Jonathan Sebat
@sebatlab.bsky.social
Psychiatric genetics, complex trait genetics, genome sequencing, rare variants are my jam
As a novel approach to causal inference, we will use collider effects to find genetic evidence to SUPPORT a causal role of environmental exposure. If E has a strong effect that is uncorrelated with G in the population, genes will explain LESS of the variance in the explosed group!
September 26, 2025 at 11:32 PM
As a novel approach to causal inference, we will use collider effects to find genetic evidence to SUPPORT a causal role of environmental exposure. If E has a strong effect that is uncorrelated with G in the population, genes will explain LESS of the variance in the explosed group!
Our 2022 paper in NG illustrates one example: the observed association of parental age with ausism consists of a mixture of causal pathway E → de novo mutation → ASD; and noncausal pathway Parental age ← polygenic score → ASD
September 26, 2025 at 11:27 PM
Our 2022 paper in NG illustrates one example: the observed association of parental age with ausism consists of a mixture of causal pathway E → de novo mutation → ASD; and noncausal pathway Parental age ← polygenic score → ASD
We will use a multi-pronged approach to causal inference using data on G and E in >2 million people, including association, MR and GxE exploring the interplay of exposures with rare and common variation that contributes to ASD, and we will rigorously evaluate rGE in family and population
September 26, 2025 at 11:15 PM
We will use a multi-pronged approach to causal inference using data on G and E in >2 million people, including association, MR and GxE exploring the interplay of exposures with rare and common variation that contributes to ASD, and we will rigorously evaluate rGE in family and population
THE major challenge in epidemiological studies of the environment in autism is the pervasive passive correlation of genes and environment (rGE) that happens in the population, also known horizontal pleiotropy. There are causal effects to be found, but we need to separate correlation from causation
September 26, 2025 at 11:05 PM
THE major challenge in epidemiological studies of the environment in autism is the pervasive passive correlation of genes and environment (rGE) that happens in the population, also known horizontal pleiotropy. There are causal effects to be found, but we need to separate correlation from causation
Bad ass mom of the year 🤘. This was NOT an easy coffee ride. This was the Saturday Cadence Cyclery ride in SD.
August 16, 2025 at 7:37 PM
Bad ass mom of the year 🤘. This was NOT an easy coffee ride. This was the Saturday Cadence Cyclery ride in SD.
Power is limited in N=243. But the signal is quantifiable. Rare SVs, TRs and rare SNVs combined explained 7.6% of the heritability. We will need larger samples to get precise estimates, but the combined common and rare is starting to reach a substantial fraction.
July 23, 2025 at 11:42 PM
Power is limited in N=243. But the signal is quantifiable. Rare SVs, TRs and rare SNVs combined explained 7.6% of the heritability. We will need larger samples to get precise estimates, but the combined common and rare is starting to reach a substantial fraction.
Gray zone carriers typically look like panel E. Only FMR1 methylation is skewed. X chromosome inactivation is not skewed. The one exception (panel D) was a girl that carried an X-linked dominant mutation in DDX3X a gene that escapes XCI and, for unknown reasons, is know to cause skewed XCI
July 23, 2025 at 11:36 PM
Gray zone carriers typically look like panel E. Only FMR1 methylation is skewed. X chromosome inactivation is not skewed. The one exception (panel D) was a girl that carried an X-linked dominant mutation in DDX3X a gene that escapes XCI and, for unknown reasons, is know to cause skewed XCI
Skewed methylation was a characteristic of all "gray zone" alleles of FMR1 (>35 repeats). But in all but one sample, the skewing was specific to FMR1. X chromosome inactivation was NOT skewed. 10/N
July 23, 2025 at 11:33 PM
Skewed methylation was a characteristic of all "gray zone" alleles of FMR1 (>35 repeats). But in all but one sample, the skewing was specific to FMR1. X chromosome inactivation was NOT skewed. 10/N
In the fragile X repeat FMR1, we went full long-read nerd with PHASED repeats AND methylation. Phased reads in one female (REACH365) shows random methylation (red) on the X. In another female (REACH561) with an expanded 49 repeat allele, methylation was totally skewed to expanded haplotype H2 9/N
July 23, 2025 at 11:30 PM
In the fragile X repeat FMR1, we went full long-read nerd with PHASED repeats AND methylation. Phased reads in one female (REACH365) shows random methylation (red) on the X. In another female (REACH561) with an expanded 49 repeat allele, methylation was totally skewed to expanded haplotype H2 9/N
Where long reads really shine is when you need to map out and assemble large complex SVs. In doing so, we found a class of duplication/deletion events (TAN-DUP-DEL and INV-DUP-DEL) events. They also produce distinct signatures in short read coverage data
July 23, 2025 at 11:19 PM
Where long reads really shine is when you need to map out and assemble large complex SVs. In doing so, we found a class of duplication/deletion events (TAN-DUP-DEL and INV-DUP-DEL) events. They also produce distinct signatures in short read coverage data
De novo SVs have been bread-and-butter of ASD genetics, and LRs detect novel de novo and somatic MOSAIC coding SVs. In this example, a de novo in-frame duplication, was present on most (but not all) reads on the H2 haplotype in the offspring and coverage also showed copy number of 2.5 instead of 3.
