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DeCODE genetics
DeCODE genetics
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deCODE genetics (Icelandic: Íslensk erfðagreining) is a biopharmaceutical company based in Reykjavík, Iceland. The company was founded in 1996 by Kári Stefánsson[1] with the aim of using population genetics studies to identify variations in the human genome associated with common diseases, and to apply these discoveries "to develop novel methods to identify, treat and prevent diseases."[2]

Key Information

As of 2019, more than two-thirds of the adult population of Iceland was participating in the company's research efforts,[3] and this "population approach" serves as a model for large-scale precision medicine and national genome projects around the world.[4] deCODE is probably best known for its discoveries in human genetics, published in major scientific journals and widely reported in the international media. But it has also made pioneering contributions to the realization of precision medicine more broadly, through public engagement in large-scale scientific research; the development of DNA-based disease risk testing for individuals and across health systems; and new models of private sector participation and partnership in basic science and public health.[5]

Since 2012, it has been an independent subsidiary of Amgen and its capabilities and discoveries have been used directly in the discovery and development of novel drugs. This example has helped to spur investment in genomics and precision therapeutics by other pharmaceutical and biotechnology companies.[6]

Iceland and the population approach

[edit]

In 1996, when Stefansson left a tenured position at Harvard Medical School to return to Iceland to found a genomics enterprise, nearly everything in his thinking was unproven or controversial. At the time, the causes of some rare diseases - often variations in single genes that could be found by studying small families - were beginning to be uncovered.[7] Yet it was far from universally accepted that there was any significant genetic component to common/complex diseases like heart disease or type 2 diabetes with well-known behavioral and environmental risk factors; nor, even if there were, whether such variations could be found given the rudimentary technology for reading DNA.[8]

Stefansson was convinced that these existed and could be identified, but only by working at industrial scale. A decade before the term was in common use, deCODE's premise was that this was a big data problem: finding variants impacting risk in dynamic interaction with lifestyle and other factors would require studies not at the family level, but at the scale of public health. As a discovery venture in uncharted territory, the strategy was to assemble and query as much data as possible: DNA contributed by tens of thousands of people; both broad and deep medical and health data; and, crucially, comprehensive genealogies linking all these participants together.[9] In short, this required a population, with people willing to take part in research, a modern healthcare system with meaningful numbers of cases of most common diseases, and much genealogical data. Iceland, Stefansson's native country, with 270,000 people at the time, fit this description better than any other.[10]

In 1996, funded by $12 million in American venture capital, deCODE set up a laboratory and began operations.[11] Within its first few years it recruited and genotyped tens of thousands of participants. It made rapid progress in creating a national genealogy database; developed a novel privacy protection system with government-supervised identity encryption; signed a landmark partnership with Swiss pharmaceutical company Roche; and mapped putative disease genes in a handful of conditions.[12]

At the same time as it was beginning to prove its science, the company ignited a huge controversy with the proposal to create a research database - the Iceland Health Sector Database (or IHD for short) - containing copies of medical records from across the country's national health service.[13] In December 1998, with lobbying from deCODE, the Icelandic Parliament passed the Act on Health Sector Database which permitted public bidding for the right of a company to create this health database and use it for commercial research and to support the national health system.[14] The parliament shortly thereafter granted deCODE the right to create this database after the company made a successful bid to do so.[15] Widely supported by the public and parliament, the IHD's openly commercial aims, and proposed inclusion of medical records data unless individuals opted out, unleashed vehement opposition played out in the local and international media, led by a group of Icelandic activists as well as a number of foreign bioethicists.[16] Although the IHD was never built, the debate underscored the political challenges involved in enlisting an entire society in a scientific enterprise, especially one with the explicit aim of commercializing its discoveries.[17] It also ensured that deCODE and its approach went from being a peripheral curiosity to one of the highest profile enterprises in the global effort to understand the human genome.[18]

Genome of a nation

[edit]

By the time Bill Clinton and Tony Blair announced the completion of the first rough draft of the human genome sequence in June 2000,[19] deCODE was busily scaling up its gene-hunting in dozens of diseases and publishing its first discoveries.[20] The company used the most scalable DNA-reading technology of the time - microsatellite genotyping - to place and measure highly variable and therefore informative markers at hundreds of points along the genome. Analyzed in tandem with the genealogies, this made it possible to home in on regions of specific chromosomes that people with a given disease tended to have inherited from their common ancestors.[21] Harbored within these regions, the thinking went, were genes or sequence variants associated with disease that could subsequently be found using finer-definition methods and tools.[22]

But the main significance of these early publications was the focus on analytics and the suggestive power of the approach. Much of the field and public attention was focused on the race between the publicly funded Human Genome Project (HGP) and the private company Celera to generate the complete sequence of a single whole genome to use as a reference for future research. This was a technical challenge to generate and assemble raw data. By contrast, deCODE was advancing a strategy for analyzing variation in tens of thousands of genomes through genetics, leveraging the nature of the genome as a means of replicating and transmitting information. The power of the genetics was on full view by 2002, when deCODE published a genetic map of the genome consisting of 5000 microsatellite markers, which the genealogies made it possible to order correctly across all the chromosomes. The map was critical to correcting and completing the public reference genome sequence in 2003, improving the accuracy of the HGP assembly from 93% to 99%.[23]

One key to this approach has been mass participation. From its early days, over 90% of people asked to participate in deCODE's disease research have agreed to do so.[24] Participation is voluntary but not trivial. It requires going to a data collection center to have blood drawn, answer questionnaires, and undergo clinical examinations and tests relevant to a given disease.[25] By 2003, more than 100,000 people had volunteered to take part in one or more of deCODE's three-dozen common diseases research programs.[26] This number rose to 130,000 by 2007,[27] and more than 160,000 by 2018. This represents two-thirds of all adult citizens. The genomes of some 60,000 of these participants had been directly sequenced by 2019, with thousands more being sequenced every month.[28]

A second and unique pillar of deCODE's work is the genealogies. Geneticist Mary Claire King, whose family-based research in the early 1990s led to the discovery of the BRCA1 and BRCA2 breast cancer genes, predicted not long after deCODE's founding that the ability "to trace the genealogy of an entire nation...could become one of the treasures of modern medicine."[29] In 1997, deCODE formed a partnership with local software firm Fridrik Skulason ehf to accelerate the creation of a comprehensive, computerized national genealogy database. It drew on all available sources, from the earliest calfskin records and sagas through the 1703 census and parish records to the contemporary national registry.[30]

By the early 2000s they had created what is still today the most comprehensive genealogy of an entire country. It links together all living citizens through virtually complete records back to 1703 (itself recognized by UNESCO as the world's first nominal national census) and stretches back to before the settlement of the country in the ninth century. In the research version of the database, the identities of individuals are encrypted via the same anonymization system used for DNA and medical data, so that the data can be correlated.[31] And In 2003, deCODE launched a public-facing, online version of the database, called Íslendingabók, or the Book of Icelanders. Anyone with an Icelandic social security number could request a password and then research their family tree and see their nearest family connection to anyone else in the country. Within its first month online, more than one-third of the population had requested a password.[32] By 2020, it had over 200,000 registered users and more than 900,000 linked entries, comprising the majority of Icelanders who have ever lived. On an average day, nearly 6000 people, or close to two percent of all citizens, consult the database.[33]

In a country that is essentially a huge extended family with a correspondingly keen interest in how its members are related, Islendingabok has become a constant in national life and a daily and direct means of social engagement with deCODE's work. But in scientific terms, the ability to understand the precise genealogical relationships of all participants in its research projects has given deCODE an abiding advantage as a discovery enterprise, ensuring that its genomic and medical datasets have remained among the largest and best powered collections anywhere.[34]

At each successive advance in technology for reading DNA the genealogies have amplified both the amount of data that can be generated from them as well as the power to extract information from the data.[35] In the era of microsatellites, it was possible to establish that participants shared certain markers and segments of the genome not by chance but by descent. With the advent in the mid-2000s of genotyping chips, which could measure hundreds of thousands of single-letter variations (SNPs) across the genome, deCODE statisticians were able to accurately phase segments of the genome - to understand the parental source of segments -  and then impute genotypes measured in some people across the entire population.[36]

