{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T16:33:03Z","timestamp":1792859583256,"version":"4.5.0"},"reference-count":54,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,4,3]],"date-time":"2025-04-03T00:00:00Z","timestamp":1743638400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,4,3]],"date-time":"2025-04-03T00:00:00Z","timestamp":1743638400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100020884","name":"Agencia Nacional de Investigaci\u00f3n y Desarrollo","doi-asserted-by":"publisher","award":["FONDECYT 1221464"],"award-info":[{"award-number":["FONDECYT 1221464"]}],"id":[{"id":"10.13039\/501100020884","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100020884","name":"Agencia Nacional de Investigaci\u00f3n y Desarrollo","doi-asserted-by":"publisher","award":["Beca Doctorado Nacional 2020 Folio 21201541"],"award-info":[{"award-number":["Beca Doctorado Nacional 2020 Folio 21201541"]}],"id":[{"id":"10.13039\/501100020884","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["1R01NS112499"],"award-info":[{"award-number":["1R01NS112499"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"DOI":"10.1038\/s41598-025-95755-8","type":"journal-article","created":{"date-parts":[[2025,4,4]],"date-time":"2025-04-04T21:04:13Z","timestamp":1743800653000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Polygenic score analysis identifies distinct genetic risk profiles in Alzheimer\u2019s disease comorbidities"],"prefix":"10.1038","volume":"15","author":[{"given":"Carlos F.","family":"Hern\u00e1ndez","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Camilo","family":"Villaman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Costin","family":"Leu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dennis","family":"Lal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ignacio","family":"Mata","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andr\u00e9s D.","family":"Klein","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eduardo","family":"P\u00e9rez-Palma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,4,3]]},"reference":[{"key":"95755_CR1","doi-asserted-by":"publisher","first-page":"e0177044","DOI":"10.1371\/journal.pone.0177044","volume":"12","author":"ML Haaksma","year":"2017","unstructured":"Haaksma, M. L. et al. Comorbidity and progression of late onset Alzheimer\u2019s disease: A systematic review. PLoS One  12, e0177044 (2017).","journal-title":"PLoS One"},{"key":"95755_CR2","doi-asserted-by":"publisher","first-page":"631770","DOI":"10.3389\/fnagi.2021.631770","volume":"13","author":"JA Santiago","year":"2021","unstructured":"Santiago, J. A. & Potashkin, J. A. The impact of disease comorbidities in Alzheimer\u2019s disease. Front. Aging Neurosci. 13, 631770 (2021).","journal-title":"Front. Aging Neurosci."},{"key":"95755_CR3","doi-asserted-by":"publisher","first-page":"865","DOI":"10.3233\/JAD-191315","volume":"74","author":"D Arnaldi","year":"2020","unstructured":"Arnaldi, D. et al. Epilepsy in neurodegenerative dementias: A clinical, epidemiological, and EEG study. JAD 74, 865\u2013874 (2020).","journal-title":"JAD"},{"key":"95755_CR4","doi-asserted-by":"publisher","first-page":"4360","DOI":"10.3390\/jcm10194360","volume":"10","author":"I Avitan","year":"2021","unstructured":"Avitan, I. et al. Towards a consensus on Alzheimer\u2019s disease comorbidity? J. Clin. Med. 10, 4360 (2021).","journal-title":"J. Clin. Med."