Advancing the understanding of autism disease mechanisms through genetics

Once the genes implicated in a disorder are identified, understanding the mechanism(s) by which they lead to disease is approachable. We use genetic engineering in model systems such as rodents (in vivo), and human neural stem cells (in vitro) to understand the biological impact of risk variants (schematic shown below).

However, since genes do not act in isolation and many complex human disorders involve the interaction of many genes, we also rely on systems biology methods to understand the biological pathways that may be impacted by disease associated variation. We employ multi-dimensional approaches to link genotype to phenotype by profiling genome-wide measures such as whole genome sequencing, transcriptomics, and epigenetics. This has necessitated the development and application of gene network methods, which form the backbone of our systems biology framework.

To move from gene networks to understanding disease mechanism(s) we need to be able to connect multiple levels of analysis, traversing the distance from gene to protein, to cell to circuit to behavior and cognition. Connecting these different levels necessitates multidisciplinary collaborations, ranging from those that study the effects of risk variants in humans, to studies that try to bridge the gap from DNA variant to cellular function and physiology using human neural stem cells (Pa?ca et al. 2015) and animal models (de la Torre-Ubieta et al. 2016, Peñagarikano et al. 2011 (watch the video abstract here), Peñagarikano et al. 2015, Chandran et al. 2017).

See also:

Gandal et al. 2016, The road to precision psychiatry: translating genetics into disease mechanisms, Nat Neurosci.
Geschwind and Konopka 2009, Neuroscience in the era of functional genomics and systems biology, Nature.
Parikshak et al. 2015, Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders, Nat Rev Genet.
de la Torre-Ubieta et al. 2016, Advancing the understanding of autism disease mechanisms through genetics., Nat Med.
Pa?ca et al. 2015, Functional cortical neurons and astrocytes from human pluripotent stem cells in 3D culture, Nat Methods.
Peñagarikano et al. 2011, Absence of CNTNAP2 leads to epilepsy, neuronal migration abnormalities, and core autism-related deficits, Cell. (watch the video abstract here)
Peñagarikano et al. 2015, Exogenous and evoked oxytocin restores social behavior in the Cntnap2 mouse model of autism, Sci Transl Med.
Chandran et al. 2017, Inducible and reversible phenotypes in a novel mouse model of Friedreich's Ataxia, eLife.
 

Most recent relevant publications listed below. Our work appears in these journals. To see a full list, click here:

The Dynamic Landscape of Open Chromatin during Human Cortical Neurogenesis.

de la Torre-Ubieta L, Stein JL, Won H, Opland CK, Liang D, Lu D, Geschwind DH.

Cell. 2018; 172(1-2):289-304.e18.

PMID: 29307494

Preview in Cell:  Weaving New Insights for the Genetic Regulation of Human Cognitive Phenotypes 

Research Highlight in Nature Reviews Neuroscience: Neural development: 'Enhancing' human cognition

Self-Organized Cerebral Organoids with Human-Specific Features Predict Effective Drugs to Combat Zika Virus Infection.

Watanabe M, Buth JE, Vishlaghi N, de la Torre-Ubieta L, Taxidis J, Khakh BS, Coppola G, Pearson CA, Yamauchi K, Gong D, Dai X, Damoiseaux R, Aliyari R, Liebscher S, Schenke-Layland K, Caneda C, Huang EJ, Zhang Y, Cheng G, Geschwind DH, Golshani P, Sun R, Novitch BG.

Cell reports. 2017; 21(2):517-532. NIHMSID: NIHMS907491

PMID: 29020636 PMCID: PMC5637483

Chromosome conformation elucidates regulatory relationships in developing human brain.

Won H, de la Torre-Ubieta L, Stein JL, Parikshak NN, Huang J, Opland CK, Gandal MJ, Sutton GJ, Hormozdiari F, Lu D, Lee C, Eskin E, Voineagu I, Ernst J, Geschwind DH.

Nature. 2016; 538(7626):523-527. NIHMSID: NIHMS833424

PMID: 27760116 PMCID: PMC5358922

Advancing the understanding of autism disease mechanisms through genetics.

de la Torre-Ubieta L, Won H, Stein JL, Geschwind DH.

Nature medicine. 2016; 22(4):345-61. NIHMSID: NIHMS821081

PMID: 27050589 PMCID: PMC5072455

A quantitative framework to evaluate modeling of cortical development by neural stem cells.

Stein JL, de la Torre-Ubieta L*, Tian Y, Parikshak NN, Hernández IA, Marchetto MC, Baker DK, Lu D, Hinman CR, Lowe JK, Wexler EM, Muotri AR, Gage FH, Kosik KS, Geschwind DH.

Neuron. 2014; 83(1):69-86. NIHMSID: NIHMS601533

PMID: 24991955 PMCID: PMC4277209

*Co-first.

Neuron Cover Article. 

FoxO6 regulates memory consolidation and synaptic function.

Salih DA, Rashid AJ, Colas D, de la Torre-Ubieta L, Zhu RP, Morgan AA, Santo EE, Ucar D, Devarajan K, Cole CJ, Madison DV, Shamloo M, Butte AJ, Bonni A, Josselyn SA, Brunet A.

Genes & development. 2012; 26(24):2780-801.

PMID: 23222102 PMCID: PMC3533081

Transcriptional regulation of neuronal polarity and morphogenesis in the mammalian brain.

de la Torre-Ubieta L, Bonni A.

Neuron. 2011; 72(1):22-40. NIHMSID: NIHMS328099

PMID: 21982366 PMCID: PMC3391704

A FOXO-Pak1 transcriptional pathway controls neuronal polarity.

de la Torre-Ubieta L, Gaudillière B, Yang Y, Ikeuchi Y, Yamada T, DiBacco S, Stegmüller J, Schüller U, Salih DA, Rowitch D, Brunet A, Bonni A.

Genes & development. 2010; 24(8):799-813.

PMID: 20395366 PMCID: PMC2854394

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