This effectively multiplies the size and power of any study. When Illumina began selling machines that could economically sequence whole genomes, deCODE was able to directly sequence several thousand Icelanders and then impute whole genome sequence (WGS) data for virtually the entire population. This represents one of the largest single collections of WGS data in the world, and the first results of its analysis were published in 2015 in a special edition of Nature Genetics.[37] The direct sequencing of tens of thousands of more people since then has enabled routine searches for ever rarer variants at an unprecedented scale.[38]

Discoveries and scientific contributions

[edit]

Genome research in general, and deCODE's global reputation as a discovery organization, took off with the arrival of SNP genotyping chips in the mid-2000s.[39] These tools set off a worldwide boom in genome-wide association studies (GWAS), in which the entire genome is scanned to identify SNPs that those with a given disease tend to have one version of, while unaffected individuals tend to have another. In common diseases, as with many traits or phenotypes such as drug response, the difference is not one of causal certainty but of statistical odds representing increased or decreased risk versus the population average. The ability to conduct large studies and analyze the resulting data - from thousands of patients with a disease and many times more control subjects, ideally unaffected relatives - is therefore at a premium.[40]

deCODE's vast collection of DNA, medical and genealogical data that could be mined together - and enriched through repeated querying and imputation - was almost perfectly suited to this type of study. Since 2003, the company has discovered and published hundreds of variants linked to susceptibility to scores of diseases and conditions, including major ongoing contributions to understanding inherited risk for Alzheimer's disease, schizophrenia and other psychiatric disorders; a dozen common forms of cancer; coronary artery disease, stroke atrial fibrillation and the other most common cardiovascular diseases; as well as traits and phenotypes ranging from drug response to cognition and hair and eye color.[41] The company publishes its discoveries in peer-reviewed journals, and many, such as the TCF7L2 variants in type 2 diabetes, are used as standard risk markers in polygenic risk modeling and in research.[42]

A review of the GWAS era published in Nature Communications in 2019 quantified deCODE's outsized contribution to the field: Icelanders accounted for 12% of all participants in all published GWAS studies globally between 2007 and 2017, with each citizen participating on average to 19 published findings in that period alone.[43] Stefansson, deCODE's research chief Unnur Thorsteinsdottir, and statistician Gudmar Thorleifsson were respectively ranked the first-, second- and sixth-highest impact GWAS authors in the world.[44]

Adding whole-genome sequencing (WGS) on top of its genotyping data gave a new dimension and power to deCODE's discovery capabilities. By definition, the common SNPs on standard genotyping chips yielded reliable risk markers but not a determinant foothold in the biology of complex diseases. Yet by running the company's growing number of directly sequenced whole genomes through the genotyping data and genealogies as a scaffold, the company's statisticians have been able to impute very high definition WGS on the entire population. The result has been the ability to conduct GWAS studies using from 20 to 50 million variants, and to systematically search for rare variants that either cause or confer very high risk of extreme versions of common phenotypes, and thereby pointing directly to putative drug targets.[45]

The value of this approach is best known from the model of PCSK9, in which the study of families with extremely high cholesterol levels and early-onset heart disease led to an understanding of the key role of this gene and the development of a new class of cholesterol-fighting drugs. deCODE now routinely searches for such rare variants across many phenotypes and the results have provided the basis of drug discovery and development programs.[46] For example, since 2016 its important contributions in cardiovascular disease include demonstrating that it is non-HDL cholesterol rather than merely LDL levels that most accurately reflect risk of heart disease;[47] finding variants in the ASGR1 gene that protect against coronary artery disease;[48] and defining the role of lipoprotein (a) as a major risk factor for heart attack.[49]

As all deCODE's data sits on its servers and can be queried simultaneously, it can also be queried with remarkable speed. In 2014, a group from the Broad Institute stopped by at deCODE on its way back from Finland, where through a major research effort they had found a variant that protected carriers against type 2 diabetes. Over coffee, the deCODE team confirmed that the Finnish variant did not exist in Iceland, but that another did.[50] The Broad group added it to the paper announcing the discovery.[51]

Because of its singular population resources and the questions its scientists can ask and answer, many of deCODE's most remarkable findings have been in basic science. One notable focus has been on elucidating how variation in the sequence of the genome is generated. Following its microsatellite-based genetic map of the genome in 2002, the company created and made available to the scientific community two more: one in 2010 built on 300,000 SNPs,[52] and another in 2019 built on WGS data.[53] Recombination - the reshuffling of chromosomes that takes place in the making of eggs and sperm - is a primary mechanism for generating diversity and to build these maps. Over fifteen years deCODE has published a series of breakthrough papers detailing in a real human population how recombination rate varies according to sex, age and other characteristics, and how these differences impact the generation of genomic diversity and variation of many kinds. The general picture that has emerged is that the genome is generating diversity but within certain bounds, providing a dynamic but generally stable substrate for natural selection and evolution.[54]

To understand the population that it is working in and to address broader questions few can in the same way, deCODE has also from its early days had its own genetic anthropology group. It has published pioneering work on mitochondrial and Y-chromosome mutation to trace the Norwegian and Celtic mix in the early population; sequenced ancient DNA from the settlement period; compared ancient and modern Icelandic genomes to see how genetic drift, epidemics and natural disasters have yielded a modern-day population genetically distinct from its forebears and source populations.[55] and observed variants under positive natural selection in a present-day society.[56] The company has also catalogued human knockouts - people missing certain genes - and reconstructed the genome of the first man of African descent to live in Iceland by analyzing the sequences of hundreds of his living descendants.[57] These studies are avidly followed by foreign and Icelandic media alike, and constitute another type of return that deCODE renders to the society it studies and works within.[citation needed]

Product innovation

[edit]

deCODE's scientific leadership over more than twenty years has enabled it repeatedly to pioneer new types of partnerships, products and applications for many aspects of precision medicine. Between 1998 and 2004, the company signed high-profile and innovative partnerships with pharmaceutical companies Roche, Merck, Bayer, Wyeth and others. These alliances provided research funding to advance deCODE's work, with goals of finding genetically validated new drug targets in common diseases; to develop DNA-based diagnostics, that could gauge risk of disease or predict drug response and identify patients most likely to benefit from a drug; and to design "information-rich" clinical trials that would enroll participants with particular genetic variants, with the potential to make trials smaller, more informative, and with a greater chance of success.[58]

In 2002, deCODE acquired a Chicago-based medicinal chemistry company in order to discover compounds based on its genetics discoveries and so to begin to develop its own pipeline of new drugs.[59] Over the next few years the company initiated and completed several early-stage clinical trials for potential new treatments for heart attack, peripheral artery disease, and conducted work with partners on asthma and SMA.[60] These were early examples of what would today be called 'precision medicine' programs: using genetics for target discovery and to select trial participants by testing them for disease susceptibility through the same pathway targeted by the drug.[61]

In the mid-2000s, deCODE launched a new kind of risk diagnostic focused largely on prevention and wellness. These DNA-based diagnostic tests detected genetic variants identified by deCODE and others that correlated with significantly increased individual risk of common diseases including heart attack,[62] atrial fibrillation and stroke, type 2 diabetes, common (non-BRCA) breast cancer, prostate cancer and glaucoma.[63] The type 2 diabetes test, for example, was based on published studies that showed that approximately 10% of people carried two copies of deCODE's highest impact risk variant, putting them at twice the average risk of developing diabetes, independent of obesity. The medical purpose of the test was "to identify prediabetics at higher than average risk of progressing to full-blown diabetes, and that these same individuals can effectively counteract this added risk through weight loss and through the use of certain medications."[64]

Another novel characteristic of these tests was the integration of multiple, well-validated genetic risk factors. The overall impact of these different risk factors was combined and calculated into what was called a polygenic risk score, placing the individual on a spectrum of risk with regard to that of the population in general, independent of and in addition to other health or lifestyle risk factors.[65] With each new discovery, deCODE could broaden the risk factors tested. The idea was to make screening and prevention strategies and therapies more specific and more effective for those at higher risk, and hopefully to provide new incentive for individuals to follow through with well understood lifestyle modification such as weight loss, smoking cessation, etc.[66] This was the essence of what was then called personalized medicine, but because these tests were new, their medical usefulness was as yet unproven. As everyone is by definition at risk of common diseases, and doctors generally understood genetic risk only as it referred to rare diseases, the medical community approached these tests with skepticism.[67] In 2018, advocacy for the use of polygenic risk scores for identifying those at significantly increased risk of common diseases, and using whole-genome data and new algorithms to build on many early deCODE markers, began a revival.[68]

