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DOI: 10.24075/brsmu.2023.001

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The approach to patient clustering based on the microchip data confined to distinct loci using the combinations of variants

Iulmetova LN, Kulemin NA, Sharova EI
About authors

Lopukhin Federal Research and Clinical Center of Physical-Chemical Medicine of the Federal Medical Biological Agency, Moscow, Russia

Correspondence should be addressed: Elena I. Sharova
Malaya Pirogovskaya, 1 str. 3, Moscow, 119435, Russia; moc.liamg@87avorahs

About paper

Funding: the study was supported by the President of the Russian Federation (grant for young postdocs МК-2951.2022.1.4)

Acknowledgements: the authors thank dbGaP for providing access to the phs000421.v1.p1 and phs000001.v3.p1 datasets. The dataset with the dbGaP registration number phs000421.v1.p1 was obtained from the genetic study of Fuchs' endothelial corneal dystrophy (FECD) available from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000421.v1.p1. The authors recognize the grants that have been used to support registration of cases and controls and would be used in this GWAS: R01EY016514 (DUEC, PI: Gordon Klintworth), R01EY016482 (CWRU, PI: Sudha Iyengar) and 1X01HG006619-01 (PI: Sudha Iyengar, Natalie Afshari). The authors express their gratitude to the FECD study participants and the FECD research team for their valuable contribution to this study. The dataset with the dbGaP registration number phs000001.v3.p1 was obtained from the Age-Related Eye Disease Study (AREDS) database available from https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000001.v3.p1. AREDS was funded by the National Eye Institute (N01-EY-0-2127). The authors thank the AREDS participants and research team for their valuable contribution to this study. The authors express their gratitude to L.O. Skorodumova, research fellow at the Lopukhin Federal Research and Clinical Center of Physical-Chemical Medicine, for valuable suggestions, comments, and support.

Author contribution: Sharova EI — concept and selection of data; Sharova EI, Iulmetova LN — planning and selection of methods; Kulemin NA — project funding and management; Iulmetova LN — design and computation; Sharova EI, Iulmetova LN, Kulemin NA — discussion, manuscript writing and editing.

Compliance with ethical standards: the study was performed according to the principles of the Declaration of Helsinki using the data of the phs000421.v1.p1 and phs000001.v3.p1 projects, the access to which was approved and provided by dbGaP in accordance with the policy of approval and access to specific datasets.

