Center for Psychiatric Genomics

Psychiatric Genomics: Current Status, Future Strategies

Sue Millager — Wed, 11 Dec 2013 20:08:44 +0000

Dr. Patrick Sullivan presented findings from the Psychiatric Genomics Consortium Schizophrenia Working Group at an invited meeting, “Psychiatric Genomics: Current Status, Future Strategies” at the Banbury Center at Cold Spring Harbor Laboratory.

Banbury Conference Center

View presentation slides

Genome Studies Open Window on Schizophrenia Etiology

Sue Millager — Wed, 27 Nov 2013 10:00:00 +0000

Psychiatry Online reports “Scientists are steadily building a knowledge base to explain the relationship between the genetics of schizophrenia and the symptoms that characterize the disorder.”

Psychiatric News reported on advances in genome research of mental illness in a two-part series.

Open Postdoctoral Position

Sue Millager — Mon, 25 Nov 2013 22:38:17 +0000

Sullivan Lab, Department of Genetics, University of North Carolina at Chapel Hill seeking post doc to work on genomics of schizophrenia. PhD in genetics required.

CLICK HERE to view posting information. To apply, send current CV, cover letter, and three professional references to sullivanunc@gmail.com.

Quantitative Methods for Evaluating Association between Rare Genetic Variants and Complex Human Traits

Sue Millager — Wed, 13 Nov 2013 10:00:00 +0000

Congratulations to Andrea Byrnes. She successfully defended her dissertation!

Title: Quantitative Methods for Evaluating Association between Rare Genetic Variants and Complex Human Traits.

Rare variants pose a problem for conventional methods of association analysis because of dismally low power. In response, this dissertation tests new quantitative methods for the aggregation of information contained in rare variants that will allow the study of biological effects despite their rarity. Topics include rare variant aggregation for GWAS data (PMID: 21055717), use of annotation and variable selection (PMID: 23836599), and rare variant association for admixed data.

Read full dissertation.

Global Genome Initiative Finding Roots of Mental Illness

Sue Millager — Fri, 08 Nov 2013 18:40:00 +0000

Psychiatric News reports on progress made by the Psychiatric Genomics Consortium

By sharing data, technology, expertise, and new discoveries, researchers are quietly but rapidly pushing forward to reveal the genetic and biochemical causes of psychiatric disorders. Psychiatric News, November 8, 2013

Detecting Large Copy Number Variants Using Exome Genotyping Arrays in a Large Swedish Schizophrenia Sample

Sue Millager — Wed, 06 Nov 2013 23:57:01 +0000

PGC contributing authors, Patrick Sullivan and Jin Szatkiewicz, Copy Number Variants (CNV) Exome Genotyping in Schizophrenia article published in Molecular Psychiatry, 2013 November.

CNVs of known importance in schizophrenia

Although copy number variants (CNVs) are important in genomic medicine, CNVs have not been systematically assessed for many complex traits. Several large rare CNVs increase risk for schizophrenia (SCZ) and autism and often demonstrate pleiotropic effects; however, their frequencies in the general population and other complex traits are unknown. , 2013 Nov; 18(11):1178-84

Genomics of Schizophrenia: Update and Implications

Sue Millager — Tue, 05 Nov 2013 23:53:00 +0000

Paola Giusti-Rodriguez and Patrick F. Sullivan article review in Journal of Clinical Investigation, Volume 123, Issue 11, November 2013. Genomics of Schizophrenia: Update and Implications

“Assessment of the genome is increasingly complete, tractable and cost effective. It is now routine to screen the whole genome for many types of genetic changes in large samples.”

Progress in Schizophrenia Genomics

Sue Millager — Fri, 01 Nov 2013 03:15:00 +0000

Dr Patrick Sullivan gave a lecture at the National Human Genome Research Institute on “Progress in Schizophrenia Genomics” on October 31, 2013.

Genome Seminar Series Poster

Dr. Patrick Sullivan, distinguished professor and director for the Center for Psychiatric Genomics, was invited to be a guest speaker at the National Human Genome Research Institute Genome Seminar Series on October 31 in Bethesda, Maryland. The topic of his talk was “the uses of 70+ genome-wide significant common variants for Schizophrenia.

Autism article rebuttal: the perils of genetic risk prediction in autism

Betsy Clarke — Mon, 28 Oct 2013 18:30:00 +0000

Dr. Sullivan and colleagues comment on findings published in Molecular Psychiatry

Dr. Patrick Sullivan

“Last year, in , Stan Skafidas and colleagues made a remarkable claim: a simple genetic test could be used to predict autism risk from birth. The degree of genetic predictive power suggested by the paper was unprecedented for a common disease, let alone for a disease . However, instead of representing a revolution in autism research, many scientists felt that the paper illustrated the pitfalls of pursuing genetic risk prediction. After nearly a year of study, two papers have shown how the Skafidas et al. study demonstrates the dangers of poor experimental design and biases due to important confounders.” (from the article in : The perils of genetic risk prediction in autism, October 28, 2013)

Psychiatric Genomics Consortium: Marked Progress via Collaboration

Sue Millager — Tue, 22 Oct 2013 04:30:00 +0000

Psychiatric Genomics Consortium symposium at World Congress for Psychiatric Genetics: Marked Progress via Collaboration chaired by Dr. Patrick Sullivan, Director of the Center for Psychiatric Genomics.

Disorder Case Samples

Dr. Patrick Sullivan chaired a symposium on October 21 at the World Congress for Psychiatric Genetics in Boston, Massachusetts, “The Psychiatric Genomics Consortium: Marked Progress via Collaboration.” Dr. Sullivan is the lead Principle Investigator of the Psychiatric Genomics Consortium (PGC). Professor Mick O’Donovan (United Kingdom) described findings for common variation, Dr. Shaun Purcell (Harvard) rare variation, Dr. Ben Neale (Broad Institute) autism, Professor Naomi Wray (Queensland Brain Institute) genetic architectures, and Dr. Mark Daly (Harvard) was discussant. The PGC now has full GWAS data on 172,000 individuals in analysis, and the “psych chip” experiment will add at least 80,000 more.