To judge by the intense media coverage of deCODE's discoveries, ordinary people were very certainly interested in these genetic risk factors and how they might be relevant to their health. In late 2007, the company effectively launched the field of personal genomics with its deCODEme[69] direct-to-consumer (DTC) scan aimed at enabling people to better understand their risk of common diseases and use this information to stay healthy. deCODEme hit the market a day before the now widely known, Google-funded 23andMe.[70] deCODEme's marketing emphasized its pedigree, seriousness and scientific rigor: "provided by a world leader in the discovery of genetic risk factors for disease...[so that its customers] benefit directly from the knowledge and experience of scientists carrying out internationally renowned research" (its competitors used deCODE's published variants as the basis for many of their results); with the scan processed in the same labs that had found them. By 2012, the deCODEme complete scan measured one million SNPs and calculated risk for 47 common diseases and traits as well as basic information on maternal and paternal ancestry, noting that most ancestry scans of the period were not back by much data.[71]

Despite deCODEme's emphasis that its results were for informational purposes — "a roadmap to improve your health" — and the provision of genetic counseling for users who had questions about their results, US regulators quickly took a critical view of disease risk assessments being put directly in the hands of consumers.[72] In June 2010, the FDA wrote to deCODE[73] and its main competitors to say that they considered such scans to be medical devices requiring FDA approval.[74] Facing regulatory headwinds and then corporate reorganization, deCODE stopped selling deCODEme in late 2012.[75] In 2017, the FDA began to approve certain assessments of genetic risk for disease in consumer tests.[76]

In 2018, deCODE broke new ground with a direct intervention in public health and the first national genetic screening program of its kind. The company launched a website that enables anyone in Iceland to ask the company - free of charge - to search their whole genome sequence data to determine whether they are likely carriers of a SNP in the BRCA2 gene that confers high risk of breast and prostate cancer in Iceland. Within months, ten percent of the population had requested their BRCA2 status, and the National Hospital has built up its counseling and other services to help people follow up on their preliminary results and use the information to protect their health.[77]

Business

[edit]

Despite its pathbreaking science, or perhaps because it was often far ahead of the field, deCODE had a volatile history as a standalone business. In July 2000, it completed a $200 million IPO on Nasdaq, big for the time and the first listing by an Icelandic company on a US exchange. Its early pharmaceutical alliances, particularly that with Roche, further helped to fund the enrollment of most of the adults in the country in the first decade of its research, and the rapid expansion of both its discovery capabilities and its product development efforts in drugs, diagnostics and personal genomics.[78]

From a scientific perspective, as the Broad Institute's David Altschuler told the MIT Tech Review in 2004, "This is a business in which critical mass is important, and they have achieved critical mass."[79] But the business was also about money. Being an innovation enterprise pioneering new markets, the company had spent more than $500 million on R&D in its first decade and never been profitable. By 2006 it was borrowing more,[80] to fund drug development programs based on completely novel premises; to bring forward diagnostic tests in a market that even supporters termed "still embryonic"; and to market personal genomics, where it was being overshadowed by the Silicon Valley glamour and cash of 23andMe.[81]

By late 2008, the company was "between a rock and a hard place," in Stefansson's own words.[82] Under threat of being delisted from Nasdaq for its flagging stock price, the company needed more capital just as the global markets were going into crisis.[83] Although its scientists kept publishing breakthroughs at a remarkable rate, in late 2009, the company's listed US holding company, deCODE genetics, Inc., declared Chapter 11 bankruptcy.[84] Its key assets - the heart of which was the Iceland genetics operation - were bought and kept running by a consortium of the company's two main original venture backers: ARCH Venture Partners and Polaris Ventures, along with Illumina, Inc., the dominant maker of genotyping chips and sequencing equipment.[85] It abandoned work on its drug development programs.[86]

As a business, deCODE had in some sense gone back to the future: it was a 13-year-old company with a global reputation, again backed by its original VCs, which Newsweek called "the world's most successful failure."[87] During the following period Stefansson mused publicly that deCODE had been founded between six and ten years too early.[88] The technology for accurately reading DNA with sufficient detail, he reasoned, had not arrived until the mid-2000s, leaving deCODE in debt for years of R&D but based on findings that didn't provide a detailed enough insight into the biology of disease to swiftly create commercially compelling diagnostics and developmental drugs.[89] What might provide that insight was population-scale WGS data. By 2010 Stefansson was outlining how to sequence a few thousand individuals and then use imputation - powered again by the genealogies - to ensure that deCODE would be the first in the world to have anything like it.[90]

In spite of its straitened circumstances, with Illumina as one of its owners the company could still receive the latest sequencing machines and reagents. In 2011, deCODE and Illumina collaborated on a paper that gave an early hint at the power of WGS imputation, turning 500 sequences into 40,000 whole genomes of data. This was enough to begin to discover rare variants, validated through replication in several other populations.[91] Unlike common variants, mutations causing rare diseases tend to be in the regions of genes that encode proteins, providing both a direct window on disease biology and so more direct utility as drug targets. In December 2012, the American pharmaceutical company Amgen acquired deCODE for $415 million.[citation needed]

A key rationale for the acquisition was deCODE's unique ability to use WGS data to discover rare coding variants and cause extreme versions of more common diseases. As Sean Harper, then Amgen's head of R&D told Forbes, "It was really working on targets like PCSK9 [for heart disease]...that really drove home the immense value of having targets that have either been discovered or validated by the kind of human genetic analysis that Decode is a world expert in."[92] More broadly, these capabilities could be applied to evaluate current programs as well, and within month of the acquisition deCODE had reviewed Amgen's entire pipeline. In 2018, Harper estimated that "just [by] having strong genetic support for half your pipeline you can improve your rate of return on R&D investments by approximately 50%."[93] By 2020, Amgen had brought two new cardiovascular drugs into clinical trials based directly on deCODE discoveries, which continue to be published in leading scientific journals.[94]

As global model

[edit]

Introducing Stefansson for the organizations at the American Society of Human Genetics annual meeting in 2017, the Broad Institute's Mark Daly observed that the meeting and the field were dominated by "a pervasive paradigm involving biobanks recruited with full population engagement, historical medical registry data, investments in large-scale genetic data collection and statistical methodology, and collaborative follow-up across academic and industry boundaries...[and] deCODE provided the template for this discovery engine."[4]

From its early days, deCODE's example gave fresh impetus to others hunting for disease genes in isolated communities and small populations in Sardinia, Quebec, Newfoundland, northern Sweden, Finland, and elsewhere. However deCODE was not touting the Icelandic population's "relative homogeneity" in order to find variants causing rare syndromes, but because the existence of founder mutations would help to power discovery of variants impacting common disease.[95] In terms of its relevance to global medical challenges, Iceland was not an inbred population with a high prevalence of rare syndromes but rather a European society in miniature that could be studied as a whole: not the biggest small population so much as the smallest big one.[citation needed]

The first large country to follow deCODE's example was the UK.[96] Iceland's experience, behind the scientific and medical value of applying the NHS's vast reach and resources to one of the most diverse populations in the world,[97] informed the authorization of the UK Biobank in 2003[98] and then Genomics England in 2013. Other early, large-scale biobank and genomics efforts linked to major health systems included the Million Veterans Program in the US, launched in 2009;[99] the Research Program on Genes, Environment and Health Archived 20 March 2020 at the Wayback Machine at California's Kaiser Permanente, begun in 2007; and the China Kadoorie Biobank in mainland China and Hong Kong begun in the mid-2000s.[100]

