Novel Polygenic Risk Score for Intracranial Aneurysms.

HomeStrokeVol. 54, No. 3Novel Polygenic Risk Score for Intracranial Aneurysms Free AccessEditorialPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessEditorialPDF/EPUBNovel Polygenic Risk Score for Intracranial Aneurysms Simon Frerich and John W. Cole Simon FrerichSimon Frerich Correspondence to: Simon Frerich, MSc, Institute for Stroke and Dementia Research, University Hospital, Ludwig Maximilian University (LMU) of Munich, Feodor-Lynen-Str. 17, 81377 Munich, Germany. Email E-mail Address: [email protected] https://orcid.org/0000-0002-8275-6113 Institute for Stroke and Dementia Research, University Hospital (S.F.), LMU Munich, Germany. Graduate School of Systemic Neurosciences (GSN) (S.F.), LMU Munich, Germany. Search for more papers by this author and John W. ColeJohn W. Cole https://orcid.org/0000-0001-9263-8930 Department of Neurology, Maryland Stroke Center, Baltimore (J.W.C.). Baltimore VA Medical Center and University of Maryland School of Medicine (J.W.C.). Search for more papers by this author Originally published19 Jan 2023https://doi.org/10.1161/STROKEAHA.122.041807Stroke. 2023;54:819–820This article is a commentary on the followingGenetic Risk Score for Intracranial Aneurysms: Prediction of Subarachnoid Hemorrhage and Role in Clinical HeterogeneityOther version(s) of this articleYou are viewing the most recent version of this article. Previous versions: January 19, 2023: Ahead of Print Since the completion of the first genome-wide association studies in the early 2000s, polygenic risk prediction has raised considerable expectations for research and clinical use.1 Despite methodological concerns about construction and validity of polygenic risk scores (PRS),2 multiple studies have shown that PRS strongly associate with disease status,3 and the number of studies related to PRS is increasing exponentially (based on a PubMed search for the terms: “polygenic risk score*” OR “genetic risk score*” OR “genetic score*” OR “polygenic score*,” as of 23/11/2022). Most commonly, polygenic risk scores, also known as genetic risk scores (GRS), represent a defined set of risk variants based on findings from genome-wide association studies. For each individual, the number of risk alleles is summed and weighted by its effect size.3 Therefore, PRS can discriminate individuals based on their genetic susceptibility to a particular trait or disease.See related article, p 810Much of the evidence supporting the clinical utility of PRS comes from well-powered studies of cardiovascular diseases, type 2 diabetes, cancer, and Alzheimer disease.3 Conversely, previous PRS studies on intracranial aneurysms (IAs) are small and scarce.4 Whereas the first PRS study on IA could not find an association between a PRS and aneurysm size,5 follow-up work showed that the PRS is higher in individuals with IAs located at the middle cerebral artery as compared with all other locations.6 Another study found that an improved PRS associated with aneurysm diameter and volume but not with aneurysm presence.7 Notably, the cited studies were based on no more than 10 genetic variants, which amounted to a SNP-based heritability of approximately 4%.5,6 In addition, associations with IA outcomes were evaluated in small cohorts of fewer than 2000 cases.5–7 The statistical power of these studies to detect meaningful associations was therefore limited.In this issue of Stroke, Bakker et al8 address this gap by creating a novel genetic risk score of IA. The authors leverage a recent genome-wide association study of IA and aneurysmal subarachnoid hemorrhage (ASAH)9 along with association data of 17 IA-related traits, to create a “meta Genetic Risk Score” (metaGRS). Among the 17 selected traits are established IA risk factors, such as blood pressure and smoking, and diseases genetically correlated with IA, including ischemic stroke.8 To construct the score, the authors utilized an “elastic net regression” methodology in a training sample from the UK Biobank (1161 IA cases, 407 392 controls). In this way, a total of 7 078 955 SNPs were included in the score. First, the authors evaluated associations of the metaGRS with ASAH incidence and IA presence in the HUNT study (828 IA cases, 68 568 controls). While the score improved ASAH incidence prediction above a model including clinical risk factors sex, blood pressure, and smoking (C-index 0.63 to 0.65), the prediction of IA presence did not increase after including the score. The authors also showed that the prediction of ASAH incidence was stronger in women than in men by using scores trained and validated in women and men separately. Next, a higher score independently associated with 3 out of 9 tested IA patient characteristics in the ISGC-IA cohort (5560 IA cases), namely hypertension, smoking status, and lower age at ASAH. In addition, a lower metaGRS was observed in patients with a single IA compared to multiple IAs, and in patients with an IA at the internal carotid artery. The latter 2 associations, however, were not independent of smoking and hypertension in a multivariate model.The predictive value of the metaGRS remains limited, given that it did not improve prediction of IA presence above a model including clinical risk factors. One reason for this could be the presence of undetected and unruptured IAs in the control group, as suggested by the authors,8 which would attenuate the statistical power to predict IAs. Only an improved characterization of the controls via brain vessel imaging (eg, MRA, CTA) can resolve this issue. Furthermore, a previously shown association with IAs located at the middle cerebral artery6 could not be replicated. Conversely, a decreased genetic load in patients with an IA at the internal carotid artery was identified, a location that was not included in the previous study. Last, the PRS is based on individuals of