Received: 2022-12-12 Accepted: 2023-01-20 Published online: 2023-02-12
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  1. Uffelmann E, Huang QQ, Munung NS, De Vries J, Okada Y, Martin AR, et al. Genome-wide association studies. Nature Reviews Methods Primers. 2021; 1 (1): 59. Available from: https://doi.org/10.1038/ s43586-021-00056-9.
  2. Lewis CM, Vassos E. Polygenic risk scores: from research tools to clinical instruments. Genome medicine. 2020; 12 (1): 1–1. Available from: https://doi.org/10.1186/s13073-020-00742-5.
  3. Stram DO. Multi-SNP haplotype analysis methods for association analysis. Statistical Human Genetics: Methods and Protocols. 2017: 485–504. Available from: https://doi.org/10.1007/978-14939-7274–6_24.
  4. Twesigomwe D, Wright GE, Drögemöller BI, da Rocha J, Lombard Z, Hazelhurst S. A systematic comparison of pharmacogene star allele calling bioinformatics algorithms: a focus on CYP2D6 genotyping. NPJ genomic medicine. 2020; 5 (1): 30. Available from: https://doi.org/10.1038/s41525-020-0135-2.
  5. Van Rheenen W, Van Der Spek RA, Bakker MK, Van Vugt JJ, Hop PJ, Zwamborn RA, et al. Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology. Nature genetics. 2021; 53 (12): 1636–48.
  6. Lee JM, Wheeler VC, Chao MJ, Vonsattel JP, Pinto RM, Lucente D, et al. Identification of genetic factors that modify clinical onset of Huntington’s disease. Cell. 2015; 162 (3): 516–26.
  7. Fautsch MP, Wieben ED, Baratz KH, Bhattacharyya N, Sadan AN, Hafford-Tear NJ. et al. TCF4-mediated Fuchs endothelial corneal dystrophy: Insights into a common trinucleotide repeat-associated disease. Progress in retinal and eye research. 2021; 81: 100883.
  8. Biswas S, Munier FL, Yardley J, Hart-Holden N, Perveen R, Cousin P. et al. Missense mutations in COL8A2, the gene encoding the α2 chain of type VIII collagen, cause two forms of corneal endothelial dystrophy. Human molecular genetics. 2001; 10 (21): 2415–23.
  9. Wieben ED, Aleff RA, Tosakulwong N, Butz ML, Highsmith WE, Edwards AO, et al. A common trinucleotide repeat expansion within the transcription factor 4 (TCF4, E2-2) gene predicts Fuchs corneal dystrophy. PLoS One. 2012; 7 (11): e49083.
  10. Afshari NA, Igo Jr RP, Morris NJ, Stambolian D, Sharma S, Pulagam VL, et al. Genome-wide association study identifies three novel loci in Fuchs endothelial corneal dystrophy. Nature communications. 2017; 8 (1): 14898.
  11. Chung DW, Frausto RF, Ann LB, Jang MS, Aldave AJ. Functional impact of ZEB1 mutations associated with posterior polymorphous and Fuchs' endothelial corneal dystrophies. Investigative Ophthalmology & Visual Science. 2014; 55 (10): 6159–66.
  12. Chaurasia S, Ramappa M, Annapurna M, Kannabiran C. Coexistence of congenital hereditary endothelial dystrophy and Fuchs endothelial corneal dystrophy associated with SLC4A11 mutations in affected families. Cornea. 2020; 39 (3): 354–7.
  13. Riazuddin SA, Vasanth S, Katsanis N, Gottsch JD. Mutations in AGBL1 cause dominant late-onset Fuchs corneal dystrophy and alter protein-protein interaction with TCF4. The American Journal of Human Genetics. 2013; 93 (4): 758–64.
  14. Riazuddin SA, Parker DS, McGlumphy EJ, Oh EC, Iliff BW, Schmedt T, et al. Mutations in LOXHD1, a recessive-deafness locus, cause dominant late-onset Fuchs corneal dystrophy. The American Journal of Human Genetics. 2012; 90 (3): 533–9.
  15. Skorodumova LO, Belodedova AV, Antonova OP, Sharova EI, Akopian TA, Selezneva OV, et al. CTG18. 1 expansion is the best classifier of late-onset Fuchs' corneal dystrophy among 10 biomarkers in a cohort from the European part of Russia. Investigative Ophthalmology & Visual Science. 2018; 59 (11): 4748–54.
  16. Louttit MD, Kopplin LJ, Igo Jr RP, Fondran JR, Tagliaferri A, Bardenstein D, et al. A multi-center study to map genes for Fuchs’ endothelial corneal dystrophy: baseline characteristics and heritability. Cornea. 2012; 31 (1): 26.
  17. Age-Related Eye Disease Study Research Group. The agerelated eye disease study (AREDS): design implications AREDS report no. 1. Controlled clinical trials. 1999; 20 (6): 573.
  18. Stambolian D, Wojciechowski R, Oexle K, Pirastu M, Li X, Raffel LJ, et al. Meta-analysis of genome-wide association studies in five cohorts reveals common variants in RBFOX1, a regulator of tissue-specific splicing, associated with refractive error. Human molecular genetics. 2013; 22 (13): 2754–64.
  19. Krachmer JH, Purcell JJ Jr, Young CW, Bucher KD. Corneal endothelial dystrophy. A study of 64 families. Arch Ophthalmol. 1978; 96 (11): 2036–9. DOI: 10.1001/ archopht.1978.03910060424004.
  20. Chang CC, Chow CC, Tellier LC, Vattikuti S, Purcell SM, Lee JJ. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience. 2015; 4: 7. DOI: 10.1186/s13742015-0047-8.
  21. Jin Y, Schäffer AA, Sherry ST, Feolo M. Quickly identifying identical and closely related subjects in large databases using genotype data. PLoS One. 2017; 12 (6): e0179106. DOI: 10.1371/journal. pone.0179106.
  22. Jin Y, Schaffer AA, Feolo M, Holmes JB, Kattman BL. GRAFpop: A Fast Distance-Based Method To Infer Subject Ancestry from Multiple Genotype Datasets Without Principal Components Analysis. G3 (Bethesda). 2019; 9 (8): 2447–61. DOI: 10.1534/ g3.118.200925.
  23. Okumura N, Hayashi R, Nakano M, Tashiro K, Yoshii K, Aleff R. et al. Association of rs613872 and Trinucleotide Repeat Expansion in the TCF4 Gene of German Patients With Fuchs Endothelial Corneal Dystrophy. Cornea. 2019; 38 (7): 799–805. DOI: 10.1097/ ICO.0000000000001952.
  24. Viberg A, Westin IM, Golovleva I, Byström B. TCF4 trinucleotide repeat expansion in Swedish cases with Fuchs' endothelial corneal dystrophy. Acta Ophthalmol. 2022; 100 (5): 541–8. DOI: 10.1111/aos.15032. Epub 2021 Oct 13.
  25. Foja S, Luther M, Hoffmann K, Rupprecht A, GruenauerKloevekorn C. CTG18.1 repeat expansion may reduce TCF4 gene expression in corneal endothelial cells of German patients with Fuchs' dystrophy. Graefes Arch Clin Exp Ophthalmol. 2017; 255 (8): 1621–31. DOI: 10.1007/s00417-017-3697-7. Epub 2017 Jun 12.
  26. Kuot A, Hewitt AW, Snibson GR, Souzeau E, Mills R, Craig JE, et al. TGC repeat expansion in the TCF4 gene increases the risk of Fuchs' endothelial corneal dystrophy in Australian cases. PLoS One. 2017; 12 (8): e0183719. DOI: 10.1371/journal. pone.0183719.
  27. Klein RJ, Zeiss C, Chew EY, Tsai JY, Sackler RS, Haynes C, et al. Complement factor H polymorphism in age-related macular degeneration. Science. 2005; 308 (5720): 385–9. DOI: 10.1126/ science.1109557. Epub 2005 Mar 10.
  28. Spencer KL, Hauser MA, Olson LM, Schmidt S, Scott WK, Gallins P, et al. Deletion of CFHR3 and CFHR1 genes in age-related macular degeneration. Hum Mol Genet. 2008; 17 (7): 971–7. DOI: 10.1093/hmg/ddm369. Epub 2007 Dec 15.
  29. Baratz KH, Tosakulwong N, Ryu E, Brown WL, Branham K, Chen W, et al. E2-2 protein and Fuchs's corneal dystrophy. N Engl J Med. 2010; 363 (11): 1016–24. DOI: 10.1056/NEJMoa1007064. Epub 2010 Aug 25.