Genetic regulation of gene expression in human brain cell types

We leveraged single nuclei RNA-seq from 192 human brain samples to map cis-eQTLs in 8 brain cell types. We found extensive cell-type specific genetic effect on gene expression and integrated our results with GWAS to identify putative novel risk genes for brain disorders and the cell types in which the disease mechanisms are likely active.

Type: Other
Archiver: European Genome-Phenome Archive (EGA)

3 Datasets 2 Publications

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID	Description	Technology	Samples
EGAD00001009166	The Roche Alzheimer’s disease dataset (Roche_AD) consists of 80 samples from 40 unique individuals (one sample from the temporal cortex and one from deep white matter for each individual, 12 cases, 25 controls, 3 dementia). A total of 12,000 estimated cells from each sample were loaded on the 10x Single Cell Next GEM G Chip. cDNA libraries were prepared using the Chromium Single Cell 3’ Library and Gel Bead v3 kit according to the manufacturer’s instructions. cDNA libraries were sequenced using the Illumina NovaSeq 6000 System and NovaSeq 6000 S2 Reagent Kit v1.5 (100 cycles), aiming at a sequencing depth of minimum 30K reads/nucleus.		80
EGAD00001009168	The Columbia Alzheimer’s dataset (white matter) consists of 24 white matter individuals (12 controls, 12 cases). A total of 12,000 estimated cells from each sample were loaded on the 10x Single Cell Next GEM G Chip. cDNA libraries were prepared using the Chromium Single Cell 3’ Library and Gel Bead v3 kit according to the manufacturer’s instructions. cDNA libraries were sequenced using the Illumina NovaSeq 6000 System and NovaSeq 6000 S2 Reagent Kit v1.5 (100 cycles), aiming at a sequencing depth of minimum 30K reads/nucleus.		24
EGAD00001009169	The Roche multiple sclerosis dataset (Roche_MS) consists of 166 cortical grey matter (GM) and white matter (WM) samples from 83 unique individuals (29 controls and 54 cases). A total of 12,000 estimated cells from each sample were loaded on the 10x Single Cell Next GEM G Chip. cDNA libraries were prepared using the Chromium Single Cell 3’ Library and Gel Bead v3 kit according to the manufacturer’s instructions. cDNA libraries were sequenced using the Illumina NovaSeq 6000 System and NovaSeq 6000 S2 Reagent Kit v1.5 (100 cycles), aiming at a sequencing depth of minimum 30K reads/nucleus.	Illumina NovaSeq 6000	166

Publications	Citations
Androgens show sex-dependent differences in myelination in immune and non-immune murine models of CNS demyelination. Zahaf A, Kassoussi A, Hutteau-Hamel T, Mellouk A, Marie C, Zoupi L, Tsouki F, Mattern C, Bobé P, Schumacher M, Williams A, Parras C, Traiffort E. Nat Commun 14: 2023 1592	12
Cell state-dependent allelic effects and contextual Mendelian randomization analysis for human brain phenotypes. Haglund A, Zuber V, Abouzeid M, Yang Y, Ko JH, Wiemann L, Otero-Jimenez M, Muhammed L, Feleke R, Nott A, Mills JD, Laaniste L, Gveric DO, Clode D, Babtie AC, Pagni S, Bellampalli R, Somani A, McDade K, Anink JJ, Mesarosova L, Fancy N, Willumsen N, Smith A, Jackson J, Alegre-Abarrategui J, Aronica E, Matthews PM, Thom M, Sisodiya SM, Srivastava PK, Malhotra D, Bryois J, Bottolo L, Johnson MR. Nat Genet 57: 2025 358-368	0

Publications

Citations

Androgens show sex-dependent differences in myelination in immune and non-immune murine models of CNS demyelination.
Zahaf A, Kassoussi A, Hutteau-Hamel T, Mellouk A, Marie C, Zoupi L, Tsouki F, Mattern C, Bobé P, Schumacher M, Williams A, Parras C, Traiffort E. Nat Commun 14: 2023 1592

Cell state-dependent allelic effects and contextual Mendelian randomization analysis for human brain phenotypes.
Haglund A, Zuber V, Abouzeid M, Yang Y, Ko JH, Wiemann L, Otero-Jimenez M, Muhammed L, Feleke R, Nott A, Mills JD, Laaniste L, Gveric DO, Clode D, Babtie AC, Pagni S, Bellampalli R, Somani A, McDade K, Anink JJ, Mesarosova L, Fancy N, Willumsen N, Smith A, Jackson J, Alegre-Abarrategui J, Aronica E, Matthews PM, Thom M, Sisodiya SM, Srivastava PK, Malhotra D, Bryois J, Bottolo L, Johnson MR. Nat Genet 57: 2025 358-368