Excited to share this preprint from first author Jon Rosen, a postdoctoral fellow in the @klmohlke.bsky.social lab and my lab. We examine eQTL study sample size and how this affects signal discovery and rates of colocalization with GWAS. www.biorxiv.org/content/10.1...

Very happy to be back in Boston for #ASHG25🧬 this time as a PI! Very proud of my stellar PhD student Jiawei who’s giving a platform talk on her work quantifying influences of genetic ancestry and the environment on tumor somatic alterations and survival. 🗓️ Wed Oct 15 11:15AM

In 2018, Charles Murray challenged me to a bet: "We will understand IQ genetically—I think most of the picture will have been filled in by 2025—there will still be blanks—but we’ll know basically what’s going on." It's now 2025, and I claim a win. I write about it in The Atlantic.

Massive sibling regression study finds that human traits are largely environmentally driven (average heritability = 0.3)

Interesting evidence for genetics explaining disparities in T2D. Previous work identified a Neanderthal introgressed haplotype common to Native American ancestry with a large effect on T2D (pmc.ncbi.nlm.nih.gov/articles/PMC...). Wonder if there's power to look at archaic admixture here.

Brilliant paper by Visscher et al. Populations differ in traits/disease burden. Are these differences due to genetics? Comparing single variants or polygenic scores between populations is biased due to environmental confounders correlated with the variants. 1/3 www.medrxiv.org/content/10.1...

Delighted to see this paper with @anaignatieva.bsky.social now published in Genetics! academic.oup.com/genetics/adv... We tackle a thorny issue arising in statistical tests for genetic interactions (epistasis) using ancestral recombination graphs (ARGs)... 🧵

Excited to share our latest manuscript, "Exposure accumulation drives age-dependent disease architectures and polygenic risk scores," led by Xilin Jiang: www.medrxiv.org/content/10.1... I am attempting an explainer thread for the first time here: (I am usually too exhausted to post one)

I wrote about a rare genetic variant (a CNV) that appears to reduce the risk of schizophrenia diagnosis by ~5x, and why that's not as unambigously amazing as it sounds, but potentially still a pretty big deal.

Great mini thread here on lessons for GxG and GxE from non-human organisms:

Nice blog and good to see this also from the twins/shared environment side. We (with my colleagues in @wittbrodtlab.bsky.social) have tried to tackle the non-additive in experimental settings (in medaka fish) which we can map to human (as the medaka fish are "wild") www.biorxiv.org/content/10.1...

🧵 on cool choices of image headers (and titles) all from @sashagusevposts.bsky.social's Substack 🔗 at the end 'Beneath the surface of the sum' Genetic interactions may look like the thing they deviate from Interaction (1964) by Julian Stanczak

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 🧵:

The twin/family studies were not clear whether it was dominance vs. epistasis vs. some other sort of nonadditivity. Dominance was just the easiest to model. We can now estimate dominance SNP h2 but can’t obtain an estimate of epistatic SNP h2. Assimilation/contrast effects may also be at play.

While I am not entirely convinced this is “real” and not some psychometric equivalent of a vowel shift (and PRS could help find out a bit I think) this it is relevant:

One of the largest twin studies of personality anticipated massive non-additive dominance/epistasis components. These have not materialized with modern data for *any trait*, no one knows why, and the entire set of findings has apparently been memory-holed.

Decrease in phenotype by intervening on additive or epistatic mechanisms in the presence of low (left) or high (right) epistasis. Red lines indicate an increase in the phenotype when a decrease was intended.

Popgen, day7: single-locus selection models. Allele frequency change is faster at intermediate frequencies! Fixation takes longer in larger pops! And a bit more from yesterday on MK (asymptotic MK test is cool!)

Any discussion of embryo selection should probably start with the description of IVF in this piece, to at least be connected to some aspect of tangiable reality.

The use of dichotomized labels for traits that are actually continuous has bothered me ever since I started working on complex trait genetics. Sasha's blog post provides an excellent explanation of why this matters in the context of polygenic risk and embryo selection.

Great thread! We make this point in the NEJM paper, but I think it flew under the radar for many.

I wrote about how genetic risk works in the context of embryo selection and how people often think about it all wrong. A short 🧵:

An old article on "PolygenX" marketing IQ embryo selection and its links to the far-right. The newly launched company HeraSight seems to share a pretty similar business model to PolygenX and an overlapping set of employees. investigations.hopenothate.org.uk/superbaby-fa...

Arun Durvasula, PhD, of @uscpphs.bsky.social writes, "Lifestyle factors play a large role in determining who gets a disease and who doesn’t. But they are far from the entire story." A fascinating read about the relationship between genetics and our environment. ⬇️ 🔗 #Science #MedSky #ResearchSky

The proportion of epistatic heritability that is estimated as additive by quantitative genetic models. Epistasis deviates more from additivity for lower frequency causal alleles, but on average >80% of biological GxG will just look like statistical G.

