Back

Enhanced Hi-C Capture Analysis reveals complex regulatory architecture at the PICALM-EED locus for Alzheimer Disease

Nasciben, L. B.; Wang, l.; Xu, W.; Ramirez, A.; Moura, S.; Lu, L.; Liu, X.; Rajabli, F.; Celis, K.; Gearing, M.; Bennett, D.; Weintraub, S.; Geula, C.; Schuck, T.; Nuytemans, K.; Scott, W.; Dykxhoorn, D.; PERICAK-VANCE, M. A.; Young, J.; Griswold, A.; Jin, F.; Vance, J. M.

2026-02-17 genomics
10.64898/2026.02.14.705927 bioRxiv
Show abstract

ObjectiveBoth the phosphatidylinositol binding clathrin assembly protein gene (PICALM) and the embryonic ectoderm development gene (EED) have been implicated as causal genes driving a genome-wide association for Alzheimer disease (AD) risk. We employed a new virtual approach using genome-wide chromatin interactions (Hi-C) called enhanced Hi-C Capture Analysis (eHiCA) to identify the genes and regulatory regions that are driving this important AD risk association. MethodsHi-C data from the frontal cortex of eight AD patients, as well as inducible pluripotent stem cell-derived microglia and spheroids of AD and control patients were used. We applied 14 eHiCA baits each containing a GWAS SNP to identify the cis regulatory interactions in this GWAS locus at a 5kb resolution. ResultsThe baits derived from the GWAS associated haplotype primarily interacted with the PICALM promoter and the large cis-regulatory elements cluster (CREe) lying upstream of the EED promoter. The EED promoter interacts with PICALM gene body and promoter region but not directly with the associated risk haplotype. Although the AD-associated variants segregate together as a haplotype in the population, each bait exhibited distinct functional chromatin interactions. InterpretationThe PICALM gene is the primary driver of the association in microglia along with the CREe locus. Different SNPs in a segregating haplotype can display different physical Hi-C interactions. This study demonstrates that eHiCA can help resolve the casual genes driving complex GWAS associations, opening new pathways to study Alzheimer disease and other disorders.

Matching journals

The top 10 journals account for 50% of the predicted probability mass.

1
Bioinformatics
1061 papers in training set
Top 3%
10.2%
2
Alzheimer's & Dementia
143 papers in training set
Top 0.8%
9.2%
3
Journal of Alzheimer’s Disease
39 papers in training set
Top 0.1%
6.4%
4
International Journal of Epidemiology
74 papers in training set
Top 0.5%
4.2%
5
Alzheimer's Research & Therapy
52 papers in training set
Top 0.6%
4.0%
6
Frontiers in Genetics
197 papers in training set
Top 2%
4.0%
7
Scientific Reports
3102 papers in training set
Top 36%
3.6%
8
PLOS ONE
4510 papers in training set
Top 39%
3.6%
9
Nature Communications
4913 papers in training set
Top 42%
3.1%
10
BMC Genomics
328 papers in training set
Top 1%
3.1%
50% of probability mass above
11
Briefings in Bioinformatics
326 papers in training set
Top 3%
2.6%
12
Computational and Structural Biotechnology Journal
216 papers in training set
Top 3%
2.4%
13
Communications Biology
886 papers in training set
Top 5%
2.1%
14
Cell Genomics
162 papers in training set
Top 2%
2.1%
15
Nucleic Acids Research
1128 papers in training set
Top 8%
2.1%
16
Genome Medicine
154 papers in training set
Top 4%
1.9%
17
Genetic Epidemiology
46 papers in training set
Top 0.4%
1.7%
18
Human Genetics and Genomics Advances
70 papers in training set
Top 0.3%
1.7%
19
PLOS Computational Biology
1633 papers in training set
Top 16%
1.7%
20
BMC Bioinformatics
383 papers in training set
Top 5%
1.5%
21
Human Molecular Genetics
130 papers in training set
Top 2%
1.5%
22
BMC Medical Genomics
36 papers in training set
Top 0.6%
1.3%
23
iScience
1063 papers in training set
Top 19%
1.3%
24
Human Genomics
21 papers in training set
Top 0.2%
1.3%
25
PLOS Genetics
756 papers in training set
Top 14%
0.8%
26
The American Journal of Human Genetics
206 papers in training set
Top 3%
0.8%
27
NAR Genomics and Bioinformatics
214 papers in training set
Top 4%
0.8%
28
eLife
5422 papers in training set
Top 57%
0.8%
29
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring
38 papers in training set
Top 1%
0.6%
30
Genomics
60 papers in training set
Top 3%
0.6%