OMB No. 0925-0001/0002 (Rev. 08/12 Approved Through 8/31/2015)
BIOGRAPHICAL SKETCH
Provide the following information for the Senior/key personnel and other significant contributors.
Follow this format for each person. DO NOT EXCEED FIVE PAGES.
NAME: Stephan Ripke
eRA COMMONS USER NAME (credential, e.g., agency login): SRIPKE
POSITION TITLE: Research Scientist, Broad Institute, Boston, MA, USA; Postdoc, Charite, Berlin, Germany.
EDUCATION/TRAINING (Begin with baccalaureate or other initial professional education, such as nursing,
include postdoctoral training and residency training if applicable. Add/delete rows as necessary.)
DEGREE
(if
applicable)
Completion
Date
MM/YYYY
University of Hamburg, Germany
M.D.
2002
Medicine
University of Utrecht, Netherlands
Ph.D.
2014
Human Genetics
INSTITUTION AND LOCATION
FIELD OF STUDY
A. Personal Statement
Since the early days of my medical training I have an interest and pursue computational methods in genetic
research. The rare combination of strong computational and statistical background with medical / clinical
training allows me to execute all necessary steps from receiving raw genotypic data, via all necessary
computational steps (QC, imputation, meta-analysis, PCA, etc) up to drawing medical/clinical conclusions from
the results. Moreover during the recent years, leading most statistical analyses of the Psychiatric Genomics
Consortium – the biggest collaborative experiment in psychiatric genetics - I developed a strong sense for the
requirements of the near future to continue our overwhelming success. It is my conviction that collecting new
psychiatric individuals and healthy, matched controls with the possibility to recontact is one of the most
valuable contributions to further progress in psychiatric research.
While keeping my central position at the Psychiatric Genomics Consortium I recently moved to Berlin, a major
capital of the world without a sizable psychiatric dataset collection.
B. Positions and Honors.
Positions and Employment
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

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Krankenhaus KEH, Berlin, Germany: Residency, Internal Medicine
Max-Planck-Institute, Munich, Germany: Postdoctoral Fellow Statistical Genetics,
Max-Planck-Institute, Munich, Germany: Residency, Neurology
Stanley Center, Broad Institute and ATGU, MGH, Boston, USA: Research Scientist
Department of Psychiatry, Charite, Berlin, Germany: Postdoc
Other Experience and Professional Memberships
2002-2005
2005-2007
2007-2008
since 2008
since 2014
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Core member of the Psychiatric Genomics Consortium
Member of the American Society of Human Genetics
Peer reviewer for: Nature, Nature Genetics, Nature Neuroscience, American Journal of Human Genetics,
European Journal of Human Genetics, Human Heredity, Translational Psychiatry
Honors

Dr. med. / M.D., Magna Cum Laude, University of Hamburg, Germany
2001

Travel Award, ASHG, Montreal
2011

Travel Award, WCPG, Hamburg
2012

Oral Presentation Award, WCPG, Hamburg
2012

Theodor Reich Young Invistigator Award of the International Society of Psychiatric Genetics. 2013
o http://2013.ispg.net/wp-content/uploads/2013/09/WCPGProgramBook2013.pdf (page 15)

The Sidney R. Baer, Jr., Prize of the Brain & Behavior Research Foundation
2014
o https://bbrfoundation.org/2014-outstanding-achievement-prizewinner

