A popular genealogy website just helped solve a serial killer cold case in Oregon

On Thursday, detectives in Portland, Ore. announced that a long-cold local murder case finally came to a resolution, 40 years after the fact. In 1979, 20-year-old Anna Marie Hlavka was found dead in the Portland apartment she shared with her fiance and sister. According to police, she was strangled to death and sexually assaulted. Police […]

On Thursday, detectives in Portland, Ore. announced that a long-cold local murder case finally came to a resolution, 40 years after the fact.

In 1979, 20-year-old Anna Marie Hlavka was found dead in the Portland apartment she shared with her fiance and sister. According to police, she was strangled to death and sexually assaulted. Police followed a number of leads and kept tabs on the case for decades without a breakthrough.

Last May, detectives with Portland’s Cold Case Homicide Detail dug back into the case using the methodology made famous when investigators last year tracked down the man believed to be the Golden State Killer.

Around that time, detectives working the Hlavka case reached out to a company called Parabon NanoLabs to determine if their case could be solved the same way, by cross-referencing the suspect’s DNA with public DNA profiles uploaded to GEDmatch, a popular free ancestry and genealogy database.

“Most of our cases are cold cases, many of which are decades old like Anna Marie’s case,” Parabon Chief Genetic Genealogist CeCe Moore told TechCrunch in an email interview.

Many law enforcement agencies are already familiar with a Parabon service called Snapshot Phenotype, which allows the company to predict aspects of a person’s physical appearance using only DNA. At Parabon, Moore’s team has successfully identified 33 individuals for law enforcement since its launch in May 2018. The team works both cold cases and active investigations.

Moore explained how her team takes a suspect’s DNA and uploads it into GEDmatch . There, the team can identify potential relatives, usually distant cousins and not-close relatives.

“We build their family trees and then try to determine who might be related to all of these different people and their ancestors,” Moore said. “When we are successful, we reverse engineer the family tree of the unknown suspect based on the trees of the people who share DNA with him in GEDMatch.”

According to the police bureau’s report, the breakthrough led them to Texas:

The forensic genealogist was able to map three of the four familial lines of the killer and identified the killer as Jerry Walter McFadden, born March 21, 1948. McFadden was a convicted murderer and was executed by the State of Texas in October 1999. Due to McFadden’s execution date, his DNA profile was never entered into the FBI CODIS database for comparison.

Detectives travelled to Texas to interview McFadden’s family members and obtain a confirmatory DNA standard to compare with the DNA evidence in the Hlavka murder. Detectives obtained DNA standards with their consent from members of McFadden’s family. Detectives also learned McFadden traveled to the Pacific Northwest in 1979 with an acquaintance from their home town. The woman reported dropping him off in Portland and having no further contact with him.

The case is the latest example of how the popularity of at-home DNA test kits — and the data they yield, often uploaded into open online genealogy databases — is a windfall for investigators. In the instance of McFadden, the DNA trail led to some surprising connections.

“In an earlier case I worked on [the 1981 murder of Ginny Freeman of Brazos, Texas], genetic genealogy analysis also led to a man who had been executed in 1999 in Texas, James Otto Earhart,” Moore told TechCrunch.

“It is really strange to think that these two serial killers that we identified through genetic genealogy a few months apart decades after their crimes, were on Texas death row together and executed the same year.

A popular genealogy website just helped solve a serial killer cold case in Oregon

On Thursday, detectives in Portland, Ore. announced that a long-cold local murder case finally came to a resolution, 40 years after the fact. In 1979, 20-year-old Anna Marie Hlavka was found dead in the Portland apartment she shared with her fiance and sister. According to police, she was strangled to death and sexually assaulted. Police […]

On Thursday, detectives in Portland, Ore. announced that a long-cold local murder case finally came to a resolution, 40 years after the fact.

In 1979, 20-year-old Anna Marie Hlavka was found dead in the Portland apartment she shared with her fiance and sister. According to police, she was strangled to death and sexually assaulted. Police followed a number of leads and kept tabs on the case for decades without a breakthrough.

Last May, detectives with Portland’s Cold Case Homicide Detail dug back into the case using the methodology made famous when investigators last year tracked down the man believed to be the Golden State Killer.

Around that time, detectives working the Hlavka case reached out to a company called Parabon NanoLabs to determine if their case could be solved the same way, by cross-referencing the suspect’s DNA with public DNA profiles uploaded to GEDmatch, a popular free ancestry and genealogy database.