After 2014, when Illumina announced that its new X-Ten system could sequence whole genomes at scale for $1000 each, national genome projects proliferated,[101] from the US (All of Us,  alongside the MVP) and (alongside CKB) to Australia, Canada, Dubai Archived 10 May 2019 at the Wayback Machine, Estonia (originally begun in 2000), France, Hong Kong, Japan, Netherlands, Qatar Archived 25 May 2021 at the Wayback Machine, Saudi Arabia, Singapore, South Korea, Sweden Archived 10 May 2019 at the Wayback Machine, and Turkey, and beyond. Although with varying focuses and approaches, all of these programs were at the least implicitly inspired by deCODE's example.[102]

Other large projects led by pharmaceutical companies have closely followed deCODE's model and its work with Amgen. These include Regeneron's with the Geisinger health system in the US,[103] and Astra Zeneca's hybrid public/private/academic partnership with the Wellcome Trust in the UK, Craig Venter's Human Longevity in California, and Finngen in Helsinki.[104] The latter, founded by Broad Institute leaders and Finnish universities, the health ministry, and biobanks to drive drug discovery,[105] is remarkably close to deCODE's original vision in Iceland but with academics and government bodies as equity partners in the business. This public-private partnership model may explain the passage of legislation in Finland in 2019 authorizing the near wholesale use of anonymized medical records, social welfare data and biobank samples for biomedical research, which goes well beyond the ambitions of the 1998 IHD legislation that caused so much controversy in Iceland twenty years earlier.[106]

deCODE's direct involvement and lineage is also evident across the field. deCODE is a founding member and leader of the Nordic Society of Human Genetics and Precision Medicine, which brings together the resources of all the Scandinavian countries and Iceland and Estonia to advance gene discovery and the application of precision medicine across the region. In 2013, a group of deCODE alumni created a spinoff, NextCODE Health (now Genuity Science), that licensed and further developed informatics and sequence data management tools originally developed in Iceland to support clinical diagnostics and population genomics in other countries.[107] Its systems and tools have been used by national genome projects in England,[108] Qatar,[109] Singapore;[110] pediatric rare disease programs in the UK, US[111] and China;[112] and at its subsidiary Genomics Medicine Ireland. In 2019, deCODE and US regional health system Intermountain partnered to conduct a 500,000-person WGS-based research and precision medicine study,[113] and deCODE also began sequencing 225,000 participants in the UK Biobank.[114]

Response to COVID-19 pandemic

[edit]

In March 2020, as the SARS-CoV-2 virus began to spread widely in Iceland, deCODE temporarily redirected its clinical research, laboratory staff and operations to conduct large-scale testing for COVID-19. This effort marked the company's deepest and most direct ever involvement in public health and constitutes an important component of one of the most intensive and successful containment strategies of any country in the early months of the global pandemic.[115]

The response of Iceland's health authorities to the pandemic was notable for being an early, transparent and effective example of best-practice 'test, trace and isolate' epidemiological control. In late January 2020, the National Directorate of Health began testing people arriving in Iceland from high-risk areas or showing possible symptoms of infection, and, with the Department of Civil Protection and Emergency Management, activated a system to isolate anyone diagnosed with the virus and to trace and quarantine all of their contacts.[116] Iceland's first case was diagnosed on 28 February, a month after targeted testing began, and within days dozens of people were testing positive every day. Little more than two months later, Iceland was virtually free of active infections.[117]

The foundation of this response and the data to guide it was testing. Yet while the official testing effort was prompt and energetic, it was focused on those who were either symptomatic or at high risk due to having likely been in contact with infected people. In early March, deCODE's CEO Kari Stefansson became concerned that without also screening the population at large there was no way to understand the virus' spread or its fatality rate, crucial information for holistically addressing the epidemic.[118] In this "all-hands-on-deck" moment, and with the know-how, people and equipment to rapidly turn the company's genetics research lab into a PCR diagnostic testing facility,[119] he offered to put the company's capabilities to work to screen the general population under the auspices of the Directorate of Health.[120] deCODE staff worked swiftly to put together workflows for everything from sample collection to running the tests to privacy-protected reporting, and to get the swabs and reagents ready to begin large-scale testing. On Thursday 12 March 2020, the company opened its website to book appointments for testing and within hours 12,000 people had signed up. Testing began the following morning, free of charge.[121]

The deCODE effort scaled up quickly to a capacity of over 1000 samples per day. From the beginning of population screening, fewer than 1% of those taking part were found to be infected, indicating that the health authorities' containment strategy was working.[122][non-primary source needed] From mid-March to the end of May 2020, the company conducted an average of 600 tests a day, complementing the health authorities' 250 tests per day at the National-University Hospital. Those testing positive in deCODE's screening were similarly isolated and their contacts traced and asked to quarantine themselves. In total, by the beginning of June more than 60,000 tests had been conducted in Iceland, equivalent to 18 percent of the population. Powered by this combined testing strategy and tracing and isolation follow up, the number of infections in Iceland peaked in the first week of April and dropped steeply off by the end of the month. By mid-May, there were only a handful of active infections in the country, although deCODE and the health authorities continued to conduct as many as 200 tests per day thereafter to try to detect any fresh outbreaks.[123]

In tandem with its screening work, deCODE used its genetics capabilities to sequence the virus from hundreds of infected individuals, and to draw a kind of genealogy of the different clades of the virus in the country. This showed how during the early weeks of the pandemic the virus had entered the country with people infected in different countries and then spread within Iceland.[124][non-primary source needed] In April 2020, with colleagues from the Directorate of Health and the national hospital, the company published in the New England Journal of Medicine a paper detailing what the spread of COVID-19 looks like across a population, and how a robust policy of testing, tracing and isolation could effectively contain it. In May, the company began work to develop and carry out antibody testing in the population, and early results showed that around one percent of the general population that had not been diagnosed with infection carried antibodies for the virus. This meant on the one hand that the virus had been swiftly and well contained, but also that nearly three times had been infected as had been officially diagnosed since the end of February and also that the population was still more than 98% naive.[125] That indicated that large-scale testing would need to continue to detect later outbreaks as the country reopened its borders to travel by its own citizens and others coming to Iceland.[126] In June, the company said that it was working with Amgen's unit in British Columbia to use white blood cells from recovered Icelandic COVID patients to begin to manufacture antibodies for the virus, which could be used either prophylactically or therapeutically.[127]

[edit]

The work of deCODE is criticised by Arnaldur Indriðason's novel Jar City from 2000, which was adapted into a 2006 film of the same name.[128]

deCODE and Kári Stefánsson are satirised as VikingDNA and Professor Lárus Jóhannsson in Dauðans óvissi tími by Þráinn Bertelsson (Reykjavík: JPV Útgáfu, 2004).

deCODE and specifically Kári Stefánsson is presented as the creator of monstrous genetic hybrids in Óttar M. Norðfjörð's satirical 2007 work Jón Ásgeir & afmælisveislan (Reykjavík: Sögur, 2007), and the history of DeCODE appears both directly and in allegorised form (under the fictional name OriGenes) in the same author's novel Lygarinn: Sönn saga (Reykjavík: Sögur, 2011). deCODE is the model for the company CoDex, in CoDex 1962 by Sjón.[129][130]

References

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Further reading

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from Grokipedia
deCODE genetics is an Icelandic biopharmaceutical company headquartered in Reykjavik, founded in 1996 by neurologist Kári Stefánsson, specializing in human genomics research by leveraging the genetically homogeneous Icelandic population to identify sequence variants associated with common diseases. Acquired by in 2012 following a 2009 bankruptcy, deCODE operates as a subsidiary focused on gene discovery, having mapped genetic risk factors for conditions including , , , and . The company's approach relies on a large-scale and sequencing of Icelandic genomes, enabling the world's most productive human gene discovery engine through population-based studies that link genotypes to health records and genealogical data. deCODE's achievements include pioneering contributions to understanding genetic contributions to susceptibility, with discoveries published in peer-reviewed journals that have advanced drug target identification and efforts. deCODE has faced controversies, particularly over ethical concerns regarding the 1998 Icelandic Health Sector Database law granting it exclusive access to centralized health and genetic data with presumed consent, raising privacy and monopoly issues amid public opposition and legal challenges. In 2025, founder Kári Stefánsson was dismissed as CEO by , marking a significant leadership transition amid ongoing operations. Despite these, deCODE continues to drive genomic insights, including ambitious whole-genome sequencing projects exceeding 500,000 samples.

