The Bump Effect: Nine Months of Big Data

Anne Morriss put down the phone and rushed to where her baby lay sleeping. She watched her newborn breathe for a minute before hurriedly picking up the phone, “He’s still alive,” she said shakily. Anne and her partner had returned home from the hospital with their newborn son when they received the most unnerving phone call of their lives. A physician they didn’t know, from the Massachusetts department of health, called to find out if their child was still alive. When Anne answered yes, the doctor asked her to go check again. Their next step was a mad rush to bring their baby to the hospital. When baby Alec was just one day old a nurse pricked his heel with a lancet and collected his blood in a slender tube before blotting it on filter paper. That small sample of blood was broken apart into charged molecules then deflected by a magnet, so that the amino acids in the baby’s blood could be measured. Newborn genetic screening is mandatory in the United States, but if you ask an obstetrician what this test reveals they likely won’t be able to tell you. It simply does too much. More than 60 diseases can be identified from the assay , most of which few physicians have ever encountered in actual patients. Alec’s newborn screening test showed that he lacked the enzymes needed to break down fat and convert it into energy for the body. The disease is called MCADD , medium chain acyl-CoA dehydrogenase deficiency, and it affects one in 15,000 babies born in the United States. Before genetic screening, babies with the disorder usually died, often misdiagnosed as Reye’s syndrome or SIDS. Newborn genetic screening likely saved Alec’s life. Morriss found herself pondering the genetic nature of the disorder. If only she and her wife had known the risk she carried within her DNA. This was magnified by the fact that the couple used a sperm donor to conceive their child, a donor who, like Morriss, also carried risk of the disease. If genetic testing could diagnose the disease why couldn’t it prevent it altogether? Building on this concept, Morriss co-founded GenePeeks in 2010. The company analyzes disease risk in potential children, predicting the likelihood of more than 500 severe disorders. Today it partners with sperm banks to offer parents a personal genetics analysis with their potential donors. One day the technology might change the way we conceive children, letting us pry into our potential. A simple blood draw could unveil a treasure trove of genetic data, including all the possible diseases we carry. The genetics of conceiving a baby is only the first analysis in the network of data that forms during pregnancy. Like a spider web, the complexity builds, offering both a biologist’s banquet and a marketer’s dream. The fetal DNA running through a pregnant woman’s veins has never been easier to capture nor as capable of revealing the secrets of an unborn child. At the same time data brokers have uncovered the sequence of events that herald a pregnancy, able to precisely target expectant parents. Made possible by breakthrough technology, both approaches are having a radical influence on pregnancy today. Nine months of big data that hold infinite promise and worrisome risk. * * *   For me, like most potential parents, the first test I took was not genetic. Instead it was a simple pregnancy test. Filled with anticipation, I bought 25 pregnancy tests from amazon in January. That’s when things started to change. Not necessarily with my body, but with my data. Immediately my Amazon search results began to skew. This was hardly surprising. We all expect the “recommendations for you” will shift based on past purchases. The big change came in late March. It seemed the Internet knew I was pregnant before I could be sure myself. In my excited frenzy over seeing a faint, barely visible red line, I googled “pregnancy test accuracy.” While I agonized over the results of the early pregnancy test, the Internet morphed around me, forming itself into a pregnancy paradise, offering pregnancy sites and baby products that followed me from news sites to blogs to online stores. Using tracking software , I found that with each site I visited more than a dozen data brokers followed me. Their alarm bells were ringing in response to my pregnancy related behavior. From one of these targeted ads I registered on a popular pregnancy site, providing my due date and downloading an app, so that I could track the baby’s growth in a weekly fruit comparison: from a blueberry to a papaya to a watermelon. While I fawned over the adorable update that my embryo was now the size of an orange seed, the company was selling my information to as many retailers as possible. It was the beginning of my pregnancy but also the start of something else. An expectant mother’s data is worth fifteen times that of the average person’s. Merchants know that a new baby means that serious purchases are about to be made and that brand loyalty, often acquired before the baby arrives, can yield years of dependable purchasing. To take advantage of this, data brokers are inventing new computati