The Simons Simplex Collection (SSC) is a core project and resource of the Simons Foundation Autism Research Initiative (SFARI). The SSC achieved its primary goal to establish a permanent repository of genetic samples from 2,600 simplex families, each of which has one child affected with an autism spectrum disorder, and unaffected parents and siblings.

Each genetic sample has an associated collection of data that provides a precise characterization, or phenotype, of the individual. Rigorous phenotyping maximizes the value of the resource for a wide variety of future research projects on the causes and mechanisms of autism.

The SSC was operated by SFARI in collaboration with 12 university-affiliated research clinics. The clinics identified and assessed potential SSC participants, with guidance from the University of Michigan Autism and Communication Disorders Center, to ensure uniformity across clinics. Active enrollment of participants ended in 2011.

Previous pioneering efforts to collect genetic samples focused on families that include multiple individuals with autism, most notably the Autism Genetic Resource Exchange (AGRE), an ongoing effort to identify these so-called ‘multiplex’ families. The SSC differs from those efforts in its focus on simplex families, and in its clinic-based assessment and diagnosis.

• The collaborating institutions and investigators are listed here: SSC sites and SSC investigators.
• A central database containing information from all study participants (with identifying information removed) is available to qualified researchers through SFARI Base.
• Blood samples were processed into cell lines and DNA was extracted at RUCDR Infinite Biologics (formerly Rutgers University Cell and DNA Repository). Stored samples are available to approved researchers on a modest fee-for-use basis, through SFARI Base.
• A subset of approximately 1,500 families who participated in the SSC are now enrolled in an online, contactable platform called the SSC registry. In 2015, SFARI recontacted all of these families to request updated medical and educational outcomes information on all family members. Data from participants who contributed to this follow-up project (440 families) are available to approved researchers via SFARI Base. Qualified researchers may also apply via SFARI Base for consideration to recruit this subset of families into new research studies. The Recruitment Process Document provides answers to many frequently asked questions. For more information, please contact [email protected].

All SSC data are available by request after logging into SFARI Base.

Some data are also available via NCBI’s Gene Expression Omnibus (GEO):

Array-based comparative genomic hybridization (CGH) data

1. Levy D. et al. Neuron 70, 886-897 (2011) PubMed, GEO data

Single nucleotide polymorphism (SNP) genotype data

1. Sanders S.J. et al. Neuron 70, 863-885 (2011) PubMed
2. Sanders S.J. et al. Neuron 87,1215-1233 (2015) PubMed

Molecular inversion probe (MIP) sequencing data

1. Stessman H.A. et al. Nat. Genet. 49, 515-526 (2017) PubMed

Whole-exome sequencing data

1. O’Roak B.J. et al. Nat. Genet. 43, 585-589 (2011) PubMed
2. Sanders S.J. et al. Nature 485, 237-241 (2012) PubMed
3. O’Roak B.J. et al. Nature 485, 246-250 (2012) PubMed
4. Iossifov I. et al. Neuron 74, 285-299 (2012) PubMed
5. Iossifov I. et al. Nature 515, 216-221 (2014) PubMed
6. Krumm N. et al. Nat. Genet. 47, 582-588 (2015) PubMed
7. Coe B.P. et al. Nat. Genet. 51, 106-116 (2019) PubMed

Whole-genome sequencing data

1. Turner T.N. et al. Am. J. Hum. Genet. 98, 58-74 (2016) PubMed, Data available through SFARI Base (please reference accessions SFARI_SSC_WGS_P [40 quad families] and SFARI_SSC_WGS_trioP [13 trio families]).
2. Collins R.L. et al. Genome Biol. 18, 36 (2017) PubMed
3. Turner T.N. et al. Cell 171, 710-722 (2017) PubMed
4. Munoz A. et al. bioRxiv (2017) Preprint
5. Brandler W.M. et al. Science 360, 327-331 (2018) PubMed
6. Werling D.M. et al. Nat. Genet. 50, 727-736 (2018) PubMed
7. An J.Y. et al. Science 362, eaat6576 (2018) PubMed
8. Zhou J. et al. Nat. Genet. 51, 973-980 (2019) PubMed

Mitochondrial DNA variation data

1. Wang Y. et al. PLoS Genet. 12, e1006391 (2016) PubMed

Gene-expression data (lymphoblastoid cell lines)

1. Luo R. et al. Am. J. Hum. Genet. 91, 38-55 (2012) PubMed, GEO data

Gene-expression data (blood)

1. Kong S.W. et al. Neurogenetics 14, 143-152 (2013) PubMed

DNA methylation profiling array-based data

1. Alisch R.S. et al. Genome Res. 22, 623-632 (2012) PubMed, Data only available through GEO