“Most of our cases are cold cases, many of which are decades old like Anna Marie’s case,” Parabon Chief Genetic Genealogist CeCe Moore told TechCrunch in an email interview.

Many law enforcement agencies are already familiar with a Parabon service called Snapshot Phenotype, which allows the company to predict aspects of a person’s physical appearance using only DNA. At Parabon, Moore’s team has successfully identified 33 individuals for law enforcement since its launch in May 2018. The team works both cold cases and active investigations.

Moore explained how her team takes a suspect’s DNA and uploads it into GEDmatch . There, the team can identify potential relatives, usually distant cousins and not-close relatives.

“We build their family trees and then try to determine who might be related to all of these different people and their ancestors,” Moore said. “When we are successful, we reverse engineer the family tree of the unknown suspect based on the trees of the people who share DNA with him in GEDMatch.”

According to the police bureau’s report, the breakthrough led them to Texas:

The forensic genealogist was able to map three of the four familial lines of the killer and identified the killer as Jerry Walter McFadden, born March 21, 1948. McFadden was a convicted murderer and was executed by the State of Texas in October 1999. Due to McFadden’s execution date, his DNA profile was never entered into the FBI CODIS database for comparison.

Detectives travelled to Texas to interview McFadden’s family members and obtain a confirmatory DNA standard to compare with the DNA evidence in the Hlavka murder. Detectives obtained DNA standards with their consent from members of McFadden’s family. Detectives also learned McFadden traveled to the Pacific Northwest in 1979 with an acquaintance from their home town. The woman reported dropping him off in Portland and having no further contact with him.

The case is the latest example of how the popularity of at-home DNA test kits — and the data they yield, often uploaded into open online genealogy databases — is a windfall for investigators. In the instance of McFadden, the DNA trail led to some surprising connections.

“In an earlier case I worked on [the 1981 murder of Ginny Freeman of Brazos, Texas], genetic genealogy analysis also led to a man who had been executed in 1999 in Texas, James Otto Earhart,” Moore told TechCrunch.

“It is really strange to think that these two serial killers that we identified through genetic genealogy a few months apart decades after their crimes, were on Texas death row together and executed the same year.

Curious 23andMe twin results show why you should take DNA testing with a grain of salt

If you’ve ever enthusiastically sent your spit off in the mail, you were probably anxious for whatever unexpected insights the current crop of DNA testing companies would send back. Did your ancestors hang out on the Iberian peninsula? What version of your particular family lore does the science support? Most people who participate in mail-order […]

If you’ve ever enthusiastically sent your spit off in the mail, you were probably anxious for whatever unexpected insights the current crop of DNA testing companies would send back. Did your ancestors hang out on the Iberian peninsula? What version of your particular family lore does the science support?

Most people who participate in mail-order DNA testing don’t think to question the science behind the results — it’s science after all. But because DNA testing companies lack aggressive oversight and play their algorithms close to the chest, the gems of genealogical insight users hope to glean can be more impressionistic than most of these companies let on.

To that point, Charlsie Agro, host of CBC’s Marketplace, and her twin sister sent for DNA test kits from five companies: 23andMe, AncestryDNA, MyHeritage, FamilyTreeDNA and Living DNA.

As CBC reports, “Despite having virtually identical DNA, the twins did not receive matching results from any of the companies.” That bit shouldn’t come as a surprise. Each company uses its own special sauce to analyze DNA so it’s natural that there would be differences. For example one company, FamilyTreeDNA, attributed 14% of the twins’ DNA to the Middle East, unlike the other four sets of results.

Beyond that, most results were pretty predictable — but things got a bit weird with the 23andMe data.

As CBC reports:

“According to 23andMe’s findings, Charlsie has nearly 10 per cent less “broadly European” ancestry than Carly. She also has French and German ancestry (2.6 per cent) that her sister doesn’t share.

The identical twins also apparently have different degrees of Eastern European heritage — 28 per cent for Charlsie compared to 24.7 per cent for Carly. And while Carly’s Eastern European ancestry was linked to Poland, the country was listed as “not detected” in Charlsie’s results.”

The twins shared their DNA with a computational biology group at Yale which verified that the DNA they sent off was statistically pretty much identical. When questioned for the story, 23andMe noted that its analyses are “statistical estimates” — a phrase that customers should bear in mind.

It’s worth remembering that the study isn’t proper science. With no control group and an n (sample size) of one set of twins, nothing definitive can be gleaned here. But it certainly raises some interesting questions.

