Back

Generation and characterization of a patient-specific human induced pluripotent stem cell line from a Skogholt syndrome patient (ASCFi003-A)

Przybyla, W.; Gupta, S.; Fjerdingstad, H. B.; Selnes, P.; Sharma, K.

2026-08-31 cell biology
10.64898/2026.08.29.747981 bioRxiv
Show abstract

We report the generation and characterization of a human induced pluripotent stem cell (iPSC) line derived from dermal fibroblasts of a patient with Skogholt disease, a rare maternally inherited neurodegenerative syndrome associated with choroid plexus dysfunction and impaired cerebrospinal fluid (CSF) homeostasis. Patient fibroblasts were reprogrammed using the non-integrating Repro-OSKGM kit. The resulting iPSC line exhibited typical pluripotent morphology, expressed canonical pluripotency markers, maintained a normal karyotype, retained the disease-associated genetic variant, was mycoplasma-free, and demonstrated trilineage differentiation potential. We also made choroid plexus (ChP) like organoids from the generated iPSCs. This patient-specific iPSC line provides a valuable resource for generating choroid plexus organoids and neurons to investigate disease mechanisms and develop therapeutic strategies.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

1
Stem Cell Reports
○ 130 papers in training set
Top 0.2%
12.7%
Similar papers in this journal
2
Scientific Reports
○ 3612 papers in training set
Top 3%
11.2%
Similar papers in this journal
3
PLOS ONE
● 5266 papers in training set
Top 26%
5.6%
Similar papers in this journal
4
Nature Communications
○ 5641 papers in training set
Top 26%
5.6%
Similar papers in this journal
5
Orphanet Journal of Rare Diseases
○ 21 papers in training set
Top 0.1%
5.6%
Similar papers in this journal
6
Cell Death & Disease
147 papers in training set
Top 0.5%
4.9%
7
Disease Models & Mechanisms
139 papers in training set
Top 0.4%
4.5%
50% of probability mass above
8
Communications Biology
○ 993 papers in training set
Top 5%
3.3%
9
Experimental Cell Research
○ 28 papers in training set
Top 0.1%
2.4%
10
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 23%
2.2%
11
EMBO Reports
○ 263 papers in training set
Top 3%
1.8%
12
JCI Insight
● 277 papers in training set
Top 4%
1.7%
13
Stem Cell Research
○ 16 papers in training set
Top 0.2%
1.4%
14
Science Advances
● 1243 papers in training set
Top 24%
1.1%
15
Genes
○ 144 papers in training set
Top 2%
1.1%
16
Biology Open
● 156 papers in training set
Top 3%
1.1%
17
Science Translational Medicine
● 127 papers in training set
Top 3%
1.1%
18
Neurobiology of Disease
○ 148 papers in training set
Top 3%
1.1%
19
Stem Cell Research & Therapy
○ 30 papers in training set
Top 0.6%
1.1%
20
Cells
○ 249 papers in training set
Top 6%
1.0%
21
iScience
○ 1154 papers in training set
Top 31%
1.0%
22
Aging
○ 75 papers in training set
Top 2%
0.9%
23
Biochemical and Biophysical Research Communications
○ 84 papers in training set
Top 2%
0.9%
24
Cell
○ 431 papers in training set
Top 10%
0.9%
25
Human Molecular Genetics
◐ 141 papers in training set
Top 3%
0.9%
26
eneuro
● 439 papers in training set
Top 7%
0.9%
27
Frontiers in Cell and Developmental Biology
○ 233 papers in training set
Top 5%
0.9%
28
Human Mutation
○ 34 papers in training set
Top 0.5%
0.9%
29
Alzheimer's & Dementia
177 papers in training set
Top 2%
0.7%
30
International Journal of Biological Sciences
● 10 papers in training set
Top 0.2%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.