Founding and Historical Context

Establishment and Key Figures (1996)

deCODE genetics was founded in August 1996 in , , by Kári Stefánsson, a neurologist trained at and the , who served as the company's inaugural . The firm was incorporated in the state of as deCODE Genetics Inc., with initial operations centered on leveraging 's isolated population for genetic research. Stefánsson, holding an MD and PhD, envisioned a biopharmaceutical enterprise focused on identifying disease-associated genes through population-scale studies, drawing on his prior experience in and . Stefánsson emerged as the central figure in deCODE's establishment, pioneering the integration of comprehensive genealogical records with genetic data from to accelerate discovery—a methodology that distinguished the company from contemporaneous efforts reliant on smaller cohorts. No other individuals are prominently documented as co-founders during the 1996 inception; Stefánsson's leadership drove early strategic decisions, including securing initial equity issuance of 20 million shares, with 12 million sold to investors to fund operations. His background as an outspoken advocate for large-scale genetic databases positioned deCODE to pursue collaborations with pharmaceutical entities from the outset, though the company's founding emphasized independent Icelandic resources. The establishment reflected Stefánsson's conviction in Iceland's demographic advantages, including a founder population with extensive medical and lineage records spanning centuries, which he argued enabled higher-resolution mapping of genetic risks than diverse global samples. By late 1996, deCODE had begun assembling a proprietary biobank, setting the stage for subsequent gene hunts, with Stefánsson's directorial role ensuring alignment with empirical genetic principles over fragmented case-control studies.

Leveraging Iceland's Unique Demographics

deCODE genetics exploits Iceland's compact population of approximately 389,000 individuals as of January 2025, which provides substantial statistical power for genetic association studies despite the modest sample sizes relative to global cohorts. This isolation, resulting from historical settlement by a limited number of Norse and Celtic founders around 874 CE followed by minimal immigration, has produced a genetically homogeneous cohort with reduced allelic diversity and elevated frequencies of certain rare variants due to founder effects and genetic drift. Such structure amplifies the detectability of disease-linked alleles that might be too infrequent or diluted in more admixed populations, as evidenced by deCODE's identification of variants enriched in Icelanders but rare elsewhere. A cornerstone of this strategy is the genealogical database, constructed by deCODE in collaboration with Icelandic records, which traces lineages for the entire contemporary population back over 1,200 years to medieval sagas and church documents. This exhaustive pedigree resource, spanning multiple generations with minimal gaps, supports parametric linkage analyses that leverage familial inheritance patterns to localize genes more efficiently than sporadic case-control designs. By , deCODE had released a public version of the database, enabling verification and expansion while underpinning proprietary research into inheritance of . Integration with Iceland's centralized health registries—covering universal medical encounters, diagnoses, and outcomes since the early —further enhances phenotypic precision when linked to genotypic data from over 160,000 volunteers, representing more than half of adults. This population-scale approach, bolstered by the absence of private healthcare disparities, curtails selection biases inherent in voluntary cohorts elsewhere and facilitates imputation of ungenotyped variants across the populace using haplotype reference panels derived from whole-genome sequences of thousands. Consequently, deCODE achieves higher resolution in genome-wide association studies for common diseases like heart attack and cancer, where environmental confounders are standardized by the shared Nordic and healthcare access.

Scientific Approach and Methodology

Population-Scale Genetics

deCODE genetics utilizes the Icelandic population's unique characteristics—its relative homogeneity, small size of approximately 370,000, and detailed historical records—to conduct large-scale genetic analyses with minimal population stratification . The company has amassed genotypic data from over 160,000 volunteers, exceeding half of Iceland's adult , paired with electronic health records from the nation's universal healthcare system. This scale surpasses typical cohort studies, enabling detection of low-frequency variants that confer modest disease risks, which are often obscured in heterogeneous populations requiring millions of samples for equivalent power. A cornerstone of deCODE's methodology involves whole-genome sequencing (WGS) of targeted subsets, followed by imputation to broader genotyped arrays. For instance, initial WGS efforts sequenced 2,636 to a depth of 20×, uncovering over 20 million SNPs and 1.5 million indels, many rare and population-specific due to founder effects and bottlenecks in Iceland's settlement history. Genotypes are imputed across larger cohorts using a probabilistic framework that incorporates Iceland's comprehensive database, spanning the entire contemporary and extending over 1,000 years. This kinship-informed phasing achieves imputation accuracy exceeding 99% for common variants and substantial coverage for rares, effectively scaling sequenced data to population-level resolution without sequencing everyone. The approach mitigates reference bias and enhances variant discovery by combining short-read WGS with long-read sequencing for structural variants. In one application, long-read data from 3,622 enabled genome-wide of structural variants, revealing their and functional impacts at population scale, where traditional methods falter due to alignment challenges. Genealogical imputation further propagates these insights, allowing association studies with effective sample sizes in the hundreds of thousands for traits like susceptibility and quantitative phenotypes. This population-scale framework has powered analyses such as a complete recombination map derived from Icelandic pedigrees, resolving fine-scale crossover patterns across the . It also supports multiplexed , where protein levels from thousands of plasma samples are correlated with imputed genotypes to dissect regulatory networks. By prioritizing empirical variant frequencies over assumed universality, deCODE's methods underscore causal genetic contributions unmasked only through dense, related sampling, contrasting with sparser, unrelated cohorts prone to underpowered rare variant signals.

Integration of Genealogy, Genomes, and Health Data

deCODE genetics integrates Iceland's extensive with genomic and to enable population-scale genetic analyses that identify variants associated with disease risk. The company's database encompasses records for the entire present-day Icelandic of approximately 370,000 individuals, tracing familial relationships back over 1,000 years using historical church and civil documents. This database facilitates the construction of detailed pedigrees, which inform phasing and imputation, allowing deCODE to infer genotypes across unsequenced relatives with high accuracy. Genomic data integration involves whole-genome sequencing and from over 160,000 Icelandic volunteers—representing more than half of the adult —alongside data from 500,000 global participants. Techniques such as whole-genome sequencing at depths of 10x to 30x enable detection of both common and rare variants, while imputation leverages the genealogical structure to expand effective sample sizes, predicting missing genotypes based on shared ancestry and long-range unique to the Icelandic bottlenecked . For instance, sequencing efforts have included 12,803 high-coverage genomes as of , with ongoing expansions linking variants to phenotypes. Health data linkage draws from Iceland's universal healthcare system, providing longitudinal electronic medical records, death registries, and disease diagnoses for participants via encrypted national identifiers. This de-identified integration minimizes , as phenotypes are ascertained population-wide rather than through clinic-based sampling, enabling genome-wide association studies (GWAS) that correlate genetic variants with traits like or cancer incidence. The approach has proven effective in pinpointing low-frequency variants with large effect sizes, which are enriched in isolated populations like Iceland's due to founder effects and . By cross-referencing these datasets, deCODE conducts through and family-based analyses, distinguishing correlation from causation in .

Major Discoveries and Contributions

Early Genetic Associations ()

In its formative years following establishment in , deCODE genetics employed linkage analysis within extended Icelandic pedigrees, integrating dense , genealogical records, and phenotypic data to pinpoint susceptibility loci for common diseases. This approach yielded initial genetic associations primarily through positional cloning, contrasting with later genome-wide association studies (GWAS). By the mid-, deCODE had mapped variants contributing to risk in multiple conditions, including neurological, cardiovascular, and metabolic disorders, though some early linkages faced replication challenges in diverse populations due to Iceland's genetic homogeneity. A landmark early finding was the mapping of a susceptibility locus for late-onset idiopathic on 1p32, reported in October 2001 and detailed in a 2002 study analyzing 118 Icelandic families; the locus explained approximately 10-15% of familial in the cohort, with follow-up implicating the pathway indirectly through . In 2003, deCODE identified sequence variants in the PDE4D on 5q12 as conferring for ischemic , with specific haplotypes increasing odds by up to 1.3-fold in Icelandic cases; this marked the first linked to common stroke forms, validated in initial replication cohorts but later showing variable effect sizes across ethnicities. Concurrent efforts uncovered a susceptibility variant on chromosome 10q near the TCF7L2 in 2003, where a repeat influenced transcription and elevated risk by 1.4- to 2-fold in carriers, a finding robustly replicated globally and highlighting non-coding regulatory mechanisms. Cardiovascular associations followed, including a 2004 report of haplotypes in the ALOX5AP (encoding 5-lipoxygenase-activating protein) raising risk by 1.2- to 1.8-fold via pathway modulation, derived from 1,000+ Icelandic cases. By 2007, a common variant at 9p21 (near CDKN2A/B) was associated with , conferring up to 30% increased odds per allele in deCODE's analysis of over 4,600 cases, ushering in common variant discoveries pre-GWAS era. These efforts collectively positioned deCODE as a pioneer in population-based , amassing evidence for polygenic contributions to despite critiques of limited generalizability beyond founder populations.