Twin studies have played a vital role in scientific research for ages. Often, twin studies allow researchers to explore the effects of biology against those of the environment across any number of traits — addiction, mental illness, heart disease, and so on. In the case of companies like 23andMe, twin studies could shed a bit of light on the secret algorithms that drive user insights and revenue.

Beyond analyzing the cold hard facts of your DNA, companies like 23andMe attract users with promises of “reports” on everything from genetic health risks to obscure geographic corners of a family tree. Most users don’t care about the raw data — they’re after the fluffier, qualitative stuff. The qualitative reporting is where companies can riff a bit, providing a DNA-based “personal wellness coach” or advice about whether you’re meant to be a morning person or a night owl.

Given the way these DNA services work, their ancestry results are surprisingly malleable over time. As 23andMe notes, “because these results reflect the ancestries of individuals currently in our reference database, expect to see your results change over time as that database grows.” As many non-white DNA testing customers have found, many results aren’t nearly as dialed in for anyone with most of their roots beyond Europe. Over time, as more people of color participate, the pool of relevant DNA grows.

Again, the CBC’s casual experiment is by no means definitive science — but neither are DNA testing services. For anyone waiting with bated breath for their test results, remember that there’s still a lot we don’t know about how these companies come to their conclusions. Given the considerable privacy trade-off in handing your genetic material over to big pharma through a for-profit intermediary, it’s just some food for thought.

Sophia Genetics bags $77M Series E, with 850+ hospitals signed up to its “data-driven medicine”

Another sizeable cash injection for big data biotech: Sophia Genetics has announced a $77M Series E funding round, bringing its total raised to $140M since the business was founded back in 2011. The company, which applies AI to DNA sequencing to enable what it dubs “data-driven medicine”, last closed a $30M Series D in fall 2017. […]

Another sizeable cash injection for big data biotech: Sophia Genetics has announced a $77M Series E funding round, bringing its total raised to $140M since the business was founded back in 2011.

The company, which applies AI to DNA sequencing to enable what it dubs “data-driven medicine”, last closed a $30M Series D in fall 2017.

The Series E was led by Generation Investment Management . Also investing: European private equity firm, Idinvest Partners. Existing investors, including Balderton Capital and Alychlo, also participated in the round.

When we last spoke to Sophia Genetics it had around 350 hospitals linked via its SaaS platform, and was then adding around 10 new hospitals per month.

Now it says its Sophia AI platform is being used by more than 850 hospitals across 77 countries, and it claims to have supported the diagnosis of more than 300,000 patients.

The basic idea is to improve diagnoses by enabling closer collaboration and knowledge sharing between hospitals via the Sophia AI platform, with an initial focus on oncology, hereditary cancer, metabolic disorders, pediatrics and cardiology. 

Expert (human) insights across the network of hospital users are used to collectively enhance genomic diagnostics, and push towards predictive analysis, by feeding and training AI algorithms intended to enhance the reading and analysis of DNA sequencing data.

Sophia Genetics describes its approach as the “democratization” of DNA sequencing expertise.

Commenting on the Series E in a statement, Lilly Wollman, co-head of Generation’s growth equity team said: “We believe that leveraging genetic sequencing and advanced digital analysis will enable a more sustainable healthcare system. Sophia Genetics is a leader in the preventive and personalized medicine revolution, enabling the development of targeted therapeutics, thereby vastly improving health outcomes. We admire Sophia Genetics not just for its differentiated analytics capability across genomic and radiomic data, but also for its exceptional team and culture”.

The new funding will be put towards further expanding the number of hospitals using Sophia Genetics’ technology, and also on growing its headcount with a plan to ramp up hiring in the US especially.

The Swiss-founded firm is now co-based in Lausanne and Boston, US.

In another recent development the company added radiomics capabilities to its platform last year, allowing for what it describes as “a prediction of the evolution of a tumour”, which it suggests can help inform a physician’s choice of treatment for the patient.

As biological manufacturing moves to the mainstream, Synvitrobio rebrands and raises cash

The pace at which the scientific breakthroughs working to bend the machinery of life to the whims of manufacturing have transformed into real businesses has intensified competition in the biomanufacturing market. That’s just one reason why Synvitrobio is rebranding as it takes on $2.6 million in new financing to pursue opportunities in biopharmaceutical and biochemical manufacturing. […]

The pace at which the scientific breakthroughs working to bend the machinery of life to the whims of manufacturing have transformed into real businesses has intensified competition in the biomanufacturing market.

