Can microattribution be applied to epilepsy genetics?

Genetic studies in seizure disorders require at least two components, (a) recruitment/phenotyping and (b) genotyping.  While genotyping technologies slowly turn into standardized industry-like analysis pipelines that allow for fast processing of large sample volumes, recruitment and phenotyping still requires significant human input and is unlikely to become more efficient in the future.  Bluntly said, it is difficult to imaging that any form of high-throughput recruitment or phenotyping can ever be realized.  On the contrary, the effort and time required for recruiting and sufficiently characterizing patients for epilepsy genetics studies is probably likely to increase, given the complexity of consenting patients for whole exome or whole genome sequencing projects [1].

In summary, large cohorts or patients consented for high-throughput sequencing technologies require an asymmetrically large time investment through referring clinicians.  These investments might already be insufficiently represented in publications, authorships and referenceable attributions of the scientific work.  Needless to say that much of the work required for recruitment and phenotyping is insufficiently covered by research funding and is often unpaid.

Nevertheless, motivated patient recruitment, thorough annotation, clinical data collection and database entry is likely to become a key issue in correlation genotypic and phenotypic data.  How this time-consuming work can be reflection in attribution is yet unsolved.

A recent string of papers in Nature Genetics has highlighted a novel avenue for crediting collaborating researcher for small contributions to a larger scientific project [2-5].  These microattributions consist of crediting authors for database entries by publicly displaying the contributor (e.g. entry created by W.G. Lennox) and agreeing to publishing the work jointly at defined stages of the research.  Applying this microattribution strategy to hemoglobinopathies has resulted in a sharp increase in reported variants [4].

Similar strategies for documenting phenotypic data could be used for collecting phenotypic data for epilepsy databases in large collaborative projects such as EuroEPINOMICS.  This strategy might enable individual researchers to reference their contribution to large collaborative projects, which usually require years until joint papers are written, submitted, reviewed and published.


1. Kaye, J., et al., Ethical implications of the use of whole genome methods in medical research. Eur J Hum Genet, 2010. 18(4): p. 398-403.

2. What is the human variome project? Nat Genet, 2007. 39(4): p. 423.

3. Crowdsourcing human mutations. Nat Genet, 2011. 43(4): p. 279.

4. Giardine, B., et al., Systematic documentation and analysis of human genetic variation in hemoglobinopathies using the microattribution approach. Nat Genet, 2011. 43(4): p. 295-301.

5. Mons, B., et al., The value of data. Nat Genet, 2011. 43(4): p. 281-3.

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Helbig, I. Can microattribution be applied to epilepsy genetics?. Retrieved [enter date], from

Ingo Helbig

Child Neurology Fellow and epilepsy genetics researcher at the Children’s Hospital of Philadelphia (CHOP), USA and Department of Neuropediatrics, Kiel, Germany

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