In Context
ENIGMA: crowdsourcing meets neuroscience A network of researchers are pooling their resources to better understand how our genetic make-up affects brain structure and function. Dara Mohammadi asks what this might mean for our understanding of brain disease.
Published Online March 24, 2015 http://dx.doi.org/10.1016/ S1474-4422(15)00005-8 For more on ENIGMA see http:// www.enigma.ini.usc.edu For more on genetic effects on brain structure see Nature 2015; published online Jan 21. DOI:10.1038/nature14101
462
How do our genetic profiles affect our brains? And what relation do the resulting phenotypes have with complex neurological and psychiatric disorders? Answers to these seemingly fundamental questions, says Paul Thompson, professor of neurology at the University of Southern California, CA, USA, lie beyond the reach of most researchers, mainly because of the expense of doing imaging and genome-wide association studies (GWAS) in a large enough population to tease out the often subtle genetic effects on the brain. “Say you and I wanted to do an imaging genomics study of 30 thousand people”, he says. “We’d go to the National Institutes of Health [NIH] in the States or the Wellcome Trust in the UK and they would laugh at us—they’d say it is too expensive and that it would cost $30 million in scans alone.” In 2009, Thompson and Nick Martin, professor of genetic epidemiology at the Queensland Institute of Medical Research, QLD, Australia, came up with a solution that is now starting to provide answers. They co-founded the Enhancing Neuroimaging and Genetics through Meta-Analysis (ENIGMA) Network—named after the code-breaking machine used by Alan Turing and colleagues during the Second World War. The network brings together researchers who are interested in cracking the thusfar elusive genotype–phenotype relations in neurological and psychiatric disorders. It boasts impressive numbers: it includes 300 scientists from 185 institutions in 33 countries who can pore through existing genomic, imaging, and clinical data from a combined 30 000 patients.
“It’s crowdsourcing meets neuroscience”, says Thompson of the Network. “One of the questions we asked most recently was a very simple one: is there anything in our genetic code that affects the structure of the brain?” Researchers pulled together brain scans from 30 000 patients, with the corresponding 30 000 sets of genetic data, and searched to see if people with common variations at different loci had different subcortical brain structures.
”Participation in big science projects such as ENIGMA can be a real boon for researchers and patients in low and middleincome countries.” Their findings, published in January, showed evidence of five novel genetic variants that affect the putamen and caudate nucleus, and of three other genetic loci known to affect hippocampal and intracranial volume. These findings, they say, provide insights that could help to elucidate mechanisms of neuropsychiatric dysfunction. “It’s an interesting way of doing gene discovery”, says Thompson. “But it’s not the end of the story. People will now have to go and do studies in, say, transgenic mice or look in other genetic databases to see if these genes tilt the scales towards autism or Alzheimer’s disease or another mental condition.” Martin is similarly excited. “I think identifying these eight hotspots is a great example of what can be achieved by this way of doing science”, he says. “What do these big hits mean for psychiatric disease? We don’t know, but the great thing about this work, like any good science, is that every
result leads onto a whole new set of questions and spawns a whole new set of projects—people are squirreling away at these hits doing functional analyses and trying to work out what this could mean for psychiatric and other behavioural conditions.” The ENIGMA working groups target ten major brain diseases: schizophrenia, bipolar disorder, major depressive disorders, attention deficit hyperactivity disorder, obsessive compulsive disorder, autism, 22q deletion syndrome, neuroinfection with HIV, post-traumatic stress disorder, and addiction. To join, researchers need to contribute only brain scans to the pool. “Obviously, if they have genetic data and clinical data as well, they can be involved in more projects”, says Thompson. Thompson’s office is the administrative fulcrum of the network. Interested researchers email the network, and their request is directed to one of 30 working groups, where primary investigators, who are often field-leaders, orchestrate individual lines of research. Subgroups then bud off to allow more targeted questioning, with each collaborating centre providing the computing and man-power needed for further analyses. “People can submit their data for analysis, or join the teams of people analysing it”, says Thompson, “in either case they’ll get to contribute to the papers that come out of the analyses. Most commonly they help to analyse their own data, but we can do it for them if they are short of time or manpower.” “It’s a very democratic process”, says Martin, explaining that together researchers decide on questions, a common protocol, and then a deadline by which analyses must www.thelancet.com/neurology Vol 14 May 2015
