the treated animals, but remained low in the controls.
Looking ahead: Dopamine is involved in a lot more than addiction, so more research is needed to not only see if the results translate to people but whether the gene therapy leads to any unwanted changes to mood or behavior.
Because the therapy requires invasive brain surgery and is likely irreversible, it’s unlikely to ever become a common treatment for alcoholism — but it could one day be the only thing standing between people with severe AUD and death.
“[The treatment] would be most appropriate for people who have already shown that all our normal therapeutic approaches do not work for them,” said Grant. “They are likely to create severe harm or kill themselves or others due to their drinking.”
This article originally appeared on Freethink, home of the brightest minds and biggest ideas of all time.
Massive benefits of AI come with environmental and human costs. Can AI itself be part of the solution?
The recent explosion of generative artificial intelligence tools like ChatGPT and Dall-E enabled anyone with internet access to harness AI’s power for enhanced productivity, creativity, and problem-solving. With their ever-improving capabilities and expanding user base, these tools proved useful across disciplines, from the creative to the scientific.
But beneath the technological wonders of human-like conversation and creative expression lies a dirty secret—an alarming environmental and human cost. AI has an immense carbon footprint. Systems like ChatGPT take months to train in high-powered data centers, which demand huge amounts of electricity, much of which is still generated with fossil fuels, as well as water for cooling. “One of the reasons why Open AI needs investments [to the tune of] $10 billion from Microsoft is because they need to pay for all of that computation,” says Kentaro Toyama, a computer scientist at the University of Michigan. There’s also an ecological toll from mining rare minerals required for hardware and infrastructure. This environmental exploitation pollutes land, triggers natural disasters and causes large-scale human displacement. Finally, for data labeling needed to train and correct AI algorithms, the Big Data industry employs cheap and exploitative labor, often from the Global South.
Generative AI tools are based on large language models (LLMs), with most well-known being various versions of GPT. LLMs can perform natural language processing, including translating, summarizing and answering questions. They use artificial neural networks, called deep learning or machine learning. Inspired by the human brain, neural networks are made of millions of artificial neurons. “The basic principles of neural networks were known even in the 1950s and 1960s,” Toyama says, “but it’s only now, with the tremendous amount of compute power that we have, as well as huge amounts of data, that it’s become possible to train generative AI models.”
Though there aren’t any official figures about the power consumption or emissions from data centers, experts estimate that they use one percent of global electricity—more than entire countries.
In recent months, much attention has gone to the transformative benefits of these technologies. But it’s important to consider that these remarkable advances may come at a price.
AI’s carbon footprint
In their latest annual report, 2023 Landscape: Confronting Tech Power, the AI Now Institute, an independent policy research entity focusing on the concentration of power in the tech industry, says: “The constant push for scale in artificial intelligence has led Big Tech firms to develop hugely energy-intensive computational models that optimize for ‘accuracy’—through increasingly large datasets and computationally intensive model training—over more efficient and sustainable alternatives.”
Though there aren’t any official figures about the power consumption or emissions from data centers, experts estimate that they use one percent of global electricity—more than entire countries. In 2019, Emma Strubell, then a graduate researcher at the University of Massachusetts Amherst, estimated that training a single LLM resulted in over 280,000 kg in CO2 emissions—an equivalent of driving almost 1.2 million km in a gas-powered car. A couple of years later, David Patterson, a computer scientist from the University of California Berkeley, and colleagues, estimated GPT-3’s carbon footprint at over 550,000 kg of CO2 In 2022, the tech company Hugging Face, estimated the carbon footprint of its own language model, BLOOM, as 25,000 kg in CO2 emissions. (BLOOM’s footprint is lower because Hugging Face uses renewable energy, but it doubled when other life-cycle processes like hardware manufacturing and use were added.)
Luckily, despite the growing size and numbers of data centers, their increasing energy demands and emissions have not kept pace proportionately—thanks to renewable energy sources and energy-efficient hardware.
But emissions don’t tell the full story.
AI’s hidden human cost
“If historical colonialism annexed territories, their resources, and the bodies that worked on them, data colonialism’s power grab is both simpler and deeper: the capture and control of human life itself through appropriating the data that can be extracted from it for profit.” So write Nick Couldry and Ulises Mejias, authors of the book The Costs of Connection.
The energy requirements, hardware manufacture and the cheap human labor behind AI systems disproportionately affect marginalized communities.