A few thoughts on Herasight, the new embryo selection company. First, their whitepaper (drive.google.com/file/d/1EpFi...) implies that competitors like Nucleus have been marketing and selling grossly erroneous risk estimates. This is shocking if true! 🧵

It is depressing, but all too predictable, how swiftly we’ve gone from the Social Science Genetic Association Consortium offering reassurances about the uses of behavioural polygenic scores to one of their lead authors marketing embryo selection for IQ

Leena Peltonen School of Human Genetics in full-swing! @gosiatrynka.bsky.social @dgmacarthur.bsky.social @bpasaniuc.bsky.social @tuuliel.bsky.social @hilarycmartin.bsky.social @sashagusevposts.bsky.social @zkutalik.bsky.social @mashaals.bsky.social @alemedinarivera.bsky.social

Good take on Columbia: "Higher ed policy in the United States is now being developed through ad hoc deals, a mode of regulation that is not only inimical to the ideal of the university as a site of critical thinking but also corrosive to the democratic order and to law itself."

Very happy to share our new paper now on @medrxivpreprint: “Genetic risk effects on psychiatric disorders act in sets”, a great effort led my PhD student @jolienrietkerk.bsky.social, and performed together with collaborators Andy Dahl, Jonathan Flint, Andrew Schork etc. Thread 1/n

Super excited to see this out. What started as some math in a grant in 2020, to a student deciding to take this on in 2022, to published in 2025. These things can take time and patience is key!

Very excited to share new work from my PhD on a new software package for eQTL mapping: quasar. The quasar software package is a C++ program designed to provide a flexible and efficient eQTL mapping. www.medrxiv.org/content/10.1...

People often intuitively interpret genetic ancestry PCA plots as simple genetic distances, but this is not always the case. Below are random pairs of individuals that are far apart in PCA space (lines) but actually have fewer total variant differences (numbers).

Nice discussion here. A particularly good point about why we both do and do not care about heritability.

The field of neuroscience views the goal of human genetics as "finding genes". This is an outdated view. In whole genome studies of rare variants, finding genes is the easy part. The more interesting and important goal is to map out the causal pathway from genes to brain function to cognitive traits

Playing around with AI research agents and they very quickly fall down analysis black holes that are difficult to climb out of or debug (e.g. can't download real data so simulate nonsense data). At the moment, I would much prefer an agent that constantly checks in.

MZ twins are much more correlated in their self-reported humor than DZ twins, but external assessment of humor ability shows no difference at all. Seems like a clear case of environmentally driven DZ twin divergence on self-perceived behavior. [ Greengross et al. pubmed.ncbi.nlm.nih.gov/40619903/ ]

A must-read piece by @sashagusevposts.bsky.social I'll be That Guy™ and point out that this is why highly distributed pedigrees are used in evolution and animal breeding in nonexperimental settings. Sibs alone (esp. twins) give bad estimates. Good to see human gen getting on board.

Sasha writes about our new study (led by bluesky-less Nikolai Eftedal) where we show how simple genetic models don't adequately fit correlations between multiple types of relatives. The mismatch between observed and expected correlations are interesting, which are explained well in his blog post:

🚨New preprint is out! How do genetic effects on complex traits change with age? In this work, we compare different approaches to obtain age-varying genetic effects, and show how design and modeling choices can impact the conclusions we draw. shorturl.at/17snd A thread 🧵👇

I wrote a little bit about a cool recent paper looking at heritability estimates from very large registry data, and how we still really don't understand why outcomes track in families. A short 🧵:

Very interesting post by @sashagusevposts.bsky.social on a recent paper showing that simple generic models don't explain the inheritance of traits in a comprehensive way. open.substack.com/pub/theinfin...

News Flash! Effect sizes don't matter! The polygenic score world is moving from anger/denial to the bargaining phase. (Thanks Sasha) ‪@hughjonesd.bsky.social‬.

If I'm reading the new STATE ( Adduri et al. , arcinstitute.org/manuscripts/... ) paper correctly, we still cannot predict the effect of genetic perturbations better than a simple mean, and many methods do worse?

Cool work from AlphaGenome ( storage.googleapis.com/deepmind-med... ). Interesting how challenging it still is to predict even just the direction of distal QTLs.

Last week, our new paper on indirect assortative mating was published.🍾 Let’s take a closer look at what this means, why it matters, and what we found (🧵/32): www.nature.com/articles/s41...

Delighted to have our work on Polygenic Modifiers of #TelomereBiologyDisorders, led by Michael Poeschla, @sashagusevposts.bsky.social, @mitchiela.bsky.social, @sharonsavage.bsky.social, @tummalalab.bsky.social, + co, published in @jclinical-invest.bsky.social today: www.jci.org/articles/vie...

So selection on traits will induce LD. However, it will often be -ve LD between like-effect variants and so goes in the opposite direction as +ve AM (and so biases estimates of AM down). Carl & I discuss this some here, and give some numbers for plausible params: journals.plos.org/plosbiology/...