In Context
be run. Analyses are done using algorithms designed and sent out by Thompson’s team. Use of these algorithms means that raw data do not have to leave the four walls of any research centre, which removes the logistical and administrative headache of international data sharing. “As in any meta-analysis”, adds Martin, “there are assumptions and loss of accuracy along the way but basically he [Thompson] has solved the problem of how you bring these scans together. They began by doing structural scans and the problem now is working on trying to do the same for connectivity scans, and then the big challenge is doing it for fMRI.” Thompson heads up a working group called the ENIGMA Center for Worldwide Medicine, Imaging and Genomics, which last year received US$11 million in funding from the NIH’s Big Data to Knowledge initiative. Members of this group develop and refine algorithms to analyse brain maps, clinical measures, and signals, and statistically relate these measures to genomic, environmental, epidemiological, and clinical outcome data. Two subgroups of neuroimaging and statistical genetics experts are developing techniques for large-scale data analysis, including diffusion tensor imaging and connectomics. “It’s an alliance to make it easier for others to do science”, says Thompson of his group. An example of collaboration facilitated by their work is the coming together of researchers studying connectome mapping and those interested in bipolar disorder and schizophrenia. “These are very different groups of people who have never worked together before”, he explains. “But they’ll use the ENIGMA protocol to map connections in all the scans they have on schizophrenia and bipolar [disorder] to ask whether the brain is wired differently if you have either of these diseases.” Difficulties, he says, lie in the fact that not all scans are the same. Many images are from standard 1·5 Tesla www.thelancet.com/neurology Vol 14 May 2015
scanners, while others are collected with advanced scanners that use magnetic fields as high as 4 Tesla: “the connectome group has been working for 6 years on harmonising this information across imaging centres. Its potential is very exciting.” Dan Stein, professor of psychiatry and mental health at the University of Cape Town, South Africa, coheads the obsessive compulsive disorder and HIV working groups in ENIGMA. His ENIGMA HIV group is investigating, among other questions, the relation between CD4 counts and brain structure in HIV. He sees the possibility of such global collaboration as a real strongpoint of ENIGMA. “The vast majority of neuropsychiatric research is conducted in high-income countries”, he says, “but the majority of people suffering from these conditions live elsewhere. ENIGMA has developed pipelines that allow researchers in less well-resourced centres to participate in its work. Participation in big science projects such as ENIGMA can be a real boon for researchers and patients in low and middle income countries.” About 10% of ENIGMA’s data come from such countries, including South Africa, Thailand, and Cambodia. Martin adds that: “It’s a remarkable example of the change in the zeitgeist of science. From all these big professors competing with each other, trying to do each other down, to taking the leap to realising that there’s actually a lot more to be gained by being cooperative.” Max Wiznitzer, professor of paediatric neurology at the Case Western Reserve University and the Rainbow Babies and Children’s Hospital, OH, USA, is not part of the ENIGMA network. “I find it to be an interesting exercise”, he says. “In neurology we’ve been doing a lot of gene-identification studies and trying to relate genetic findings to clinical phenotypes, and what ENIGMA provided is an important intermediary step between these two things. But it’s not going to answer all the questions.”
The questions he says any such macro-level studies can’t answer are those to do with problems associated with abnormalities at the synapse level or in morphology, such as dysplasia. “Not all disorders can be seen on MRI”, he says, “but they can definitely make progress in some disorders. The benefits obviously need to be balanced against use of limited resources and costs, and we need to ensure there is appropriate interpretation of data to make sure we’re not too enthusiastic and don’t jump to incorrect conclusions as we’ve seen before with other GWAS findings.” Russell Poldrack, a professor of psychology at Stanford University, CA, USA, also gives the project “a big thumbs up” with caveats. “I don’t know if we still have a good idea of, mechanistically, what it means for a gene or group of genes to be associated with a particular aspect of the structure of the brain”, he says, explaining that, in previous studies of brain structure, sometimes bigger is better and sometimes it is worse, and in a lot of cases more targeted, hypothesis-driven research is also needed. “Having said that, clearly they’re finding replicable associations and one would hope that that’s a start towards doing some real biology and finding out what it all actually means.”
