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Josh Weinstock

@joshweinstock.bsky.social
231 followers 309 following 27 posts

Assistant Professor in the Department of Human Genetics at Emory University. Statistical genetics and genomics + genetic epidemiology of somatic mosaicism. weinstocklab.org

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Josh Weinstock @joshweinstock.bsky.social · 26/08/2026
We haven't looked into those. How strong is the evidence that UV exposure causes mutations in blood?
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Josh Weinstock @joshweinstock.bsky.social · 25/08/2026
Thanks again to @prarthana-s-r.bsky.social for a herculean effort to bring this all together -- she rapidly gained comfort in genetics after joining my group in January. Please let us know if you have any feedback!
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Josh Weinstock @joshweinstock.bsky.social · 25/08/2026
Finally, we mapped the aging-related disease correlates of both observed passenger burden and its polygenic risk score, finding the two yield large differences in several phenotypes. IMO, CH epidemiology should often include a CH PRS as a covariate to mitigate certain forms of confounding.
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Josh Weinstock @joshweinstock.bsky.social · 25/08/2026
Through RVAS, we observed the convergence of some new hits on classic CH pathways (epigenetic regulation and splicing), suggesting that germline and somatic variation converge on shared pathways to govern clonal expansion in aging blood:
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Josh Weinstock @joshweinstock.bsky.social · 25/08/2026
IMO, passenger mutations are quite interesting as they are conceptually very simple, yet highly informative about clonal expansion. After GWAS in UKB and AofU, among our first questions was to what extent genetic architecture varies by sex and ancestry, finding evidence for heterogeneity in both.
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Josh Weinstock @joshweinstock.bsky.social · 25/08/2026
Excited to share our latest foray into studying the ways in which germline variation gives rise to somatic variation in aging blood: www.medrxiv.org/content/10.6... In work led by @prarthana-s-r.bsky.social , we map how common and rare germline variation links to (somatic) passenger mutations 🧬🧵👇
medrxiv.org
Multi-ancestry analysis of 791K whole genomes reveals the genetic, geographic, and phenotypic correlates of somatic passenger mutations in blood
Clonal hematopoiesis (CH), an aging-related expansion of hematopoietic stem cell (HSC) clones, is associated with hematologic malignancy, cardiovascular disease, and mortality. Most clonal expansions,...
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Josh Weinstock @joshweinstock.bsky.social · 05/06/2026
Thanks, this is on v2.
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Josh Weinstock @joshweinstock.bsky.social · 04/06/2026
Anyone have a good workflow for downloading GWAS summary statistics from All of Us? Totally in compliance with their policy, but the file is simply too large (1.7GB), and downloads time out. We split into several 10mb files, but that is painful to download.
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Josh Weinstock @joshweinstock.bsky.social · 13/03/2026
Here's our R package for interacting with WGS derived GWAS summary statistics with many rare variants (from e.g. UKB or AofUs). It uses duckdb underneath so it's fast. Includes some helpful tie ins to Open Targets / Encode Screen / Ensembl APIs for annotation. weinstocklab.github.io/gwasplot/ind...
weinstocklab.github.io
High Performance GWAS Plotting And Annotation
More about what it does (maybe more than one line). Continuation lines should be indented.
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Josh Weinstock @joshweinstock.bsky.social · 05/12/2025
STATGEN 2026 will be in Atlanta @emoryrollins.bsky.social - see more info here: statgen26.emory.edu
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Reposted by Josh Weinstock
Jeff Spence @jeffspence.github.io · 07/11/2025
How do GWAS and rare variant burden tests rank gene signals? In new work @nature.com with @hakha.bsky.social, @jkpritch.bsky.social, and our wonderful coauthors we find that the key factors are what we call Specificity, Length, and Luck! 🧬🧪🧵 www.nature.com/articles/s41...
nature.com
Specificity, length and luck drive gene rankings in association studies - Nature
Genetic association tests prioritize candidate genes based on different criteria.
