Hyejung Won

Thanks Leo! It was lovely to meet you again!

Thanks so much Keri for inviting me ❤️ It was a great pleasure to visit Lieber and meet so many amazing scientists!

Phenomenal talk from @hyejungwon.bsky.social who is visiting us @lieberinstitute.bsky.social for the day. Groundbreaking work w/ important implications and roadmap for using rapidly emerging information on psychiatric genetics to prioritize variants and understand their impact on 🧠 function

Our "Atlas of Variant Effects 2030 Roadmap" is live: zenodo.org/records/1542...

1/n

How does APOE change your risk of developing Alzheimer's disease? At least partially by changing the function of immune cells in your brain 🧠🧬

New paper out in @natcomms.nature.com today: www.nature.com/articles/s41...

@ukdri.ac.uk @kingsioppn.bsky.social @imperialbrains.bsky.social

Huge congrats Debby! This was a lovely story when you presented at GRC ❤️

Huge congrats Alexi and Sarah 🎉

Silencing of transgenes during iPSC differentiation is a frequent problem. 🧬🫢

Check out the piggyBac system below, which has resisted silencing in many protocols across many labs. 💪

Excited that our lab could contribute to this team effort led by @tuenaka.bsky.social & Marius Wernig!

Watch the video📽️attached to see what each of these awesome #FemsinSTEM are up to!

🧵3/3

Marija, I am so much happy for you! Huge congrats! 😍

Genome-wide association study of borderline personality disorder reveals genetic overlap with bipolar disorder, major depression and schizophrenia - Translational Psychiatry Translational Psychiatry - Genome-wide association study of borderline personality disorder reveals genetic overlap with bipolar disorder, major depression and schizophrenia

Hello, it is because borderline disorder GWAS is not well powered: i.e. it does not have any hits (dots) above the red line in figure 2: www.nature.com/articles/tp2.... This means that there are not robust and reliable genomic regions that we can chase after for functional analysis.

This is soooo cool Pedro! Huge congrats!

Massively parallel assessment of gene regulatory activity at human cortical structure associated variants Genetic association studies have identified hundreds of largely non-coding loci associated with inter-individual differences in the structure of the human cortex, though the specific genetic variants ...

Very good new preprint by @nanamatoba.bsky.social @hyejungwon.bsky.social @steinlab.bsky.social, using a Massively Parallel Reporter Assay to gain insight into regulatory elements associated with inter-individual differences in cortical structure (Wnt response sensitivity plays a prominent role)🧪🧠🧬

15/ Last but not least, I'd like to thank fabulous first authors, Sool Lee, Jessica McAfee, and Jiseok Lee; great collaborators, Pat Sullivan, Adriana Beltran, @markgerstein.bsky.social, Alan Boyle; and a fantastic editor, Scott Behie!

Thanks so much!

Yay thanks! You deserve a credit here 😆

14/ There’s much more in the full manuscript, including findings on Alu elements with gene regulatory activity and CRISPR validation. Check it out here for full access: authors.elsevier.com/a/1kU9ZL7PXq...

13/ Together, our findings suggest pleiotropy arises from the functional properties of target genes and proteins, including prolonged gene activity during neuronal differentiation and higher protein connectivity in PPI networks.

12/ PPI networks were a recurring theme: mDis3-bound transcription factors, mDis3 proteins, and even downstream effectors all showed higher connectivity in PPI networks. Connectivity in these networks seems critical to how pleiotropic variants exert their effects.

11/ We also investigated protein-protein interaction (PPI) networks. mDis3 proteins were significantly more interconnected than mDis1 proteins. This implies pleiotropic proteins may amplify their effects through network connectivity, rippling through molecular pathways.

10/ This suggests that mDis3 variants target genes with broader or longer activity across excitatory neuronal differentiation, potentially driving multiple downstream effects. These temporal differences may explain part of the functional diversity seen in pleiotropy.

9/ We next examined the functional properties of variants and their target genes. Both mDis1 and mDis3 variants were enriched in the excitatory neuronal lineage. In this lineage, mDis1 genes were often expressed in a single cell type, while mDis3 genes showed prolonged, multi-cell-type expression.

8/ Next, we wondered if mDis3 variants have more complex regulatory connectivity (e.g., linking to multiple genes). Again, no significant differences were found between mDis3 and mDis1 loci in the number of genes connected to emVars.

7/ First, we asked if mDis3 loci simply have more emVars than mDis1 loci. The number of emVars didn’t differ between mDis3 and mDis1 loci. So, the extent of pleiotropy wasn’t explained by the number of variants with regulatory activity.

6/ Why exclude 2-disorder variants? Many were linked to bipolar and schizophrenia, which have high genetic correlation (>0.7). This made it hard to determine if they were truly pleiotropic or just driven by shared biology between these two highly related disorders.

5/ MPRA narrowed ~17k variants to ~680 with validated regulatory activity, which we call expression-modulating variants (emVars). We categorized emVars into: (1) mDis3: linked to 3+ disorders. (2) mDis1: linked to 1 disorder. Variants linked to 2 disorders were excluded.

4/ One challenge: ~17k variants in cross-disorder loci showed nominal associations (p < 1e-5), making it hard to pinpoint key variants. To address this, we used MPRA (massively parallel reporter assay) to test the regulatory activity of thousands of variants simultaneously.

3/ In 2019, the PGC cross-disorder group conducted a meta-GWAS of 8 psychiatric disorders, identifying 136 “cross-disorder loci.” Among these, 109 loci were linked to 2+ disorders (pleiotropic loci). But how do pleiotropic loci differ from disorder-specific loci?

2/ Pleiotropy occurs when genetic variants affect multiple traits. It's common in psychiatry, where many disorders show significant genetic correlations.

Massively parallel reporter assay investigates shared genetic variants of eight psychiatric disorders High-throughput experimental validation of genetic variants linked to eight psychiatric disorders reveals the regulatory mechanisms underlying variants with pleiotropic and disorder-specific effects.

1/ I am beyond thrilled to share our new paper in @CellCellPress! We explored the regulatory principles underlying pleiotropy in psychiatric disorders.
www.cell.com/cell/abstrac...