Molecular PsychiatryNeurosciencePeer-reviewed journal article
Induction of Dopaminergic Neurons for Neuronal Subtype-Specific Modeling of Psychiatric Disease Risk
Samuel K. PowelliD, Callan P. O’SheaiD, Kayla G. TownsleyiD, Iya PrytkovaiD, Kristina DobrindtiD, Rahat Elahi, Marina IskhakovaiD, Tova Y. LambertiD, Aditi ValadaiD, Will LiaoiD, Seok‐Man HoiD, Paul A. SlesingeriD, Laura M. HuckinsiD, Schahram AkbarianiD, Kristen BrennandiD
Abstract
Dopaminergic neurons are critical to movement, mood, addiction, and stress. Current techniques for generating dopaminergic neurons from human induced pluripotent stem cells (hiPSCs) yield heterogenous cell populations with variable purity and inconsistent reproducibility between donors, hiPSC clones, and experiments. Here, we report the rapid (5 weeks) and efficient (~90%) induction of induced dopaminergic neurons (iDANs) through transient overexpression of lineage-promoting transcription factors combined with stringent selection across five donors. We observe maturation-dependent increase in dopamine synthesis, together with electrophysiological properties consistent with midbrain dopaminergic neuron identity, such as slow-rising after hyperpolarization potentials, an action potential duration of ~3ms, tonic sub-threshold oscillatory activity, and spontaneous burst firing at frequency of ~1.0-1.75 Hz. Transcriptome analysis reveals robust expression of genes involved in fetal midbrain dopaminergic neuron identity. Specifically expressed genes in iDANs, relative to their isogenic glutamatergic and GABAergic counterparts, were linked to the genetic risk architecture of a broad range of psychiatric traits, with iDANs showing particularly strong enrichment in loci conferring heritability for cannabis use disorder, schizophrenia, and bipolar disorder. Therefore, iDANs provide a critical tool for modeling midbrain dopaminergic neuron development and dysfunction in psychiatric disease.
- organism: human
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: statistical model
- Citations
- 31
- FWCI
- 1.41
- Field percentile
- top 18%
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