Advancements in Disease Risk Factors

deCODE genetics has advanced the understanding of risk factors through large-scale genome-wide association studies (GWAS) and whole-genome sequencing (WGS) leveraging Iceland's genetically isolated population, identifying hundreds of sequence variants associated with common diseases. Early efforts in the 2000s focused on common variants, such as those linked to , , and , establishing genetic correlations with cardiovascular outcomes. These findings demonstrated that polygenic scores, aggregating multiple low-effect variants, better predict disease susceptibility than single loci, shifting paradigms from monogenic to multifactorial causation. Subsequent advancements incorporated rare variants via WGS, revealing high-penetrance loss-of-function mutations, such as in ITSN1 for , where carriers exhibited up to 6-fold increased . For , deCODE's meta-analyses across ancestries identified loci influencing ischemic subtypes, informing polygenic tools with improved cross-population transferability. In , sequence variants tied to length and B-cell markers were linked to predisposition, elucidating causal pathways beyond GWAS signals. Recent work has emphasized epistatic interactions and gene-environment effects, as in where variants in multiple loci synergize with lifestyle factors to modulate risk, explaining heterogeneity in phenotypic expression. Similarly, BMI-associated variants mediate disease risk primarily through rather than direct , with confirming causality in metabolic disorders. These insights, derived from over 500,000 Icelandic genomes, have enhanced polygenic risk modeling for conditions like and nonalcoholic , prioritizing variants with functional annotations for therapeutic targeting.

Recent Innovations and Publications (2010s–2025)

In the 2010s, deCODE genetics expanded its population-scale genotyping and sequencing efforts, yielding genome-wide association studies (GWAS) that pinpointed novel risk loci for cardiovascular conditions, including 13 susceptibility variants for identified across over 100,000 individuals. Similarly, rare variants in genes such as MYH6 were linked to elevated risk of sick sinus syndrome, informing electrophysiological mechanisms of arrhythmias. These findings leveraged Iceland's genealogical depth and nearly complete population coverage to achieve high statistical power, distinguishing deCODE's approach from smaller cohort studies elsewhere. By mid-decade, integrations of whole-genome sequencing with phenotypic data facilitated discoveries in metabolic traits, such as variants influencing susceptibility. The 2010s also saw methodological innovations, including refined imputation techniques and the 2010 publication of a high-resolution recombination map derived from Icelandic pedigrees, which enhanced fine-mapping of causal variants across the . Post-2012 acquisition by , deCODE's pipeline shifted toward actionable genetics for drug target validation, exemplified by gain-of-function mutations in LDLR associated with lifelong reductions in LDL levels, supporting therapeutic modulation strategies. Publications emphasized rare variants with large effect sizes, contrasting with common variant polygenicity dominant in earlier GWAS, thus providing causal insights into heterogeneity. Entering the 2020s, deCODE's whole-genome sequencing of over 60,000 enabled multi-omics integrations, such as a 2021 study merging plasma with across hundreds of thousands of samples to nominate protein-trait associations for 3,600+ traits. Key disease-specific advances included a 2021 GWAS of 1.1 million individuals identifying 75 risk loci for , prioritizing targets like TREM2. In nonalcoholic , a 2022 multi-omics analysis revealed pathway enrichments in and , validated via . Rare variant analyses dominated later publications, with a 2023 study uncovering loss-of-function variants in HECTD2 and AKAP11 conferring substantial risk for major depression, affecting up to 2% of cases. subtypes were dissected in 2023 via variants with odds ratios exceeding 2, implicating neuronal signaling pathways. A 2023 New England Journal of Medicine report on Icelandic longevity linked actionable genotypes—such as those in BRCA2 for cancer risk—to lifespan reductions of up to 3 years per carrier status. By 2024–2025, deCODE produced foundational genomic resources, including a complete high-resolution recombination map from 173,000+ Icelandic samples, resolving meiotic crossover patterns at resolution to aid modeling. Innovations in reproductive highlighted lethal de novo mutations causing ~1 in 136 early losses, quantified via sequenced miscarriage tissues. associations with rare loss-of-function variants in two genes were reported in 2025, alongside a missense variant in FRS3 protecting against by lowering BMI. These outputs underscore deCODE's sustained productivity in rare variant discovery, with over 500 publications in high-impact journals since 2010, prioritizing empirical variant effect sizes over polygenic scores for .

Business Trajectory

Initial Funding, Partnerships, and Expansion

deCODE genetics secured initial venture capital funding, including a seed round in 1998 led by Atlas Venture, to launch operations following its founding in 1996. A landmark partnership was established in February 1998 with Hoffmann-La Roche, committing up to $200 million over five years for gene discovery in common diseases such as osteoarthritis, schizophrenia, and rheumatoid arthritis; the deal encompassed equity investments, research funding, and milestone payments tied to target validation. This alliance provided critical resources for early research, yielding mappings of disease-linked genes by 1999–2001. In July 2000, deCODE completed an on , raising $173 million by issuing 9.6 million shares at $18 each, which supported operational scaling amid a volatile biotech market. These financial inflows, combined with the collaboration, facilitated expansion through recruitment of international geneticists and development of infrastructure tailored to Iceland's genealogical and records. By the early , deCODE had forged additional pharmaceutical partnerships, including with Merck and , broadening its scope to multiple therapeutic areas and accelerating discovery efforts.

Financial Crisis and Bankruptcy (2009)

deCODE genetics faced escalating financial pressures starting in late 2008, amid chronic unprofitability and the broader collapse of Iceland's banking system in October 2008, which nationalized the country's major banks and triggered a severe economic contraction. The company, which had accumulated losses over 13 years of operations due to high research and development costs—including maintenance of its extensive biobank—and stalled progress in commercializing genetic discoveries into viable therapeutics, struggled to service its debt obligations. Revenue from direct-to-consumer genetic testing services, launched via deCODEme in 2007, remained insufficient to offset expenses, while partnerships with pharmaceutical firms provided limited inflows compared to outlays. Efforts to restructure , ongoing for over a year prior to the filing, included negotiations with creditors and attempts to secure new financing, but these failed as the company could not meet payments on its senior convertible notes and incurred losses from investments in ' auction-rate securities during the 2008 . Although executives did not attribute the crisis directly to Iceland's banking failures, the interconnectedness of deCODE's financing with domestic lenders amplified liquidity constraints in an environment where foreign capital dried up. By early 2009, the firm's had plummeted, reflecting investor skepticism about its path to profitability in population-scale . On November 17, 2009, deCODE genetics, Inc. filed for Chapter 11 protection in the U.S. Bankruptcy Court for the District of , listing assets of approximately $69.9 million against liabilities of $313.9 million. The filing enabled the company to continue limited operations while pursuing an auction sale of substantially all assets, including its Icelandic biobank containing genetic, genealogical, and health data from about 140,000 individuals—roughly half of Iceland's population. A bid was arranged with Saga Investments LLC, a U.S.-based entity, aiming for asset transfer by January 2010, though common stockholders faced likely total wipeout with no recovery anticipated. CEO Kári Stefánsson described the venture as launched "about five years too early," emphasizing that the underlying scientific advancements in would endure beyond the commercial setback.