Ph. D., Cum Laude, Utrecht University, Netherlands
2014
C. Contribution to Science
(* indicates joint first authors)
1. Early GWAS in psychiatric and non-pyschiatric genetics. In my early publications I contributed to genome
wide association analyses from single research centers. While some (e.g. for Restless Legs Syndrome) could
successfully identify and replicate genetic variants associated with disease, for most studies it became
apparent that the sample size was not sufficient for successful GWAS. As a collaborator and co-author for
these studies I learned the common pitfalls and importance of quality controls in these early days of GWAS.
a. Winkelmann J, Schormair B, Lichtner P, Ripke S, et al. "Genome-wide association study of restless
legs syndrome identifies common variants in three genomic regions." (2007). Nat Genet 39(8):1000-6,
PMID: 17637780.
b. Ising M, Lucae S, Binder EB, Bettecken T, Uhr M, Ripke S, et al. "A genomewide association study
points to multiple loci that predict antidepressant drug treatment outcome in depression." (2009). Arch
Gen Psychiatry 66(9):966-75, PMID: 19736353.
c. Weber F, Fontaine B, Cournu-Rebeix I, Kroner A, Knop M, Lutz S, Muller-Sarnowski F, Uhr M,
Bettecken T, Kohli M, Ripke S, et al."IL2RA and IL7RA genes confer susceptibility for multiple sclerosis
in two independent European populations." (2008). Genes Immun 9(3):259-63, PMID: 18354419.
2. Developing algorithms and software for statistical genetics. Since the early days of my scientific career I was
directly involved in method development for computational methods in human genetics. Many of these still
serve as “golden standards” for genetic analyses. Most of my contributions were on the co-authorship level
with providing data and interpretation of results.
a. Aulchenko YS, Ripke S, et al. "GenABEL: an R library for genome-wide association analysis." (2007).
Bioinformatics
b. Bulik-Sullivan BK, Loh PR, Finucane HK, Ripke S, et al. "LD Score regression distinguishes
confounding from polygenicity in genome-wide association studies." (2015). Nat Genet
c. Gusev A, Lee SH, Trynka G, Finucane H, Vilhjalmsson BJ, Xu H, Zang C, Ripke S, et al. "Partitioning
heritability of regulatory and cell-type-specific variants across 11 common diseases." (2014). Am J
Hum Genet 95(5):535-52
d. Lee SH, DeCandia TR, Ripke S, et al. "Estimating the proportion of variation in susceptibility to
schizophrenia captured by common SNPs." (2012). Nat Genet 44(3):247-50
3. Disease specific GWAS of schizophrenia and other psychistric diseases. My main field of research was the
accumulation and joint analysis of hundreds of psychiatric GWAS datasets from all over the world of
psychiatric genetics. Due to extensive collaboration with enormous increase of samplesize we could identify
valid, replicating genetic variations associated to psychiatric disease. I organized phone conferences,
performed QC, imputation, meta-analysis, prepared manuscripts and presented the results at numerous
scientific meetings. For all listed publications I served as a first author or co-first author.
a. Ripke S*, Wray NR*, Major Depressive Disorder Working Group of the Psychiatric GWAS Consortium*,
et al. "A mega-analysis of genome-wide association studies for major depressive disorder." (2013). Mol
Psychiatry 18(4):497-511, PMID: 22472876.
b. Ripke S*, Schizophrenia Psychiatric Genome-Wide Association Study (GWAS) Consortium*, et al.,
"Genome-wide association study identifies five new schizophrenia loci." (2011). Nat Genet 43(10):96976, PMID: 21926974.
c. Ripke S*, O Dushlaine C*, et al. "Genome-wide association analysis identifies 13 new risk loci for
schizophrenia." (2013). Nat Genet 45(10):1150-9, PMID: 23974872.
d. Ripke S*, Schizophrenia Working Group of the Psychiatric Genomics Consortium*, et al. "Biological
insights from 108 schizophrenia-associated genetic loci." (2014). Nature 511(7510):421-7, PMID:
25056061.
4. Psychiatric GWAS across diagnostic boundaries. With direct access to raw genotype information we could
also examine the genetic correlation across distinct psychiatric diseases. This lead to a deeper understanding
of the genetic commonalities and differences between distinct diseases on the level of single variants but most
importantly on the genomewide level integrating the entirety of genetic information at once. Also we could
successfully apply these methods to so called endophenotypes of psychiatric illness. In most of these projects
I was directly involved with primary analyses and served as a co-author or co-first author.
a. Ruderfer DM*, Fanous AH*, Ripke S*, et al. "Polygenic dissection of diagnosis and clinical dimensions
of bipolar disorder and schizophrenia." (2014). Mol Psychiatry 19(9):1017-24, PMID: 24280982.
b. Cross-Disorder Group of the Psychiatric Genomics Consortium, Lee SH, Ripke S, et al. "Genetic
relationship between five psychiatric disorders estimated from genome-wide SNPs." (2013). Nat Genet
45(9):984-94, PMID: 23933821.
c. Smoller JW*, Ripke S*, Cross-Disorder Group of the Psychiatric Genomics Consortium*, et al.
"Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide
analysis." (2013). Lancet 381(9875):1371-9, PMID: 23453885.
5. GWAS of non-psychitric disease. In the non-psychiatric field I was leading a big meta-analytic GWAS project
for inflammatory bowel disease (IBD). For this “gold standard disease” in GWAS we show the enormous
information gain with customized and affordable genotyping platforms (here “Immunochip”), here published as
co-first author. In addition I was involved on a first and co-authorship level in numerous other projects for
complex traits, such as HIV-controllers, age related macular degeneration, alopecia areata, adult height, body
mass index.
a. Jostins L*, Ripke S*, et al. "Host-microbe interactions have shaped the genetic architecture of
inflammatory bowel disease." (2012). Nature 491(7422):119-24, PMID: 23128233.
b. McLaren PJ, Coulonges C, Ripke S, et al. "Association study of common genetic variants and HIV-1
acquisition in 6,300 infected cases and 7,200 controls." (2013). PLoS Pathog 9(7):e1003515, PMID:
23935489.
c. Betz RC*, Petukhova L*, Ripke S*, "Genome-wide meta-analysis in alopecia areata resolves HLA
associations and reveals two new susceptibility loci." (2015). Nat Commun, PMID: 25608926.
d. Locke AE, Kahali B, Berndt SI, [...], Ripke S, et al "Genetic studies of body mass index yield new
insights for obesity biology." (2015). Nature 518(7538):197-206, PMID: 25673413.
Full list of published work on pubmed:
http://www.ncbi.nlm.nih.gov/sites/myncbi/1VQTc6r4jpmAw/bibliography/43370366/public/?sort=date&direction
=ascending
D. Research Support
5U01MH094432-02 (Daly, PI)
05/10/12 -03/31/16
NIH/ NIHM
2/3 Psychiatric GWAS Consortium: Genomic Followup Next Gen Sequencing and Genotyping
The aims of this proposal are to build on the already successful Psychiatric GWAS consortium's efforts
aggregating genetic data for psychiatric illness. As additional work in the community is being conducted that
expands the GWAS data and is beginning to generate sequencing data, further work is necessary to ensure
that maximal value is extracted from these combined efforts.