That’s just one reason why Synvitrobio is rebranding as it takes on $2.6 million in new financing to pursue opportunities in biopharmaceutical and biochemical manufacturing. Under its new name, Tierra Biosciences, the company hopes to emphasize its focus on agricultural and biochemical products.

The company is one of several looking to commercialize the field of “cell-free” manufacturing — where biological engineers strip down the cellular building blocks of life to their most basic components to create processes that ideally can be more easily manipulated to produce different kinds of chemicals.

There’s a standard way to create these cell free processes (described quite nicely in The Economist).

Grab a few quarts of culture with some kind of bacteria, plant or animal cells in it. Then use pressure to force the cells through a valve to break up their membranes and DNA . Give the goo a nice warm environment heated to roughly the average temperature of a human body for about an hour. That activates enzymes that will eat the existing DNA.

Put all of it in a centrifuge to separate out the ribosomes (which are the important bits). Take those ribosomes and give them a mixture of sugars, amino acids, adenosine triphosphate (the molecular compound that breaks down to provide energy for all biological functions), and new DNA with a different set of instructions on what to make and voila! Micro-factories in a test tube.

Along with co-founders Richard Murray, of the California Institute of Technology, and George Church, one of the living legends of modern genetics, chief executive officer Zachary Sun designed Tierra to be an engine for new biochemical discovery.

“Everything floats in the cytoplasm… We keep that internal stuff and that allows us to run reactions where a cell wall isn’t necessary. I want to reduce the complex system down to its component parts,” says Sun. “We look at this as a data collection problem. We want to use cell free to tell you what to put either in a cell or in cell free systems… We can collect more data faster using our cell free system.”

The startup is already working with the Department of Energy research institution at Oak Ridge National Laboratory to develop processes to create vanillin (vanilla extract) and mevalonate (turpentine) from biomass.

It’s an approach that is already showing the potential for investment returns in life sciences and pharmaceuticals. For inspiration, Tierra can look to the South San Francisco-based Sutro Biopharma.

That company has signed a drug discovery agreement with Merck to develop new immune-modulating therapies (that bring the immune system into check) for cancer and auto-immune disorders, in a deal worth up to $1.6 billion if the company hits certain milestones — in addition to a $60 million upfront payment. Sutro raised over $85 million in new funding in July (from investors including Merck) and just filed to go public on the Nasdaq.

According to Sun, the newly-named Tierra has its own partnerships with global 2000 companies in the works. “We’re looking to scale those commitments. We see the application space as being this natural products environment,” he says.

There’re multiple avenues to pursue with the technology widely applicable to everything from pesticides to pharmaceuticals, flavorings, and even energy.

Cyclotron Road team photos. 2016. Zachary Sun

“Synthetic biology at its core is about applying engineering best practices to speed up the ‘design-build-test’ cycles in the reprogramming of existing or construction of new biological systems. By component-izing and modularizing the cell they can radically increase the speed of those cycles,” says Seth Bannon, a co-founder of the venture capital firm Fifty Years, which invests in startups commercializing “frontier” science. 

For the investors, entrepreneurs and reporters who witnessed the birth of the cleantech bubble a decade ago and then tracked its implosion in subsequent years, the excitement this kind of technology elicits is another of history’s rhymes.

Technologies like Tierra’s aren’t new. San Diego-based Genomatica has been working on biological manufacturing for the past 18 years. The company is now exploring a cell-free system to grow chemicals that are used in the manufacture of materials like Lycra. Since 2008, Medford, Mass.-based GreenLight Biosciences has been working to bring its own biologically-based zero-calorie sugar substitute to market.

What may be different now is the maturity of the technologies that are being commercialized and the perspective of the startups coming to market — who have the benefit of avoiding the missteps made by an earlier generation.

Investors led by Social Capital with participation from Fifty Years, KdT Ventures and angel investors seem to see a difference in these companies. And large research institutions are also marshaling resources to support the vision laid out by Sun, Murray and Church. DARPA, the National Institutes of Health, the Department of Energy, Cyclotron Road and Lawrence Berkeley National Laboratory, the National Science Foundation, and the Gates Foundation have all backed the company as well.

“So many therapeutic molecules come from nature. As the DNA of plants, animals, and microbes is read in exponentially increasing volume, we expect to find useful and game-changing chemistry encoded by it. Tierra’s platform will allow us to look for molecules which might otherwise be buried in the complexity of cells’ metabolism,” says Louis Metzger, Chief Scientific Officer of Tierra, who comes from a background of drug discovery.