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Josh Weinstock @joshweinstock.bsky.social · 14/10/2025
Shout to extraordinary collaborators and co-authors on this, Karen Conneely, Cameron Russell, Mitchell Machiela, Marios Arvanitis, Janghee Woo. For more info, I'm presenting this work on Thursday at #ASHG at 1:45pm, Room 210C
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Josh Weinstock @joshweinstock.bsky.social · 14/10/2025
To make results easier to parse, we also release a summary statistics "portal" to view our results, including lots of QC metrics: somatic.emory.edu We also release lots of code for this, which was all done on the DNA Nexus RAP in a cost effective way.
somatic.emory.edu
Explore clonal hematopoiesis associations with proteins and disease in UK Biobank.
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Josh Weinstock @joshweinstock.bsky.social · 14/10/2025
The IGH and IGL mutations in particular had really large effect sizes, so we then did a GWAS of a combined IGH + IGL phenotype, which resulted in a single hit: GRAMD1B. Remarkably, this is well characterized risk locus for CLL, suggesting that we are converging on CLL relevant biology.
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Josh Weinstock @joshweinstock.bsky.social · 14/10/2025
We then quantified the variance explained on a liability scale of CH to 30 common aging-related diseases. CH explains far more 'liability' scale variance for hematologic malignancies than other classes (as one would expect), though chronic kidney disease appears high here as well.
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Josh Weinstock @joshweinstock.bsky.social · 14/10/2025
New hits are generally indeed "weaker" than most classic CH drivers, suggesting that these are just underneath the "tip of the iceberg". We also replicate the telomere attrition mechanism reported here www.nature.com/articles/s41..., finding that the phenomenon is broader than previously observed
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Josh Weinstock @joshweinstock.bsky.social · 14/10/2025
The strongest hits are indeed strongly enriched for canonical CH genes, but we also find non-coding mutations at FGF1, UGT2B7, DGKB, the TERT promoter, chr17 centromere, and immunoglobulin loci:
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Josh Weinstock @joshweinstock.bsky.social · 14/10/2025
What happens if you search the genomes of ~490K adults for variants that associate with age at blood draw? We actually did this crazy idea, using the UKB WGS (from peripheral blood). Turns out this 'discovers' classic clonal hematopoiesis drivers and more 🧵👇 www.medrxiv.org/content/10.1... #ASHG
medrxiv.org
Genome-wide characterization of clonal hematopoiesis reveals extensive non-coding putative driver mutations
As humans age, we acquire somatic mutations in our blood, leading to clonal hematopoiesis (CH). Despite the prevalence of clonal hematopoiesis (CH) in aged individuals, recent searches for selective s...
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Reposted by Josh Weinstock
Ben Strober @bennystrobes.bsky.social · 07/10/2025
Exciting updates!! (1) I just opened my lab at Boston Children’s Hospital (Harvard-affiliated) (2) I’m hiring a postdoc focused on integrating GWAS and functional genomic data. Reach out if you’re interested or connect at ASHG next week! (3) Learn more at stroberlab.com
stroberlab.com
Strober Lab
The Strober lab is a computational group at Boston Children's Hospital (a Harvard Medical School affiliated hospital) focused on developing statistical and machine learning tools applied to human gene...
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Reposted by Josh Weinstock
Jesse Engreitz @jengreitz.bsky.social · 18/09/2025
Excited for a major milestone in our efforts to map enhancers and interpret variants in the human genome: The E2G Portal! e2g.stanford.edu This collates our predictions of enhancer-gene regulatory interactions across >1,600 cell types and tissues. Uses cases 👇 1/
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Reposted by Josh Weinstock
Sasha Gusev @sashagusevposts.bsky.social · 27/08/2025
I wrote about gene-gene interactions (epistasis) and the implications for heritability, trait definitions, natural selection, and therapeutic interventions. Biology is clearly full of causal interactions, so why don't we see them in the data? A 🧵:
open.substack.com
Beneath the surface of the sum
When genetic interactions matter and when they don't
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Josh Weinstock @joshweinstock.bsky.social · 22/07/2025
You can find PRSFNN code here: github.com/weinstockj/PRS . It takes in GWAS summary statistics + LD reference panel + annotations, and we compute the posterior using variational inference to make it fast. A pleasure to build this with @aprilkim.bsky.social and @alexisbattle.bsky.social
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Josh Weinstock @joshweinstock.bsky.social · 22/07/2025
We observed similar non-linear effects with AlphaMissense predictions, where low impact coding variants were prioritized, but highly pathogenic variants were not prioritized (presumably because these are so rare in real GWAS).