Technologies we use daily inexorably gather our data. “Human experience, potentially every layer and aspect of it, is becoming the target of profitable extraction,” Couldry and Meijas say. This feeds data capitalism, the economic model built on the extraction and commodification of data. While we are being dispossessed of our data, Big Tech commodifies it for their own benefit. This results in consolidation of power structures that reinforce existing race, gender, class and other inequalities.
“The political economy around tech and tech companies, and the development in advances in AI contribute to massive displacement and pollution, and significantly changes the built environment,” says technologist and activist Yeshi Milner, who founded Data For Black Lives (D4BL) to create measurable change in Black people’s lives using data. The energy requirements, hardware manufacture and the cheap human labor behind AI systems disproportionately affect marginalized communities.
AI’s recent explosive growth spiked the demand for manual, behind-the-scenes tasks, creating an industry described by Mary Gray and Siddharth Suri as “ghost work” in their book. This invisible human workforce that lies behind the “magic” of AI, is overworked and underpaid, and very often based in the Global South. For example, workers in Kenya who made less than $2 an hour, were the behind the mechanism that trained ChatGPT to properly talk about violence, hate speech and sexual abuse. And, according to an article in Analytics India Magazine, in some cases these workers may not have been paid at all, a case for wage theft. An exposé by the Washington Post describes “digital sweatshops” in the Philippines, where thousands of workers experience low wages, delays in payment, and wage theft by Remotasks, a platform owned by Scale AI, a $7 billion dollar American startup. Rights groups and labor researchers have flagged Scale AI as one company that flouts basic labor standards for workers abroad.
It is possible to draw a parallel with chattel slavery—the most significant economic event that continues to shape the modern world—to see the business structures that allow for the massive exploitation of people, Milner says. Back then, people got chocolate, sugar, cotton; today, they get generative AI tools. “What’s invisible through distance—because [tech companies] also control what we see—is the massive exploitation,” Milner says.
“At Data for Black Lives, we are less concerned with whether AI will become human…[W]e’re more concerned with the growing power of AI to decide who’s human and who’s not,” Milner says. As a decision-making force, AI becomes a “justifying factor for policies, practices, rules that not just reinforce, but are currently turning the clock back generations years on people’s civil and human rights.”
Ironically, AI plays an important role in mitigating its own harms—by plowing through mountains of data about weather changes, extreme weather events and human displacement.
Nuria Oliver, a computer scientist, and co-founder and vice-president of the European Laboratory of Learning and Intelligent Systems (ELLIS), says that instead of focusing on the hypothetical existential risks of today’s AI, we should talk about its real, tangible risks.
“Because AI is a transverse discipline that you can apply to any field [from education, journalism, medicine, to transportation and energy], it has a transformative power…and an exponential impact,” she says.
AI's accountability
“At the core of what we were arguing about data capitalism [is] a call to action to abolish Big Data,” says Milner. “Not to abolish data itself, but the power structures that concentrate [its] power in the hands of very few actors.”
A comprehensive AI Act currently negotiated in the European Parliament aims to rein Big Tech in. It plans to introduce a rating of AI tools based on the harms caused to humans, while being as technology-neutral as possible. That sets standards for safe, transparent, traceable, non-discriminatory, and environmentally friendly AI systems, overseen by people, not automation. The regulations also ask for transparency in the content used to train generative AIs, particularly with copyrighted data, and also disclosing that the content is AI-generated. “This European regulation is setting the example for other regions and countries in the world,” Oliver says. But, she adds, such transparencies are hard to achieve.
Google, for example, recently updated its privacy policy to say that anything on the public internet will be used as training data. “Obviously, technology companies have to respond to their economic interests, so their decisions are not necessarily going to be the best for society and for the environment,” Oliver says. “And that’s why we need strong research institutions and civil society institutions to push for actions.” ELLIS also advocates for data centers to be built in locations where the energy can be produced sustainably.
Ironically, AI plays an important role in mitigating its own harms—by plowing through mountains of data about weather changes, extreme weather events and human displacement. “The only way to make sense of this data is using machine learning methods,” Oliver says.
Milner believes that the best way to expose AI-caused systemic inequalities is through people's stories. “In these last five years, so much of our work [at D4BL] has been creating new datasets, new data tools, bringing the data to life. To show the harms but also to continue to reclaim it as a tool for social change and for political change.” This change, she adds, will depend on whose hands it is in.