},{"key":"95755_CR5","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1038\/s41582-024-00932-4","volume":"20","author":"A Kamondi","year":"2024","unstructured":"Kamondi, A., Grigg-Damberger, M., L\u00f6scher, W., Tanila, H. & Horvath, A. A. Epilepsy and epileptiform activity in late-onset alzheimer disease: clinical and pathophysiological advances, gaps and conundrums. Nat. Rev. Neurol. 20, 162\u2013182 (2024).","journal-title":"Nat. Rev. Neurol."},{"key":"95755_CR6","doi-asserted-by":"publisher","first-page":"1196185","DOI":"10.3389\/fnagi.2023.1196185","volume":"15","author":"J Kim","year":"2023","unstructured":"Kim, J., Ha, W. S., Park, S. H., Han, K. & Baek, M. S. Association between migraine and Alzheimer\u2019s disease: a nationwide cohort study. Front. Aging Neurosci. 15, 1196185 (2023).","journal-title":"Front. Aging Neurosci."},{"key":"95755_CR7","doi-asserted-by":"publisher","first-page":"1565","DOI":"10.1007\/s43440-021-00293-5","volume":"73","author":"K Maciejewska","year":"2021","unstructured":"Maciejewska, K., Czarnecka, K. & Szyma\u0144ski, P. A review of the mechanisms underlying selected comorbidities in Alzheimer\u2019s disease. Pharmacol. Rep. 73, 1565\u20131581 (2021).","journal-title":"Pharmacol. Rep."},{"key":"95755_CR8","doi-asserted-by":"publisher","first-page":"474","DOI":"10.2337\/diabetes.53.2.474","volume":"53","author":"J Janson","year":"2004","unstructured":"Janson, J. et al. Increased risk of type 2 diabetes in alzheimer disease. Diabetes 53, 474\u2013481 (2004).","journal-title":"Diabetes"},{"key":"95755_CR9","doi-asserted-by":"publisher","first-page":"505","DOI":"10.1016\/j.biopsych.2009.02.013","volume":"67","author":"LA Profenno","year":"2010","unstructured":"Profenno, L. A., Porsteinsson, A. P. & Faraone, S. V. Meta-analysis of Alzheimer\u2019s disease risk with obesity, diabetes, and related disorders. Biol. Psychiatr.  67, 505\u2013512 (2010).","journal-title":"Biol. Psychiatry"},{"key":"95755_CR10","doi-asserted-by":"publisher","first-page":"3573","DOI":"10.18632\/aging.202299","volume":"13","author":"ZR Tsai","year":"2021","unstructured":"Tsai, Z. R. et al. Late-onset epilepsy and subsequent increased risk of dementia. Aging (Albany NY) 13, 3573\u20133587 (2021).","journal-title":"Aging (Albany NY)"},{"key":"95755_CR11","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1093\/brain\/awz381","volume":"143","author":"S Gourmaud","year":"2020","unstructured":"Gourmaud, S. et al. Alzheimer-like amyloid and Tau alterations associated with cognitive deficit in Temporal lobe epilepsy. Brain 143, 191\u2013209 (2020).","journal-title":"Brain"},{"key":"95755_CR12","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1038\/s41593-018-0326-7","volume":"22","author":"DM Howard","year":"2019","unstructured":"Howard, D. M. et al. Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nat. Neurosci. 22, 343\u2013352 (2019).","journal-title":"Nat. Neurosci."},{"key":"95755_CR13","doi-asserted-by":"publisher","first-page":"1843","DOI":"10.1038\/s41588-023-01538-0","volume":"55","author":"G Bjornsdottir","year":"2023","unstructured":"Bjornsdottir, G. et al. Rare variants with large effects provide functional insights into the pathology of migraine subtypes, with and without aura. Nat. Genet. 55, 1843\u20131853 (2023).","journal-title":"Nat. Genet."