Acquisition by Amgen and Restructuring (2012)

In December 2012, Inc. announced its acquisition of deCODE genetics, the Icelandic genomics company, for $415 million in an all-cash transaction, marking a significant shift following deCODE's financial recovery from its 2009 bankruptcy. The deal, unanimously approved by 's , required no regulatory approvals and closed by the end of the year, subject only to customary adjustments. This purchase valued deCODE at approximately $5.25 per share, providing with access to deCODE's extensive database of over 500,000 genotyped and sequenced Icelandic individuals, integrated with genealogical and medical records. The acquisition followed deCODE's restructuring after its November 2009 Chapter 11 bankruptcy filing, which was initiated to facilitate an orderly asset sale amid liquidity constraints from the global financial crisis. Post-bankruptcy, deCODE emerged under new ownership, including financing from investors such as Arch Venture Partners and Venture Partners, who provided $11 million in debtor-in-possession funding that contributed to the eventual sale price. Restructured as deCODE Genetics ehf., the company stabilized operations in Reykjavik, retaining its core scientific team and continuing genome-wide association studies without major layoffs or asset liquidations during the interim period. By 2012, this leaner structure—focused on high-value genetic data assets rather than expansive —made deCODE an attractive target for , which sought to bolster early-stage target validation using population-scale . Amgen's strategic rationale centered on leveraging deCODE's proprietary Icelandic cohort to accelerate identification of novel disease targets, particularly for cardiovascular, oncology, and neuroscience indications, where deCODE had demonstrated validated genetic variants. deCODE's founder and CEO, Kári Stefánsson, emphasized that the acquisition would preserve the company's research independence, allowing it to maintain its Reykjavik-based operations as a wholly owned without immediate shifts in personnel or methodology. This integration enabled Amgen to apply deCODE's findings to its , though initial post-acquisition efforts focused on data harmonization rather than broad operational overhauls. The transaction thus represented not a dissolution but a repositioning of deCODE within a larger biotech framework, sustaining its contributions to while addressing prior financial vulnerabilities.

Controversies and Criticisms

deCODE genetics' approach to data collection relied on Iceland's centralized system, enabled by the 1998 Health Sector Database Act, which authorized the creation of a national database integrating medical histories, genealogical , and genetic information under a presumed model with an provision. Under this framework, individuals' data were included by default unless they actively registered an , a process requiring submission of a form to the Data Protection Authority; explicit prior was not mandated for database construction, distinguishing it from models requiring affirmative participation. For direct genetic sample collection and , deCODE required explicit written from participants, aligning with stricter protocols for biological materials. Privacy concerns emerged prominently during the project's , fueled by the risks of re-identification in Iceland's homogeneous of approximately 280,000 in , where shared ancestry amplifies the identifiability of anonymized through linkages. Critics, including ethicists and advocacy groups, argued that the mechanism inadequately protected , as many citizens remained unaware of the initiative or its implications, with initial opt-out rates below 1% despite public debates; by 2004, around 20,000 had opted out, reflecting growing unease over commercial exploitation of national resources without granular control. The absence of oversight to enforce further intensified scrutiny, as the law granted deCODE exclusive access without independent review of individual usage. Proponents, including deCODE's leadership, defended the model as ethically robust, claiming it exceeded data protection standards through encryption, pseudonymization, and secure processing, while emphasizing benefits from population-scale insights that individual might hinder. However, opponents highlighted systemic vulnerabilities, such as potential insurer or employer access to inferred risks from genealogical-genetic correlations, and the ethical tension of privatizing a de facto national , where low burdens shifted responsibility onto individuals rather than researchers. Legal challenges, including lawsuits from advocates in the early 2000s, tested these practices but largely upheld the framework, though they underscored ongoing debates about balancing innovation with rights in closed populations. Post-2009 and Amgen's 2012 acquisition, deCODE maintained options and enhanced data policies, but foundational critiques persisted in academic discourse. deCODE genetics faced significant legal hurdles stemming from Iceland's 1998 Act on a Health Sector Database, which authorized the company to compile and commercialize a centralized repository of anonymized medical records linked to the national genealogy database, presuming consent from citizens unless they explicitly opted out. This opt-out model was challenged as insufficient for protecting individual privacy, particularly in Iceland's small population of approximately 300,000, where familial connections enable high risks of re-identification even with pseudonymization. Opponents argued that the legislation bypassed standard ethical requirements for informed consent in genetic research, prioritizing commercial efficiency over participant autonomy. A pivotal legal setback occurred in April 2004 when Iceland's ruled that transferring the health records of a deceased —whose family had objected—to deCODE's database violated protections under Article 71 of the Icelandic Constitution, effectively stalling the project's implementation. The court emphasized that presumed consent did not override the right to control sensitive posthumously, highlighting tensions between national innovation goals and . This decision underscored broader ethical critiques that deCODE's model commodified public health data without adequate safeguards against misuse, such as by insurers or employers, despite subsequent U.S. legislative protections like GINA in 2008. Further regulatory obstacles arose in June 2013, when Iceland's Data Protection Authority denied deCODE permission to link imputed genotypes—derived from aggregated population data—to individual without explicit , citing risks of inferring personal genetic information indirectly. Ethically, this practice raised concerns about "imputed consent," where deCODE could reconstruct profiles of non-participants using relatives' data, potentially eroding trust in biobanking and exacerbating inequities in benefit-sharing from discoveries commercialized by private entities. Critics, including bioethicists, contended that such approaches favored technical prowess over relational ethics in kinship-dense societies, though deCODE maintained that anonymization and provisions aligned with evolving international standards.

Debates on Data Monopoly and Public Benefit

The Icelandic government's 1998 Health Sector Database Act granted deCODE Genetics an exclusive 12-year to compile and operate a aggregating the country's electronic records, medical histories, and genealogical from nearly all 275,000 citizens at the time. Proponents, including deCODE's founder Kári Stefánsson, contended that this monopoly would enable rapid gene-disease associations, yielding advancements such as targeted therapies and preventive measures, with revenues potentially reinvested into Icelandic research. Critics, including local scientists, ethicists, and physicians, argued that the arrangement privatized a national resource, creating a commercial stranglehold that barred academic and competing firms from accessing the , thereby hindering broader scientific progress and public oversight. Opposition highlighted risks of insufficient public reciprocity, as deCODE's for-profit model prioritized patentable discoveries for shareholders over open dissemination, potentially exporting genetic insights without commensurate benefits returning to whose fueled the enterprise. The presumed framework—allowing rather than requiring affirmative participation—intensified debates, with detractors asserting it undermined individual autonomy and enabled deCODE to amass a de facto genetic monopoly without rigorous ethical review or research plans. In 2003, Iceland's invalidated the Act, ruling it violated constitutional protections by presuming for sensitive linkage without explicit individual approval, preventing the full database's realization. deCODE subsequently shifted to a volunteer-recruited , over 500,000 by the 2020s through , which mitigated some monopoly concerns but sustained critiques of exclusivity. Following Amgen's acquisition for $415 million, ownership transferred to a U.S. multinational, prompting renewed questions about whether proprietary control limits with Icelandic institutions or global open-access initiatives, despite deCODE's publication of hundreds of peer-reviewed findings on disease variants. Advocates of the model emphasize tangible outputs, such as variants linked to cardiovascular risks informing , as evidence of net public gain outweighing exclusivity drawbacks. Skeptics counter that systemic barriers to persist, echoing early fears that concentrated control favors private valorization over equitable, population-level benefits.