For more on the Big Data to Knowledge initiative see http:// bd2k.nih.gov
Dara Mohammadi
Paul Thompson and Nick Martin
463
ENIGMA: crowdsourcing meets neuroscience A network of researchers are pooling their resources to better understand how our genetic make-up affects brain structure and function. Dara Mohammadi asks what this might mean for our understanding of brain disease.
Published Online March 24, 2015 http://dx.doi.org/10.1016/ S1474-4422(15)00005-8 For more on ENIGMA see http:// www.enigma.ini.usc.edu For more on genetic effects on brain structure see Nature 2015; published online Jan 21. DOI:10.1038/nature14101
462
How do our genetic profiles affect our brains? And what relation do the resulting phenotypes have with complex neurological and psychiatric disorders? Answers to these seemingly fundamental questions, says Paul Thompson, professor of neurology at the University of Southern California, CA, USA, lie beyond the reach of most researchers, mainly because of the expense of doing imaging and genome-wide association studies (GWAS) in a large enough population to tease out the often subtle genetic effects on the brain. “Say you and I wanted to do an imaging genomics study of 30 thousand people”, he says. “We’d go to the National Institutes of Health [NIH] in the States or the Wellcome Trust in the UK and they would laugh at us—they’d say it is too expensive and that it would cost $30 million in scans alone.” In 2009, Thompson and Nick Martin, professor of genetic epidemiology at the Queensland Institute of Medical Research, QLD, Australia, came up with a solution that is now starting to provide answers. They co-founded the Enhancing Neuroimaging and Genetics through Meta-Analysis (ENIGMA) Network—named after the code-breaking machine used by Alan Turing and colleagues during the Second World War. The network brings together researchers who are interested in cracking the thusfar elusive genotype–phenotype relations in neurological and psychiatric disorders. It boasts impressive numbers: it includes 300 scientists from 185 institutions in 33 countries who can pore through existing genomic, imaging, and clinical data from a combined 30 000 patients.
“It’s crowdsourcing meets neuroscience”, says Thompson of the Network. “One of the questions we asked most recently was a very simple one: is there anything in our genetic code that affects the structure of the brain?” Researchers pulled together brain scans from 30 000 patients, with the corresponding 30 000 sets of genetic data, and searched to see if people with common variations at different loci had different subcortical brain structures.
”Participation in big science projects such as ENIGMA can be a real boon for researchers and patients in low and middleincome countries.” Their findings, published in January, showed evidence of five novel genetic variants that affect the putamen and caudate nucleus, and of three other genetic loci known to affect hippocampal and intracranial volume. These findings, they say, provide insights that could help to elucidate mechanisms of neuropsychiatric dysfunction. “It’s an interesting way of doing gene discovery”, says Thompson. “But it’s not the end of the story. People will now have to go and do studies in, say, transgenic mice or look in other genetic databases to see if these genes tilt the scales towards autism or Alzheimer’s disease or another mental condition.” Martin is similarly excited. “I think identifying these eight hotspots is a great example of what can be achieved by this way of doing science”, he says. “What do these big hits mean for psychiatric disease? We don’t know, but the great thing about this work, like any good science, is that every
result leads onto a whole new set of questions and spawns a whole new set of projects—people are squirreling away at these hits doing functional analyses and trying to work out what this could mean for psychiatric and other behavioural conditions.” The ENIGMA working groups target ten major brain diseases: schizophrenia, bipolar disorder, major depressive disorders, attention deficit hyperactivity disorder, obsessive compulsive disorder, autism, 22q deletion syndrome, neuroinfection with HIV, post-traumatic stress disorder, and addiction. To join, researchers need to contribute only brain scans to the pool. “Obviously, if they have genetic data and clinical data as well, they can be involved in more projects”, says Thompson. Thompson’s office is the administrative fulcrum of the network. Interested researchers email the network, and their request is directed to one of 30 working groups, where primary investigators, who are often field-leaders, orchestrate individual lines of research. Subgroups then bud off to allow more targeted questioning, with each collaborating centre providing the computing and man-power needed for further analyses. “People can submit their data for analysis, or join the teams of people analysing it”, says Thompson, “in either case they’ll get to contribute to the papers that come out of the analyses. Most commonly they help to analyse their own data, but we can do it for them if they are short of time or manpower.” “It’s a very democratic process”, says Martin, explaining that together researchers decide on questions, a common protocol, and then a deadline by which analyses must www.thelancet.com/neurology Vol 14 May 2015