European ancestry, resulting in reduced predictive accuracy in other populations.3Despite these limitations, the novel PRS by Bakker et al8 is a major improvement over previous scores. The statistical power is considerably larger, as the utilized genome-wide association study more than doubled the number of cases compared to previous studies (7495 IA/ASAH cases, 71 934 controls).9 SNP-based heritability increased to 21.6%, thereby explaining more than half of the twin-based heritability of IA (h2=41%).9 More than 7000 IA cases were used for creating and evaluating the metaGRS.9 Further, the authors used 3 different cohorts to train and validate their score (UK Biobank, HUNT, ISGC-IA).In closing, the investigators constructed a metaGRS with predictive ability for ASAH, although with limited added value over standard clinical risk factors. This finding emphasizes the need for patient-specific vascular risk factor control in the setting of IA, specifically optimizing blood pressure and smoking cessation. However, their findings that prediction by the metaGRS for ASAH performed better in women than in men, and in subjects at a younger age, independent of both hypertension and smoking, further highlights that genetic drivers also play a key role. While these results do not indicate that regular use of the metaGRS is clinically warranted, they certainly highlight that both genetic and environmental factors jointly contribute to disease risk and that additional research in needed to further clarify these relationships.Article InformationAcknowledgmentsS. Frerich and Dr Cole drafted and revised the article, and analyzed and interpreted the data.Disclosures Dr Cole receives royalty payments from Springer; and is partially supported by an American Heart Association (AHA)-Bayer Discovery Grant (Grant 17IBDG33700328), the AHA Cardiovascular Genome-Phenome Study (Grant-15GPSPG23770000), NIH (Grants: R01-NS114045; R01-NS100178; R01-NS105150), and the US Department of Veterans Affairs.FootnotesThe opinions expressed in this article are not necessarily those of the editors or of the American Heart Association.For Disclosures, see page 820.Correspondence to: Simon Frerich, MSc, Institute for Stroke and Dementia Research, University Hospital, Ludwig Maximilian University (LMU) of Munich, Feodor-Lynen-Str. 17, 81377 Munich, Germany. Email simon.frerich@med.uni-muenchen.deReferences1. Bell J. Predicting disease using genomics.Nature. 2004; 429:453–456. doi: 10.1038/nature02624CrossrefGoogle Scholar2. Janssens ACJ. Validity of polygenic risk scores: are we measuring what we think we are?Hum Mol Genet. 2019; 28:R143–R150. doi: 10.1093/hmg/ddz205CrossrefMedlineGoogle Scholar3. Lewis CM, Vassos E. Polygenic risk scores: from research tools to clinical instruments.Genome Med. 2020; 12:44. doi: 10.1186/s13073-020-00742-5CrossrefMedlineGoogle Scholar4. Bakker MK, Ruigrok YM. Genetics of intracranial aneurysms.Stroke. 2021; 52:3004–3012. doi: 10.1161/strokeaha.120.032621LinkGoogle Scholar5. Kleinloog R, van ’t Hof FNG, Wolters FJ, Rasing I, van der Schaaf IC, Rinkel GJE, Ruigrok YM. The association between genetic risk factors and the size of intracranial aneurysms at time of rupture.Neurosurgery. 2013; 73:705–708. doi: 10.1227/NEU.0000000000000078CrossrefMedlineGoogle Scholar6. van ’t Hof FNG, Kurki MI, Kleinloog R, de Bakker PIW, von und zu Fraunberg M, Jaaskelainen JE, Gaal EI, Lehto H, Kivisaari R, Laakso A, et al. Genetic risk load according to the site of intracranial aneurysms.Neurology. 2014; 83:34–39. doi: 10.1212/wnl.0000000000000547CrossrefMedlineGoogle Scholar7. Peymani A, Adams HHH, Cremers LGM, Krestin G, Hofman A, van Duijn CM, Uitterlinden AG, van der Lugt A, Vernooij MW, Ikram MA. Genetic determinants of unruptured intracranial aneurysms in the general population.Stroke. 2015; 46:2961–2964. doi: 10.1161/STROKEAHA.115.010414LinkGoogle Scholar8. Bakker MK, Kanning JP, Abraham G, Martinsen AE, Winsvold BS, Zwart J-A, Bourcier R, Sawada T, Koido M, Kamatani Y, et al. Genetic risk score for intracranial aneurysms: prediction of subarachnoid hemorrhage and role in clinical heterogeneity.Stroke. 2023; 54:810–818. doi: 10.1161/STROKEAHA.122.040715LinkGoogle Scholar9. Bakker MK, van der Spek RAA, van Rheenen W, Morel S, Bourcier R, Hostettler IC, Alg VS, van Eijk KR, Koido M, Akiyama M, et al. Genome-wide association study of intracranial aneurysms identifies 17 risk loci and genetic overlap with clinical risk factors.Nat Genet. 2020; 52:1303–1313. doi: 10.1038/s41588-020-00725-7CrossrefMedlineGoogle Scholar eLetters(0)eLetters should relate to an article recently published in the journal and are not a forum for providing unpublished data. Comments are reviewed for appropriate use of tone and language. Comments are not peer-reviewed. Acceptable comments are posted to the journal website only. Comments are not published in an issue and are not indexed in PubMed. Comments should be no longer than 500 words and will only be posted online. References are limited to 10. Authors of the article cited in the comment will be invited to reply, as appropriate.Comments and feedback on AHA/ASA Scientific Statements and Guidelines should be directed to the AHA/ASA Manuscript Oversight Committee via its Correspondence page.Sign In to Submit a Response to This Article Previous Back to top Next FiguresReferencesRelatedDetailsRelated articlesGenetic Risk Score for Intracranial Aneurysms: Prediction of Subarachnoid Hemorrhage and Role in Clinical HeterogeneityMark K. Bakker, et al. Stroke. 2023;54:810-818 March 2023Vol 54, Issue 3 Advertisement Article InformationMetrics © 2023 American Heart Association, Inc.https://doi.org/10.1161/STROKEAHA.122.041807PMID: 36655556 Originally publishedJanuary 19, 2023 Keywordsintracranial aneurysmsEditorialsPDF download Advertisement SubjectsGenetic, Association StudiesGeneticsIntracranial HemorrhagePrecision Medicine