Public Health Applications

Response to COVID-19 Pandemic

deCODE genetics, in collaboration with Icelandic public health authorities and under Amgen's ownership, played a pivotal role in Iceland's genomic surveillance of , sequencing viral genomes from infected individuals to map transmission dynamics and origins. Beginning in early , the company sequenced the virus from over 600 cases by , constructing phylogenetic trees of haplotypes to reveal multiple independent introductions into , primarily from high-risk groups like travelers, with subsequent community spread occurring outside these clusters. This effort supported Iceland's aggressive testing and contact-tracing strategy, contributing to one of the lowest mortality rates globally, at approximately 0.3 deaths per 100,000 by mid-2020. A landmark study published on April 14, 2020, in the New England Journal of Medicine, sponsored by deCODE, analyzed data from over 13,000 diagnostic tests and sequenced 362 viral genomes, estimating a true prevalence of about 0.8% through random screening of 19,764 individuals. The screening revealed that only 48.4% of infections were detected via PCR testing, underscoring the value of serological surveys for undetected cases, while genomic data confirmed diverse strains with shifting dominance, aiding in real-time outbreak control. deCODE's infrastructure, leveraging its population-based and high-throughput sequencing, enabled rapid turnaround, with viral genomes sequenced alongside host samples to differentiate imported from domestic transmission. Beyond viral tracking, deCODE investigated host genetic factors influencing outcomes, identifying variants associated with severe disease through genome-wide association studies on Icelandic cohorts. A September 2020 analysis showed that antibody titers remained stable over four months post-infection, informing immunity duration estimates without relying on unverified assumptions of rapid waning. Later reconstructions, such as a 2022 study of Iceland's third wave, integrated deCODE's sequencing of 2,522 cases with to model transmission trees, demonstrating that age-targeted could have averted more infections than random strategies, based on empirical lineage data rather than simulations alone. These contributions exemplified private-public synergy, with deCODE providing genomic expertise to complement national testing at facilities like Landspitali University Hospital. deCODE's work extended to broader epidemiological insights, including molecular benchmarks for epidemic control published in in June 2021, which used Icelandic data to validate genomic as a tool for assessing intervention efficacy, such as border screenings that captured 95% of introductions. This approach prioritized from sequence-linked cases over correlative metrics, highlighting how Iceland's cohesive response—bolstered by deCODE's capacity—limited , with reproduction numbers dropping below 1 by April 2020.

Broader Implications for Epidemiology

deCODE genetics' population-based genomic studies have advanced epidemiological understanding by integrating high-resolution genetic data with longitudinal health records, enabling the identification of causal and polygenic contributions to disease etiology. In , where nearly half the population has consented to participation, deCODE has sequenced over 500,000 individuals, linking variants to phenotypes like cardiovascular events and cancer incidence through nationwide registries. This approach reveals estimates and gene-environment interactions, as seen in studies of de novo mutations increasing with paternal age, which explain variations in rates independent of familial inheritance. Such findings shift from correlative risk factors to mechanistic insights, facilitating analyses that distinguish genetic from environmental drivers of disease progression. A key implication lies in enhanced risk stratification for management. deCODE's genome-wide association studies (GWAS) have pinpointed variants modulating susceptibility, such as those in clonal hematopoiesis—a premalignant condition affecting up to 10% of older adults—where specific mutations predict progression to myeloid neoplasms with defined epidemiological patterns. Polygenic risk scores (PRS) derived from these efforts, combined with clinical covariates, outperform single-marker predictions for outcomes like and heart , though deCODE data underscore limitations in cross-ancestry transferability due to Iceland's genetic homogeneity. Moreover, analyses of BMI-associated variants demonstrate partial of risks (e.g., ) through adiposity, informing targeted interventions beyond broad population averages. These tools support prospective cohort designs that incorporate genomic data, improving predictive accuracy over traditional epidemiological models reliant on lifestyle and demographic factors alone. Broader epidemiological paradigms benefit from deCODE's emphasis on rare variants and somatic events, which traditional surveys overlook. For clonal processes, deCODE's whole-genome sequencing of 45,699 quantified burdens and genes, yielding incidence rates and age-specific prevalences that refine models of cancer precursors and inform screening protocols. This extends to applications, where genetic insights calibrate disease forecasting; for example, protein measurements from deCODE cohorts predict all-cause mortality more effectively than PRS, highlighting the need for multi-omics integration in systems. Critically, while Iceland's isolated population accelerates variant discovery, deCODE's methodologies—emphasizing consent-based biobanks and imputation—offer scalable blueprints for global , though replication in diverse cohorts remains essential to mitigate ascertainment biases inherent in founder populations.

Current Operations and Outlook

Integration into Amgen's Portfolio

Amgen completed its acquisition of deCODE genetics on December 31, 2012, for an upfront payment of $173 million plus up to $242 million in milestone payments, establishing deCODE as a wholly-owned focused on research. This integration enabled Amgen to incorporate deCODE's proprietary and data from approximately 140,000 —representing a significant portion of the nation's —into its broader framework, enhancing target identification and validation for novel therapeutics. deCODE's operations remained centered in Reykjavik, preserving its specialized expertise in population-based while aligning with Amgen's emphasis on genetics-driven . Post-acquisition, deCODE's discovery engine has directly supported Amgen's pipeline by uncovering genetic variants linked to s such as cardiovascular conditions and , informing the prioritization of drug candidates with validated human genetic evidence. For example, deCODE's research identified variants in the ASGR1 influencing levels and heart risk, providing a rationale for potential inhibitory therapies to reduce non-HDL . This approach has shifted Amgen's strategy toward as a core pillar, integrating deCODE's findings with Amgen's biologics and small-molecule platforms to accelerate progression from discovery to clinical stages. By , the collaboration had expanded beyond early-stage research into development, yielding insights that bolster Amgen's targeted treatment advancements. The subsidiary's role has further evolved through strategic partnerships, such as the 2019 collaboration with Intermountain Healthcare to analyze DNA from 500,000 individuals, aiming to link to outcomes and refine Amgen's omics-based methodologies. As of 2025, deCODE continues to drive Amgen's integration of with for predictive modeling in R&D, maintaining its status as a key asset despite Amgen's occasional shifts in broader portfolio priorities. This sustained integration underscores deCODE's value in providing causal genetic insights, though outcomes remain dependent on translating discoveries into approved therapies amid industry challenges in validation and commercialization.

Leadership Transitions (2025)

On May 2, 2025, deCODE genetics announced the end of Kari Stefánsson's tenure as founder and , a position he had held since establishing the company in 1996. The announcement described the change as a natural conclusion to his leadership, emphasizing deCODE's ongoing commitment to scientific excellence in as a of . In conjunction with Stefánsson's departure, Unnur Þorsteinsdóttir, Ph.D., and Patrick Sulem, M.D., were appointed as co-managing directors to oversee operations during the transition period. Þorsteinsdóttir, who joined deCODE in 2000, previously served as Executive Director of Genetic Research, contributing to key advancements in genomic sequencing and epidemiological studies leveraging Iceland's population database. Sulem, a deCODE employee since 2002, had led clinical sequencing efforts, focusing on translating genetic data into therapeutic insights for Amgen's portfolio. No specific timeline for the transition or permanent CEO appointment was detailed in the official statement. Stefánsson publicly contested the characterization of his exit, stating in interviews that he was summarily dismissed by without prior notice, describing the decision as an attempt to "domesticate" his independent approach after nearly three decades at the helm. This claim highlights tensions between deCODE's foundational entrepreneurial culture and 's corporate oversight since the 2012 acquisition, though the company provided no further commentary on the matter. The leadership shift occurs amid deCODE's continued integration into 's rare disease and pipelines, with no reported disruptions to ongoing .

Future Research Directions

deCODE genetics, as an subsidiary, is poised to expand its genomic research into multi-omics integration, combining whole-genome sequencing with and other data layers to pinpoint causal variants for complex diseases. This approach aims to enhance target validation for 's therapeutic pipeline, building on collaborations that analyze diverse global populations to uncover rare variants influencing disease susceptibility. Recent advancements, such as the 2025 publication of a complete recombination map, underscore potential directions in refining models for polygenic trait prediction, enabling more precise risk stratification in areas like cardiovascular and metabolic disorders. Future efforts are likely to prioritize translating genetic discoveries into clinical applications, including obesity-related therapies informed by population-scale studies of and variants. deCODE's Icelandic , augmented by international datasets, will support longitudinal analyses to dissect gene-environment interactions, particularly for age-related conditions. This shift from discovery to development aligns with Amgen's strategy, as evidenced by ongoing validation of targets like those in heart disease protection pathways. Emerging research trajectories include investigating somatic mutations in early pregnancy loss and their implications for reproductive health interventions, as highlighted in deCODE's 2025 publication on sequence diversity. With Amgen's resources, deCODE may accelerate AI-driven variant prioritization to address undruggable targets, fostering novel modalities like editing or small-molecule inhibitors derived from evidence. These directions emphasize empirical validation over hypothesis-driven biases, leveraging deCODE's track record of over 1,000 sequence associated with 200+ traits.

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