Integration of Genomics and Transcriptomics in unselected Twins and in Major Depression

Our goals are to develop a comprehensive understanding of the genomics of transcription in a population based unselected sample and to discover DNA and RNA biomarkers for major depressive disorder (MDD). This work is essential to developing a more complete understanding of the biological basis of MDD, a common complex trait associated with considerable morbidity, mortality, and personal/societal cost. All biological samples have been collected from well-defined populations, and are now available.

First, we conduct a "genetical genomics" or eQTL study of ~800 MZ and ~800DZ twin pairs. Each subject has been assayed for genome-wide SNPs and CNVs and gene expression from peripheral blood sampled under standardized conditions. We determine the genetic architecture (genetic and non-genetic proportions of variance via twin analyses) for every transcript, and the genome-wide associations (i.e., SNP-transcript eQTL pairs). These analyses will be expanded to consider transcriptional modules. The key deliverable is a detailed catalogue of the general and specific architecture of transcription plus raw intensity files.

Second, we seek to discover DNA and RNA biomarkers relevant to MDD, capitalizing on the results of a large MDD study with repeated clinical and biological assessments; we have previously shown that PB is a reasonable proxy for CNS expression and employ an advanced modelling framework: (a) Using baseline data, we identify biomarkers for MDD by comparing ~1000 controls with ~1400 MDD cases via comparisons of SNP, CNV, expression transcripts, and transcriptional modules. (b) Using longitudinal data, we contrast gene expression signatures assessed at baseline and two years later in ~200 controls and ~500 MDD cases.

• Study Weblinks:
  • Netherlands Study of Depression and Anxiety (NESDA)
  • Netherland Twin Register
• Study Design:
  • Prospective Longitudinal Cohort
• Study Type:
  • Cohort
• dbGaP estimated ancestry using GRAF-pop
• Total number of consented subjects: 5339
• Subject Sample Telemetry Report (SSTR)

Netherlands Twin Registry (NTR). The NTR has collected longitudinal data on twins and their families via 8 surveys every 2-3 years, beginning in 1991 (~22,000 participants from ~5,000 families). Most twins were recruited as young adults through City Council registration, and additional twins via a variety of approaches. Longitudinal phenotyping includes assessment of DSM-IV MDD by CIDI, depressive symptoms (multiple instruments), anxiety, neuroticism, and other personality measures. Additionally, subjects are asked about major medical illnesses/health, medications, life events, and lifestyle, and a genetic factor score for MDD liability is available. There are banked RNA and DNA samples from ~1600 pairs, with an almost equal distribution of monozygotic and dizygotic twin pairs. Most of these individuals are controls but some meet case definitions.

Netherlands Study of Depression and Anxiety (NESDA). NESDA is an ongoing cohort study designed to investigate the long-term course and consequences of depressive and anxiety disorders. Participants were 18-65 years at baseline in 2004-2007 and were recruited from the community (19%), general practice (54%), and mental health settings (27%). At baseline, there were ~1000 individuals with current MDD and ~1100 with past but not current history of MDD. The baseline assessment included the CIDI, demography, and medical assessment. DSM-IV MDD diagnoses were established with the CIDI which has high inter-rater reliability, test-retest reliability, and validity for MDD. Of the baseline subjects, 87% participated in a two year follow-up. The CIDI was repeated to query MDD in the time since baseline (augmented by the use of a Life Chart Interview). These measures allow classification into distinct clinical trajectories over two years of follow-up: chronic or recurrent course with symptoms >1y (poor course) and remission within one year (good course, initial MDD episode lasts <1y with complete remission >1y). Of subjects with current MDD at baseline, a minority (44.9%) were taking antidepressants (usually SSRIs). Antidepressant use data are now being coded. Most NESDA subjects are cases but an independent, longitudinally-assessed sample of controls was also collected.

Harmonized Biological Sampling. Processing and storage protocols were harmonized between the NESDA and NTR studies. Blood sampling in NESDA took place between 0830-0930h and between 0700-1000h for NTR. All venous blood samples were taken after an overnight fast.

RNA Sampling. Within 20 minutes of sampling, heparinized blood was transferred into PAXgene tubes and stored at −20°C. DNA isolation. EDTA tubes were used. For NESDA, FlexiGene DNA AGF3000 kits were used on an AutoGenFlex 3000 workstation. For NTR, Puregene DNA isolation kits were used on frozen whole blood samples. DNA concentrations were determined using PicoGreen dsDNA kits. All procedures were performed via manufacturer's protocols.

Covariates. Available covariates include: sampling time/date; age at sampling; sex; complete blood count with differential; consumption/quantity of tobacco and alcohol near the time of sampling; detailed list of medications (including antidepressants); and detailed health status (chronic/recent acute medical illness, allergies, etc.).

Data upload: The GODOT project has typed DNA and RNA from peripheral blood for large samples from both the NESDA and NTR studies. The available data are Affy6 genotype assays, as well as Affymetrix U219 expression assays on the same set of individuals (except for minor lack of overlap due to quality control flagging). Additional subject information includes twin pedigree descriptions (for the NTR subjects), major depressive disorder phenotyping for the NESDA subjects, and a set of patient/covariates that may influence expression levels.

• Primary Phenotype: Depressive Disorder, Major

• BioProject
• PubMed
• BioSample
• MeSH
• PMC

• Principal Investigator
  • Patrick F. Sullivan, MD. University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
• Co-Investigators
  • Fred Wright, PhD. University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Wei Wang, PhD. University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Wei Sun, PhD. University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Fei Zou, Phd. University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Sandra Batista, PhD. University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Vered Madar, PhD. University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Kai Xia, PhD. University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Andrew Brooks, PhD. Rutgers The State University of New Jersey, New Brunswick, NJ, USA.
  • Jay Tischfield, PhD. Rutgers The State University of New Jersey, New Brunswick, NJ, USA.
  • Qi Wang, PhD. Rutgers The State University of New Jersey, New Brunswick, NJ, USA.
  • Ani Qu, PhD. Rutgers The State University of New Jersey, New Brunswick, NJ, USA.
  • Jaspreet Kochar, PhD. Rutgers The State University of New Jersey, New Brunswick, NJ, USA.
  • David D'Ambrosia, MD. Rutgers The State University of New Jersey, New Brunswick, NJ, USA.
  • Dr. Brenda Penninx. VU University, Amsterdam, The Netherlands.
  • Dr. Johannes Smit. VU University, Amsterdam, The Netherlands.
  • Dr. Rick Jansen. VU University, Amsterdam, The Netherlands.
  • Gerard van Grootheest. VU University, Amsterdam, The Netherlands.
  • Dr. Dorret Boomsma. VU University, Amsterdam, The Netherlands.
  • Dr. Eco deGeus. VU University, Amsterdam, The Netherlands.
  • Dr. Gonneke Willemsen. VU University, Amsterdam, The Netherlands.
  • Dr. Jouke-Jan Hottenga. VU University, Amsterdam, The Netherlands.
• Funding Source
  • 5-RC2-MH089951-01 (Patrick F. Sullivan, MD). National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA.