Population-scale multiome immune cell atlas reveals complex disease drivers Article Swipe
Jarno Honkanen
,
Rodosthenis S. Rodosthenous
,
Isabella Teixeira-Soldano
,
Han Sung Hwang
,
Yuanxiang Zhang
,
Eric Chen
,
Kosaku Nanki
,
Neelima Mehrotra
,
Emily P. Finan
,
Yixiao Zhu
,
Mikko Arvas
,
Mary Pat Reeve
,
Caroline Porter
,
Jukka Partanen
,
Daniel B. Graham
,
Mark J. Daly
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1101/2025.11.25.25340489
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1101/2025.11.25.25340489
Most genetic variants associated with complex diseases lie in non-coding regions, yet mechanistic insights have been limited by the lack of an empirical framework for characterizing the molecular consequences of regulatory variation. Single-cell profiling of molecular quantitative trait loci (QTL) can connect variants to gene regulation, but prior studies lacked the sample size to detect variants at disease-relevant genes and the simultaneous measurements across regulatory layers needed to trace complete mechanisms from chromatin state to gene expression. Here we show that population-scale simultaneous profiling of chromatin accessibility and gene expression across immune cell types reveals multi-layered regulatory pathways connecting genetic variants to disease. We generated paired single-nucleus ATAC-seq and RNA-seq profiles from 10 million peripheral blood mononuclear cells across 1,108 Finnish individuals, identifying 51,083 cis -eQTLs for 20,829 genes, 338,100 cis -caQTLs for 210,584 peaks, 119,094 fine-mapped variants, and 496,488 enhancer–gene links. Systematic classification of regulatory mechanisms revealed that variants with complete chromatin-to-expression cascades show twice the disease colocalization of chromatin-only effects, establishing a hierarchy where mechanistic cascade predicts disease relevance. Analysis of evolutionarily constrained genes revealed multi-layered regulatory buffering where chromatin accessibility changes occur with normal effect sizes, but transmission to gene expression is attenuated through systematically weaker enhancer–gene links, reconciling why disease variants preferentially target these genes despite apparent eQTL depletion. We incorporated base editing to experimentally validate causal variants and mechanisms at Finnish-enriched disease loci such as TNRC18 . This resource provides testable mechanistic hypotheses for over half of immune disease associations.
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- Type
- preprint
- Landing Page
- https://doi.org/10.1101/2025.11.25.25340489
- https://www.medrxiv.org/content/medrxiv/early/2025/11/27/2025.11.25.25340489.full.pdf
- OA Status
- green
- References
- 100
- OpenAlex ID
- https://openalex.org/W4416753073
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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- DOI
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https://doi.org/10.1101/2025.11.25.25340489Digital Object Identifier
- Title
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Population-scale multiome immune cell atlas reveals complex disease driversWork title
- Type
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preprintOpenAlex work type
- Publication year
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2025Year of publication
- Publication date
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2025-11-27Full publication date if available
- Authors
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Jarno Honkanen, Rodosthenis S. Rodosthenous, Isabella Teixeira-Soldano, Han Sung Hwang, Yuanxiang Zhang, Eric Chen, Kosaku Nanki, Neelima Mehrotra, Emily P. Finan, Yixiao Zhu, Mikko Arvas, Mary Pat Reeve, Caroline Porter, Jukka Partanen, Daniel B. Graham, Mark J. DalyList of authors in order
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https://doi.org/10.1101/2025.11.25.25340489Publisher landing page
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https://www.medrxiv.org/content/medrxiv/early/2025/11/27/2025.11.25.25340489.full.pdfDirect link to full text PDF
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
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https://www.medrxiv.org/content/medrxiv/early/2025/11/27/2025.11.25.25340489.full.pdfDirect OA link when available
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| abstract_inverted_index.10 | 113 |
| abstract_inverted_index.We | 104, 214 |
| abstract_inverted_index.an | 22 |
| abstract_inverted_index.as | 230 |
| abstract_inverted_index.at | 57, 225 |
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| abstract_inverted_index.we | 79 |
| abstract_inverted_index.and | 60, 88, 109, 139, 223 |
| abstract_inverted_index.but | 47, 190 |
| abstract_inverted_index.can | 41 |
| abstract_inverted_index.cis | 125, 131 |
| abstract_inverted_index.for | 25, 127, 133, 239 |
| abstract_inverted_index.lie | 8 |
| abstract_inverted_index.the | 19, 27, 51, 61, 157 |
| abstract_inverted_index.why | 203 |
| abstract_inverted_index.yet | 12 |
| abstract_inverted_index.Here | 78 |
| abstract_inverted_index.Most | 1 |
| abstract_inverted_index.This | 233 |
| abstract_inverted_index.base | 216 |
| abstract_inverted_index.been | 16 |
| abstract_inverted_index.cell | 93 |
| abstract_inverted_index.eQTL | 212 |
| abstract_inverted_index.from | 72, 112 |
| abstract_inverted_index.gene | 45, 76, 89, 193 |
| abstract_inverted_index.half | 241 |
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| abstract_inverted_index.loci | 39, 228 |
| abstract_inverted_index.over | 240 |
| abstract_inverted_index.show | 80, 155 |
| abstract_inverted_index.size | 53 |
| abstract_inverted_index.such | 229 |
| abstract_inverted_index.that | 81, 149 |
| abstract_inverted_index.with | 5, 151, 186 |
| abstract_inverted_index.(QTL) | 40 |
| abstract_inverted_index.1,108 | 120 |
| abstract_inverted_index.blood | 116 |
| abstract_inverted_index.cells | 118 |
| abstract_inverted_index.genes | 59, 176, 209 |
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| abstract_inverted_index.prior | 48 |
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| abstract_inverted_index.trace | 69 |
| abstract_inverted_index.trait | 38 |
| abstract_inverted_index.twice | 156 |
| abstract_inverted_index.types | 94 |
| abstract_inverted_index.where | 166, 181 |
| abstract_inverted_index.-eQTLs | 126 |
| abstract_inverted_index.20,829 | 128 |
| abstract_inverted_index.51,083 | 124 |
| abstract_inverted_index.TNRC18 | 231 |
| abstract_inverted_index.across | 64, 91, 119 |
| abstract_inverted_index.causal | 221 |
| abstract_inverted_index.detect | 55 |
| abstract_inverted_index.effect | 188 |
| abstract_inverted_index.genes, | 129 |
| abstract_inverted_index.immune | 92, 243 |
| abstract_inverted_index.lacked | 50 |
| abstract_inverted_index.layers | 66 |
| abstract_inverted_index.links, | 201 |
| abstract_inverted_index.links. | 142 |
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| abstract_inverted_index.normal | 187 |
| abstract_inverted_index.paired | 106 |
| abstract_inverted_index.peaks, | 135 |
| abstract_inverted_index.sample | 52 |
| abstract_inverted_index.sizes, | 189 |
| abstract_inverted_index.target | 207 |
| abstract_inverted_index.weaker | 199 |
| abstract_inverted_index.-caQTLs | 132 |
| abstract_inverted_index.119,094 | 136 |
| abstract_inverted_index.210,584 | 134 |
| abstract_inverted_index.338,100 | 130 |
| abstract_inverted_index.496,488 | 140 |
| abstract_inverted_index.Finnish | 121 |
| abstract_inverted_index.RNA-seq | 110 |
| abstract_inverted_index.cascade | 168 |
| abstract_inverted_index.changes | 184 |
| abstract_inverted_index.complex | 6 |
| abstract_inverted_index.connect | 42 |
| abstract_inverted_index.despite | 210 |
| abstract_inverted_index.disease | 158, 170, 204, 227, 244 |
| abstract_inverted_index.editing | 217 |
| abstract_inverted_index.genetic | 2, 100 |
| abstract_inverted_index.limited | 17 |
| abstract_inverted_index.million | 114 |
| abstract_inverted_index.reveals | 95 |
| abstract_inverted_index.studies | 49 |
| abstract_inverted_index.through | 197 |
| abstract_inverted_index.ATAC-seq | 108 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.Analysis | 172 |
| abstract_inverted_index.apparent | 211 |
| abstract_inverted_index.cascades | 154 |
| abstract_inverted_index.complete | 70, 152 |
| abstract_inverted_index.disease. | 103 |
| abstract_inverted_index.diseases | 7 |
| abstract_inverted_index.effects, | 162 |
| abstract_inverted_index.insights | 14 |
| abstract_inverted_index.pathways | 98 |
| abstract_inverted_index.predicts | 169 |
| abstract_inverted_index.profiles | 111 |
| abstract_inverted_index.provides | 235 |
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| abstract_inverted_index.revealed | 148, 177 |
| abstract_inverted_index.testable | 236 |
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| abstract_inverted_index.variants | 3, 43, 56, 101, 150, 205, 222 |
| abstract_inverted_index.buffering | 180 |
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| abstract_inverted_index.framework | 24 |
| abstract_inverted_index.generated | 105 |
| abstract_inverted_index.hierarchy | 165 |
| abstract_inverted_index.molecular | 28, 36 |
| abstract_inverted_index.profiling | 34, 84 |
| abstract_inverted_index.variants, | 138 |
| abstract_inverted_index.Systematic | 143 |
| abstract_inverted_index.associated | 4 |
| abstract_inverted_index.attenuated | 196 |
| abstract_inverted_index.connecting | 99 |
| abstract_inverted_index.depletion. | 213 |
| abstract_inverted_index.expression | 90, 194 |
| abstract_inverted_index.hypotheses | 238 |
| abstract_inverted_index.mechanisms | 71, 147, 224 |
| abstract_inverted_index.non-coding | 10 |
| abstract_inverted_index.peripheral | 115 |
| abstract_inverted_index.regulatory | 31, 65, 97, 146, 179 |
| abstract_inverted_index.relevance. | 171 |
| abstract_inverted_index.variation. | 32 |
| abstract_inverted_index.Single-cell | 33 |
| abstract_inverted_index.constrained | 175 |
| abstract_inverted_index.expression. | 77 |
| abstract_inverted_index.fine-mapped | 137 |
| abstract_inverted_index.identifying | 123 |
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| abstract_inverted_index.reconciling | 202 |
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| abstract_inverted_index.colocalization | 159 |
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| abstract_inverted_index.experimentally | 219 |
| abstract_inverted_index.preferentially | 206 |
| abstract_inverted_index.single-nucleus | 107 |
| abstract_inverted_index.systematically | 198 |
| abstract_inverted_index.enhancer–gene | 141, 200 |
| abstract_inverted_index.Finnish-enriched | 226 |
| abstract_inverted_index.disease-relevant | 58 |
| abstract_inverted_index.population-scale | 82 |
| abstract_inverted_index.chromatin-to-expression | 153 |
| cited_by_percentile_year | |
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| institutions_distinct_count | 16 |
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