},{"key":"95755_CR14","doi-asserted-by":"publisher","first-page":"e0203896","DOI":"10.1371\/journal.pone.0203896","volume":"13","author":"J Ward","year":"2018","unstructured":"Ward, J. et al. Polygenic risk scores for major depressive disorder and neuroticism as predictors of antidepressant response: Meta-analysis of three treatment cohorts. PLoS One  13, e0203896 (2018).","journal-title":"PLoS One"},{"key":"95755_CR15","doi-asserted-by":"crossref","unstructured":"Andrews, S. J. et al. The complex genetic architecture of Alzheimer\u2019s disease: novel insights and future directions. eBioMedicine 90, (2023).","DOI":"10.1016\/j.ebiom.2023.104511"},{"key":"95755_CR16","doi-asserted-by":"publisher","first-page":"bbae140","DOI":"10.1093\/bib\/bbae140","volume":"25","author":"S Gao","year":"2024","unstructured":"Gao, S. et al. Interpretation of 10 years of Alzheimer\u2019s disease genetic findings in the perspective of statistical heterogeneity. Brief. Bioinform.  25, bbae140 (2024).","journal-title":"Brief. Bioinform"},{"key":"95755_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3233\/JAD-220025","volume":"89","author":"K Clark","year":"2022","unstructured":"Clark, K., Leung, Y. Y., Lee, W. P., Voight, B. & Wang, L. S. Polygenic risk scores in Alzheimer\u2019s disease genetics: methodology, applications, inclusion, and diversity. J. Alzheimers Dis. 89, 1\u201312 (2022).","journal-title":"J. Alzheimers Dis."},{"key":"95755_CR18","doi-asserted-by":"publisher","first-page":"1219","DOI":"10.1038\/s41588-018-0183-z","volume":"50","author":"AV Khera","year":"2018","unstructured":"Khera, A. V. et al. Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nat. Genet. 50, 1219\u20131224 (2018).","journal-title":"Nat. Genet."},{"key":"95755_CR19","doi-asserted-by":"publisher","first-page":"14","DOI":"10.3389\/fdgth.2020.00014","volume":"2","author":"E Baker","year":"2020","unstructured":"Baker, E. & Escott-Price, V. Polygenic risk scores in Alzheimer\u2019s disease: current applications and future directions. Front. Digit. Health  2, 14 (2020).","journal-title":"Front. Digit. Health"},{"key":"95755_CR20","doi-asserted-by":"crossref","unstructured":"Hahn, S. J., Kim, S., Choi, Y. S., Lee, J. & Kang, J. Prediction of type 2 diabetes using genome-wide polygenic risk score and metabolic profiles: A machine learning analysis of population-based 10-year prospective cohort study. eBioMedicine 86, (2022).","DOI":"10.1016\/j.ebiom.2022.104383"},{"key":"95755_CR21","doi-asserted-by":"publisher","first-page":"e364","DOI":"10.1212\/NXG.0000000000000364","volume":"5","author":"LJA Kogelman","year":"2019","unstructured":"Kogelman, L. J. A. et al. Migraine polygenic risk score associates with efficacy of migraine-specific drugs. Neurol. Genet. 5, e364 (2019).","journal-title":"Neurol. Genet."},{"key":"95755_CR22","doi-asserted-by":"publisher","first-page":"3473","DOI":"10.1093\/brain\/awz292","volume":"142","author":"C Leu","year":"2019","unstructured":"Leu, C. et al. Polygenic burden in focal and generalized epilepsies. Brain 142, 3473\u20133481 (2019).","journal-title":"Brain"},{"key":"95755_CR23","doi-asserted-by":"publisher","first-page":"704","DOI":"10.1038\/s41586-022-05275-y","volume":"610","author":"L Yengo","year":"2022","unstructured":"Yengo, L. et al. A saturated map of common genetic variants associated with human height. Nature 610, 704\u2013712 (2022).","journal-title":"Nature"},{"key":"95755_CR24","doi-asserted-by":"publisher","first-page":"101e1","DOI":"10.1016\/j.neurobiolaging.2020.09.014","volume":"99","author":"B Fulton-Howard","year":"2021","unstructured":"Fulton-Howard, B. et al. Greater effect of polygenic risk score for Alzheimer\u2019s disease among younger cases who are Apolipoprotein E-\u03b54 carriers. Neurobiol. Aging  99, 101e1\u2013101e9 (2021).","journal-title":"Neurobiol. Aging"},{"key":"95755_CR25","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1177\/1533317518813551","volume":"34","author":"M Asadollahi","year":"2019","unstructured":"Asadollahi, M., Atazadeh, M. & Noroozian, M. Seizure in Alzheimer\u2019s disease: an underestimated phenomenon. Am. J. Alzheimers Dis. Other Demen.  34, 81\u201388 (2019).","journal-title":"Am. J. Alzheimers Dis. Other Demen"},{"key":"95755_CR26","doi-asserted-by":"publisher","first-page":"e2589","DOI":"10.1002\/brb3.2589","volume":"12","author":"P Ioannou","year":"2022","unstructured":"Ioannou, P. et al. The burden of epilepsy and unmet need in people with focal seizures. Brain Behav. 12, e2589 (2022).","journal-title":"Brain Behav."},{"key":"95755_CR27","unstructured":"Purushotham, M. et al. The association between Alzheimer\u2019s disease and epilepsy: A narrative review. Cureus 14, e30195 ."},{"key":"95755_CR28","doi-asserted-by":"publisher","first-page":"922535","DOI":"10.3389\/fneur.2022.922535","volume":"13","author":"D Zhang","year":"2022","unstructured":"Zhang, D. et al. The clinical correlation between Alzheimer\u2019s disease and epilepsy. Front. Neurol. 13, 922535 (2022).","journal-title":"Front. Neurol."},{"key":"95755_CR29","doi-asserted-by":"publisher","first-page":"476","DOI":"10.1007\/s11892-014-0476-2","volume":"14","author":"A Jayaraman","year":"2014","unstructured":"Jayaraman, A. & Pike, C. J. Alzheimer\u2019s disease and type 2 diabetes: multiple mechanisms contribute to interactions. Curr. Diab Rep. 14, 476 (2014).","journal-title":"Curr. Diab Rep."},{"key":"95755_CR30","doi-asserted-by":"publisher","first-page":"889","DOI":"10.4239\/wjd.v5.i6.889","volume":"5","author":"M Barbagallo","year":"2014","unstructured":"Barbagallo, M. & Dominguez, L. J. Type 2 diabetes mellitus and Alzheimer\u2019s disease. World J. Diabetes  5, 889\u2013893 (2014).","journal-title":"World J. Diabetes"},{"issue":"Suppl 1","key":"95755_CR31","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1016\/j.neurobiolaging.2005.09.018","volume":"26","author":"A Convit","year":"2005","unstructured":"Convit, A. Links between cognitive impairment in insulin resistance: an explanatory model. Neurobiol. Aging  26 (Suppl 1), 31\u201335 (2005).","journal-title":"Neurobiol. Aging"},{"key":"95755_CR32","doi-asserted-by":"publisher","first-page":"1604","DOI":"10.1007\/s00125-003-1235-0","volume":"46","author":"T den Heijer","year":"2003","unstructured":"den Heijer, T. et al. Type 2 diabetes and atrophy of medial Temporal lobe structures on brain MRI. Diabetologia 46, 1604\u20131610 (2003).","journal-title":"Diabetologia"},{"key":"95755_CR33","doi-asserted-by":"publisher","first-page":"12366","DOI":"10.3390\/ijms222212366","volume":"22","author":"FC Pignalosa","year":"2021","unstructured":"Pignalosa, F. C. et al. Diabetes and cognitive impairment: A role for glucotoxicity and dopaminergic dysfunction. Int. J. Mol. Sci. 22, 12366 (2021).","journal-title":"Int. J. Mol. Sci."},{"key":"95755_CR34","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1046\/j.1464-5491.1999.00027.x","volume":"16","author":"R Stewart","year":"1999","unstructured":"Stewart, R. & Liolitsa, D. Type 2 diabetes mellitus, cognitive impairment and dementia. Diabet. Med. 16, 93\u2013112 (1999).","journal-title":"Diabet. Med."},{"key":"95755_CR35","doi-asserted-by":"publisher","first-page":"12419","DOI":"10.3390\/ijms222212419","volume":"22","author":"OV Saik","year":"2021","unstructured":"Saik, O. V. & Klimontov, V. V. Hypoglycemia, vascular disease and cognitive dysfunction in diabetes: insights from text mining-based reconstruction and bioinformatics analysis of the gene networks. Int. J. Mol. Sci. 22, 12419 (2021).","journal-title":"Int. J. Mol. Sci."},{"key":"95755_CR36","doi-asserted-by":"publisher","first-page":"1565","DOI":"10.1001\/jama.2009.460","volume":"301","author":"RA Whitmer","year":"2009","unstructured":"Whitmer, R. A., Karter, A. J., Yaffe, K., Quesenberry, C. P. & Selby, J. V. Hypoglycemic episodes and risk of dementia in older patients with type 2 diabetes mellitus. JAMA 301, 1565\u20131572 (2009).","journal-title":"JAMA"},{"key":"95755_CR37","doi-asserted-by":"publisher","first-page":"964463","DOI":"10.3389\/fnagi.2022.964463","volume":"14","author":"J Yang","year":"2022","unstructured":"Yang, J. et al. Prediction value of the genetic risk of type 2 diabetes on the amnestic mild cognitive impairment conversion to Alzheimer\u2019s disease. Front. Aging Neurosci. 14, 964463 (2022).","journal-title":"Front. Aging Neurosci."},{"key":"95755_CR38","doi-asserted-by":"publisher","first-page":"962","DOI":"10.1016\/S1474-4422(22)00395-7","volume":"21","author":"J Hardy","year":"2022","unstructured":"Hardy, J. & De Strooper, B. Escott-Price, V. Diabetes and Alzheimer\u2019s disease: shared genetic susceptibility? Lancet Neurol. 21, 962\u2013964 (2022).","journal-title":"Lancet Neurol."},{"key":"95755_CR39","doi-asserted-by":"publisher","first-page":"2544","DOI":"10.2337\/dc22-0105","volume":"45","author":"EM Litkowski","year":"2022","unstructured":"Litkowski, E. M. et al. A diabetes genetic risk score is associated with all-cause dementia and clinically diagnosed vascular dementia in the million veteran program. Diabetes Care  45, 2544\u20132552 (2022).","journal-title":"Diabetes Care"},{"key":"95755_CR40","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1038\/s41588-021-00997-7","volume":"54","author":"P Wainschtein","year":"2022","unstructured":"Wainschtein, P. et al. Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data. Nat. Genet. 54, 263\u2013273 (2022).","journal-title":"Nat. Genet."},{"key":"95755_CR41","doi-asserted-by":"publisher","first-page":"522","DOI":"10.1016\/j.ajhg.2018.08.016","volume":"103","author":"MH Guo","year":"2018","unstructured":"Guo, M. H., Plummer, L., Chan, Y. M., Hirschhorn, J. N. & Lippincott, M. F. Burden testing of rare variants identified through exome sequencing via publicly available control data. Am. J. Hum. Genet. 103, 522\u2013534 (2018).","journal-title":"Am. J. Hum. Genet."},{"key":"95755_CR42","doi-asserted-by":"publisher","first-page":"5852","DOI":"10.1038\/s41467-021-26114-0","volume":"12","author":"R Lali","year":"2021","unstructured":"Lali, R. et al. Calibrated rare variant genetic risk scores for complex disease prediction using large exome sequence repositories. Nat. Commun. 12, 5852 (2021).","journal-title":"Nat. Commun."},{"key":"95755_CR43","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1038\/s41586-018-0579-z","volume":"562","author":"C Bycroft","year":"2018","unstructured":"Bycroft, C. et al. The UK biobank resource with deep phenotyping and genomic data. Nature 562, 203\u2013209 (2018).","journal-title":"Nature"},{"key":"95755_CR44","unstructured":"World Health Organization. ICD-10 : international statistical classification of diseases and related health problems : tenth revision.  https:\/\/apps.who.int\/iris\/handle\/10665\/42980 (2004)."},{"key":"95755_CR45","doi-asserted-by":"publisher","first-page":"290","DOI":"10.1038\/s41586-021-03205-y","volume":"590","author":"NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium","year":"2021","unstructured":"NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium. Sequencing of 53,831 diverse genomes from the NHLBI topmed program. Nature 590, 290\u2013299 (2021).","journal-title":"Nature"},{"key":"95755_CR46","doi-asserted-by":"publisher","first-page":"560","DOI":"10.1038\/s41588-022-01058-3","volume":"54","author":"A Mahajan","year":"2022","unstructured":"Mahajan, A. et al. Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation. Nat. Genet. 54, 560\u2013572 (2022).","journal-title":"Nat. Genet."},{"key":"95755_CR47","unstructured":"Gormley, P. et al. Meta-analysis of 375,000 individuals identifies 38 susceptibility loci for migraine. Nat. Genet. 48, (2016)."},{"key":"95755_CR48","doi-asserted-by":"publisher","first-page":"1471","DOI":"10.1038\/s41588-023-01485-w","volume":"55","author":"R Stevelink","year":"2023","unstructured":"Stevelink, R. et al. GWAS meta-analysis of over 29,000 people with epilepsy identifies 26 risk loci and subtype-specific genetic architecture. Nat. Genet. 55, 1471\u20131482 (2023).","journal-title":"Nat. Genet."},{"key":"95755_CR49","doi-asserted-by":"publisher","first-page":"668","DOI":"10.1038\/s41588-018-0090-3","volume":"50","author":"NR Wray","year":"2018","unstructured":"Wray, N. R. et al. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat. Genet. 50, 668\u2013681 (2018).","journal-title":"Nat. Genet."},{"key":"95755_CR50","doi-asserted-by":"publisher","first-page":"2190","DOI":"10.1093\/bioinformatics\/btq340","volume":"26","author":"CJ Willer","year":"2010","unstructured":"Willer, C. J., Li, Y. & Abecasis, G. R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190\u20132191 (2010).","journal-title":"Bioinformatics"},{"key":"95755_CR51","doi-asserted-by":"publisher","first-page":"4521","DOI":"10.1093\/bioinformatics\/btaa570","volume":"36","author":"IM Nolte","year":"2020","unstructured":"Nolte, I. M. Metasubtract: an R-package to analytically produce leave\u2010one\u2010out meta\u2010analysis GWAS summary statistics. Bioinformatics 36, 4521\u20134522 (2020).","journal-title":"Bioinformatics"},{"key":"95755_CR52","doi-asserted-by":"publisher","unstructured":"Thompson, D. J. et al. UK biobank release and systematic evaluation of optimised polygenic risk scores for 53 diseases and quantitative traits.  https:\/\/doi.org\/10.1101\/2022.06.16.22276246 (2022).","DOI":"10.1101\/2022.06.16.22276246"},{"key":"95755_CR53","unstructured":"R Core Team. R: A Language and Environment for Statistical Computing.  https:\/\/www.R-project.org\/ (2022)."},{"key":"95755_CR54","doi-asserted-by":"publisher","unstructured":"Wickham, H. Ggplot2  https:\/\/doi.org\/10.1007\/978-3-319-24277-4 (Springer International Publishing, 2016).","DOI":"10.1007\/978-3-319-24277-4"}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-95755-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-95755-8","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-95755-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,5]],"date-time":"2025-04-05T04:52:07Z","timestamp":1743828727000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-95755-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,3]]},"references-count":54,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["95755"],"URL":"https:\/\/doi.org\/10.1038\/s41598-025-95755-8","relation":{},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4,3]]},"assertion":[{"value":"20 November 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 March 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 April 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"11407"}}