In Context
be run. Analyses are done using algorithms designed and sent out by Thompson’s team. Use of these algorithms means that raw data do not have to leave the four walls of any research centre, which removes the logistical and administrative headache of international data sharing. “As in any meta-analysis”, adds Martin, “there are assumptions and loss of accuracy along the way but basically he [Thompson] has solved the problem of how you bring these scans together. They began by doing structural scans and the problem now is working on trying to do the same for connectivity scans, and then the big challenge is doing it for fMRI.” Thompson heads up a working group called the ENIGMA Center for Worldwide Medicine, Imaging and Genomics, which last year received US$11 million in funding from the NIH’s Big Data to Knowledge initiative. Members of this group develop and refine algorithms to analyse brain maps, clinical measures, and signals, and statistically relate these measures to genomic, environmental, epidemiological, and clinical outcome data. Two subgroups of neuroimaging and statistical genetics experts are developing techniques for large-scale data analysis, including diffusion tensor imaging and connectomics. “It’s an alliance to make it easier for others to do science”, says Thompson of his group. An example of collaboration facilitated by their work is the coming together of researchers studying connectome mapping and those interested in bipolar disorder and schizophrenia. “These are very different groups of people who have never worked together before”, he explains. “But they’ll use the ENIGMA protocol to map connections in all the scans they have on schizophrenia and bipolar [disorder] to ask whether the brain is wired differently if you have either of these diseases.” Difficulties, he says, lie in the fact that not all scans are the same. Many images are from standard 1·5 Tesla www.thelancet.com/neurology Vol 14 May 2015
scanners, while others are collected with advanced scanners that use magnetic fields as high as 4 Tesla: “the connectome group has been working for 6 years on harmonising this information across imaging centres. Its potential is very exciting.” Dan Stein, professor of psychiatry and mental health at the University of Cape Town, South Africa, coheads the obsessive compulsive disorder and HIV working groups in ENIGMA. His ENIGMA HIV group is investigating, among other questions, the relation between CD4 counts and brain structure in HIV. He sees the possibility of such global collaboration as a real strongpoint of ENIGMA. “The vast majority of neuropsychiatric research is conducted in high-income countries”, he says, “but the majority of people suffering from these conditions live elsewhere. ENIGMA has developed pipelines that allow researchers in less well-resourced centres to participate in its work. Participation in big science projects such as ENIGMA can be a real boon for researchers and patients in low and middle income countries.” About 10% of ENIGMA’s data come from such countries, including South Africa, Thailand, and Cambodia. Martin adds that: “It’s a remarkable example of the change in the zeitgeist of science. From all these big professors competing with each other, trying to do each other down, to taking the leap to realising that there’s actually a lot more to be gained by being cooperative.” Max Wiznitzer, professor of paediatric neurology at the Case Western Reserve University and the Rainbow Babies and Children’s Hospital, OH, USA, is not part of the ENIGMA network. “I find it to be an interesting exercise”, he says. “In neurology we’ve been doing a lot of gene-identification studies and trying to relate genetic findings to clinical phenotypes, and what ENIGMA provided is an important intermediary step between these two things. But it’s not going to answer all the questions.”
The questions he says any such macro-level studies can’t answer are those to do with problems associated with abnormalities at the synapse level or in morphology, such as dysplasia. “Not all disorders can be seen on MRI”, he says, “but they can definitely make progress in some disorders. The benefits obviously need to be balanced against use of limited resources and costs, and we need to ensure there is appropriate interpretation of data to make sure we’re not too enthusiastic and don’t jump to incorrect conclusions as we’ve seen before with other GWAS findings.” Russell Poldrack, a professor of psychology at Stanford University, CA, USA, also gives the project “a big thumbs up” with caveats. “I don’t know if we still have a good idea of, mechanistically, what it means for a gene or group of genes to be associated with a particular aspect of the structure of the brain”, he says, explaining that, in previous studies of brain structure, sometimes bigger is better and sometimes it is worse, and in a lot of cases more targeted, hypothesis-driven research is also needed. “Having said that, clearly they’re finding replicable associations and one would hope that that’s a start towards doing some real biology and finding out what it all actually means.”
For more on the Big Data to Knowledge initiative see http:// bd2k.nih.gov
Dara Mohammadi
Paul Thompson and Nick Martin
463