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Josh Weinstock @joshweinstock.bsky.social · 22/07/2025
More compellingly, it also learns non-linear effects wrt to chromatin accessibility - variants in cCREs present in 10-50 cell types were more highly prioritized than variants in cCRE that are present in numerous (> 50) cell types, suggesting a preference for cell/tissue specificity.
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Josh Weinstock @joshweinstock.bsky.social · 22/07/2025
In our annotation curation, we included lots of scATAC, cCREs from ENCODE, conservation from Zoonomia, pathogenicity from AlphaMissense, among others. Generally - PRSFNN "learns" that low-frequency SNPs in accessible chromatin are likely to have larger effect sizes (maybe not that surprising).
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Josh Weinstock @joshweinstock.bsky.social · 22/07/2025
We connected the SNP annotations to the parameters of the prior distribution on the weights in a novel way with a neural network, so we're calling it Polygenic Risk Scores with Functional Neural Network (PRSFNN). We were excited to see that PRSFNN does well in benchmarks (at least in our hands).
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Josh Weinstock @joshweinstock.bsky.social · 22/07/2025
Really excited to share our new PRS method, developed with @aprilkim.bsky.social and @alexisbattle.bsky.social ! Our approach is to use a lot of recently developed functional annotations to better estimate the weights of the SNPs. www.medrxiv.org/content/10.1...
medrxiv.org
Polygenic prediction of phenotypes with a neural empirical Bayes approach
Polygenic risk scores (PRS) estimate the expected value of a phenotype based on individual genotypes. Although statistical approaches for calculating PRS have advanced considerably in recent years, fe...
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Josh Weinstock @joshweinstock.bsky.social · 05/06/2025
Congratulations!
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Reposted by Josh Weinstock
Bohan Ni @bohanni.bsky.social · 26/03/2025
Happy to share our work characterizing functional rare SVs in rare diseases with long-read genome sequencing and transcriptomic outlier data: genome.cshlp.org/content/earl...
genome.cshlp.org
Integration of transcriptomics and long-read genomics prioritizes structural variants in rare disease
An international, peer-reviewed genome sciences journal featuring outstanding original research that offers novel insights into the biology of all organisms
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Josh Weinstock @joshweinstock.bsky.social · 05/03/2025
Sharing some of our lecture slides on statistical genetics! 🧬 Co-taught with Mike Epstein, Dave Cutler, Karen Conneely, Jingjing Yang, Jian Hu. Mendelian randomization: weinstocklab.org/lecture_slid... Biobank scale GWAS methods: weinstocklab.org/lecture_slid... Hope they're helpful!
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Reposted by Josh Weinstock
Hakhamanesh Mostafavi @hakha.bsky.social · 01/06/2024
We have multiple postdoc positions available in my group at NYU. Join us if you're interested in complex trait genetics and biology. More information about the lab on our website: mostafavilab.org
mostafavilab.org
Home | Mostafavi Lab
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Reposted by Josh Weinstock
bioRxiv Genomics @biorxiv-genomic.bsky.social · 16/12/2024
Specificity, length, and luck: How genes are prioritized by rare and common variant association studies www.biorxiv.org/content/10.1101/202…
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Reposted by Josh Weinstock
Josh Popp @jmpopp.bsky.social · 04/12/2024
Excited to see our study on genetic regulation in heterogeneous differentiating cultures out in final form! www.cell.com/cell-genomics/fulltext/S2666-979X(24)00330-6
cell.com
Cell type and dynamic state govern genetic regulation of gene expression in heterogeneous differentiating cultures
Popp et al. generate dozens of cell types from 53 human iPSC lines in order to characterize the dynamic genetic regulation of gene expression across early stages of cellular differentiation. Accessing...
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Josh Weinstock @joshweinstock.bsky.social · 22/11/2024
I'm developing a pipeline to call CHIP mutations in UK Biobank using the DNA Nexus RAP that is fast/cheap/reproducible. Initial results are promising; calls looks reasonable and cost to do this across all of UKB is likely < 500$. Feel free to DM if of interest.
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Josh Weinstock @joshweinstock.bsky.social · 03/11/2023
Great talk from Zeyun Lu on integrating cis-eQTLs with perturb-seq to increase discovery in Mendelian randomization #ASHG2023 !
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