July 23, 2025 at 11:12 PM
De novo SVs have been bread-and-butter of ASD genetics, and LRs detect novel de novo and somatic MOSAIC coding SVs. In this example, a de novo in-frame duplication, was present on most (but not all) reads on the H2 haplotype in the offspring and coverage also showed copy number of 2.5 instead of 3.
Panel C (coding SVs in constrained genes) are a class variants with well-established associations with ASD. To maximize detection of these, one needs a combination of short reads and long reads. For large (>50 bp) tandem repeat variants, long reads alone do a good job 4/N.
July 23, 2025 at 11:07 PM
Panel C (coding SVs in constrained genes) are a class variants with well-established associations with ASD. To maximize detection of these, one needs a combination of short reads and long reads. For large (>50 bp) tandem repeat variants, long reads alone do a good job 4/N.
a susbstantial fraction of SVs are only detetable with LRs. However, there is also a significant fraction of SVs that are detectable only with Illumina WGS, particularly large CNVs that are detectable based on coverage. (A) All SVs (B) coding SVs (C) coding SVs in constrained genes (pLI>0.9).
July 23, 2025 at 11:01 PM
a susbstantial fraction of SVs are only detetable with LRs. However, there is also a significant fraction of SVs that are detectable only with Illumina WGS, particularly large CNVs that are detectable based on coverage. (A) All SVs (B) coding SVs (C) coding SVs in constrained genes (pLI>0.9).
While not attributable to the major loci, patterns are consistent within them. When you look closely at cell-type specific gene expression in DUP 16p11.2 or DEL 22q11.2, you begin to appreciate how the effects of a CNV can be mediated through distinct pathways across a variety of cell types
July 17, 2025 at 12:25 AM
While not attributable to the major loci, patterns are consistent within them. When you look closely at cell-type specific gene expression in DUP 16p11.2 or DEL 22q11.2, you begin to appreciate how the effects of a CNV can be mediated through distinct pathways across a variety of cell types
Factor F2 was driven by differential DUP effects in neuronal vs non-neuronal cell types in mood disorders. F3 by differential spatial patterns of DEL effects in MDD and ADHD. The 3 factors, factor loadings and factor scores remain concordant after we remove all 18 genome-wide significant loci
July 17, 2025 at 12:20 AM
Factor F2 was driven by differential DUP effects in neuronal vs non-neuronal cell types in mood disorders. F3 by differential spatial patterns of DEL effects in MDD and ADHD. The 3 factors, factor loadings and factor scores remain concordant after we remove all 18 genome-wide significant loci
As a reminder, DEL effects are concentrated in visual, auditory, sensorimotor. DUP effects are more frontal. Dose dependent effects in SCZ appear to show differential patterns at multiple levels synaptic/regulatory, excitatory/inhibitory, sensory/association
July 17, 2025 at 12:13 AM
As a reminder, DEL effects are concentrated in visual, auditory, sensorimotor. DUP effects are more frontal. Dose dependent effects in SCZ appear to show differential patterns at multiple levels synaptic/regulatory, excitatory/inhibitory, sensory/association
The major factor F1 represents dose-dependent effects in SCZ characterized by DUP effects in Reg pathways in postnatal Exc. neurons, neurovascular, microglia - and divergent DEL effects in synaptic, Ca+, axon guidance in postnatal Inh. neurons as well as early fetal neurons.
