@pgc_fg

Functional Genomics working group of the Psychiatric Genetics Consortium.

pgc.unc.edu/for-researchers/working-groups/functional-genomics-working-group/
Joined February 2024
  • Tweets80
  • Following78
  • Followers143
8Media
The PGC Functional Genomics workgroup serves as a dynamic hub for collaborative, open discovery science and scalable method development. We aim to understand how genes, cells and molecules impact the symptoms and course of psychiatric disorders in populations globally.
1
2
6
884
🚨Our SECOND new paper alert for today 🚨 ✨Check out the new large OCD-case control EWAS published by Höffler & colleagues ✨ 🔗bit.ly/4x9c5qx 1/5 🧵

Methylome-Wide Association Study of Obsessive-Compulsive Disorder

Obsessive-compulsive disorder (OCD) is a debilitating psychiatric condition influenced by both genetic and environmental risk factors. Epigenetic modifications, such as DNA methylation, may offer...

biologicalpsychiatryjournal.com
1
42
more replies
🔑Key findings (3/3): ✨Differences in estimated cell composition and the identification of immune-related genes ✨suggests a potential role for immune system processes in OCD. 4/5 🧵
1
5
Well done to the team🎉, and remember to find the full paper at 🔗bit.ly/4x9c5qx 5/5 🧵

Methylome-Wide Association Study of Obsessive-Compulsive Disorder

Obsessive-compulsive disorder (OCD) is a debilitating psychiatric condition influenced by both genetic and environmental risk factors. Epigenetic modifications, such as DNA methylation, may offer...

biologicalpsychiatryjournal.com
5
🚨New paper alert!🚨 The bipolar disorder (BD) meta epigenome-wide association study (EWAS) by Tesfaye & colleagues is Out now in eBioMedicine 🔗bit.ly/4sGX9O6 🧵1/5
1
30
more replies
🔑Key findings (2/2): 🔷Importantly, polymethylation scores (PMS) improved prediction beyond polygenic scores (PGS), 🔷especially for bipolar I disorder: combined PMS + PGS models explained 18.5% of variance. 🧵4/5
1
8
A big congrats to the team🥳, and don't forget to check out the full paper here 🔗bit.ly/4sGX9O6 🧵4/5
7
So, who are the the Functional Genomics Working Group? 🎯Our goal is to understand how genes🧬, cells🦠and molecules💠contribute to psychiatric disorders🧠 We work with other PGC groups and different 'omics data (methylation, cytometry, single cell etc.) to do this🧪 🧵1/3
1
2
2
128
We have two awesome chairs ✨@HjerlingLeffler and @MLynall✨, who started the group in Fenruary 2024! We also have 5 project groups, 🔬exploring different ways of understanding #FunctionalGenomics in psychiatric disorders🧠 🧵2/3
1
2
36
Ultimately, we: 🌟drive inclusive and diverse 'omics' mental health research, 🌟and foster a collective effort that transcends individual capabilities for global science🌎! 🧵3/3
1
32
Before we get started, let’s introduce our two Social Media Reps - @BertholdNatasha and @Eva_C_Schulte! We're here for the #functionalgenomics🧬, and #Science #Communication📡is a🔑key part! 💫Check out their profiles💫
3
4
414
✨Welcome to the Functional Genomics Takeover of the PGC main account!✨ For the next 2 weeks @BertholdNatasha and @Eva_C_Schulte will be taking you through the achievements and highlights of year 2 in the @pgc_fg.
1
1
247
Key Takeaways🔑: ✨EpiAnceR+ improves ancestry adjustment when genotyping data aren’t available ✨and is compatible with all major Illumina methylation arrays 🧵5/6
1
112
Such a huge congratulations to the team🥳 Remember, you can find the full article here 🔗bit.ly/49syndi #epigenetics #DNAmethylation 🧵6/6
9
✨Hello folks!✨ We're back in your feed with an amazing paper spotlight by Kira Höffler & colleagues📰🔦 "Optimizing genetic ancestry adjustment in DNA methylation studies: a comparative analysis of approaches" 🔗bit.ly/49syndi Read our overview below! 🧵1/6
1
13
more replies
Results📊: ✨EpiAnceR+ improved on existing methods✨ Its ancestry PCs: 1⃣clustered repeated samples more tightly, 2⃣correlated more strongly with true genetic ancestry, 3⃣and outperformed methylation-based PCs and surrogate variables for ancestry correction 🧵4/6
1
9
Methods🗒️: To address this, the team developed EpiAnceR+🧑🏾‍💻, an R-based tool for ancestry adjustment in DNA methylation studies🧬 Function: 1⃣removes technical and biological noise, integrates SNP-related data 2⃣and generates ancestry PCs for downstream analysis 🧵3/6
1
15
Background❓: 🧬Genetic ancestry can confound DNA methylation results 🧬When genotyping data aren’t available, existing ancestry-adjustment methods often: 1⃣perform suboptimally, 2⃣or aren’t compatible with newer methylation arrays 🧵2/6
1
92
Load more