July 16, 2025 at 11:57 PM
The major factor F1 represents dose-dependent effects in SCZ characterized by DUP effects in Reg pathways in postnatal Exc. neurons, neurovascular, microglia - and divergent DEL effects in synaptic, Ca+, axon guidance in postnatal Inh. neurons as well as early fetal neurons.
To elucidate where gene-dosage effects converge, we performed exploratory factor analysis of functional gene sets to identify latent factors that correspond to different gene-trait relationships. In all Dx's except ASD DEL and DUP effects form distinct components in distinct neural processes
July 16, 2025 at 11:51 PM
To elucidate where gene-dosage effects converge, we performed exploratory factor analysis of functional gene sets to identify latent factors that correspond to different gene-trait relationships. In all Dx's except ASD DEL and DUP effects form distinct components in distinct neural processes
To characterize how gene dosage effects are distributed in the brain, we performed GSBA on the the intersections of pathways, cell types, and brain regions. We then evaluated which levels of biological organization best explain variation in gene-set effects in mixed effects models
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July 16, 2025 at 11:34 PM
To characterize how gene dosage effects are distributed in the brain, we performed GSBA on the the intersections of pathways, cell types, and brain regions. We then evaluated which levels of biological organization best explain variation in gene-set effects in mixed effects models
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Team members @kkumar.bsky.social and Sebastien Jacquemont devised some interesting ways to apply GSBA to gene sets highly expressed in 180 cortical brain regions. When gene set associations are projected on the brain map, Psych Dxs differ in the spatial distribution of DEL and DUP effects
July 16, 2025 at 11:12 PM
Team members @kkumar.bsky.social and Sebastien Jacquemont devised some interesting ways to apply GSBA to gene sets highly expressed in 180 cortical brain regions. When gene set associations are projected on the brain map, Psych Dxs differ in the spatial distribution of DEL and DUP effects
Considering 1 level of biological organization at a time, the pathways and cell types associated with ASD, SCZ and other disorders are exactly as we expected. But we begin to see DIVERGENCE between Dx's when we stratify by DOSAGE. In SCZ, DUP→core regulatory pathways, DEL→synapse, calcium...
July 16, 2025 at 11:05 PM
Considering 1 level of biological organization at a time, the pathways and cell types associated with ASD, SCZ and other disorders are exactly as we expected. But we begin to see DIVERGENCE between Dx's when we stratify by DOSAGE. In SCZ, DUP→core regulatory pathways, DEL→synapse, calcium...
Given that CNVs exhibit dose dependent effects on psychiatric traits, we developed a framework to characterize how gene-Dx relationships are mediated by pathway, cell type, brain regions. We begin with a statistical genetic approach Gene Set Burden Analysis (GSBA)
July 16, 2025 at 10:55 PM
Given that CNVs exhibit dose dependent effects on psychiatric traits, we developed a framework to characterize how gene-Dx relationships are mediated by pathway, cell type, brain regions. We begin with a statistical genetic approach Gene Set Burden Analysis (GSBA)
And gene findings in schizophrenia were also, you guessed it, synaptic, chromatin, cell signaling etc. 3/N
July 16, 2025 at 10:44 PM
And gene findings in schizophrenia were also, you guessed it, synaptic, chromatin, cell signaling etc. 3/N
From the early days of autism genetics PMID: 24768552, we marveled at all the "functional convergence". The genes that were identified by CNV, whole exome studies were clearly pointing at pathways that regulate early brain development! including synaptic, chromatin, cell signaling 2/N
July 16, 2025 at 10:36 PM
From the early days of autism genetics PMID: 24768552, we marveled at all the "functional convergence". The genes that were identified by CNV, whole exome studies were clearly pointing at pathways that regulate early brain development! including synaptic, chromatin, cell signaling 2/N