Faculty Opinions recommendation of Polygenic risk for depression increases risk of ischemic stroke: from the stroke genetics network study.

Abstract Background MRI-derived cortical folding measures are an indicator of largely genetically driven early developmental processes. However, the effects of genetic risk for major mental disorders on early brain development are not well understood. Methods We extracted cortical complexity values from structural MRI data of 580 healthy participants using the CAT12 toolbox. Polygenic risk scores (PRS) for schizophrenia, bipolar disorder, major depression, and cross-disorder (incorporating cumulative genetic risk for depression, schizophrenia, bipolar disorder, autism spectrum disorder, and attention-deficit hyperactivity disorder) were computed and used in separate general linear models with cortical complexity as the regressand. In brain regions that showed a significant association between polygenic risk for mental disorders and cortical complexity, volume of interest (VOI)/region of interest (ROI) analyses were conducted to investigate additional changes in their volume and cortical thickness. Results The PRS for depression was associated with cortical complexity in the right orbitofrontal cortex (right hemisphere: p = 0.006). A subsequent VOI/ROI analysis showed no association between polygenic risk for depression and either grey matter volume or cortical thickness. We found no associations between cortical complexity and polygenic risk for either schizophrenia, bipolar disorder or psychiatric cross-disorder when correcting for multiple testing. Conclusions Changes in cortical complexity associated with polygenic risk for depression might facilitate well-established volume changes in orbitofrontal cortices in depression. Despite the absence of psychopathology, changed cortical complexity that parallels polygenic risk for depression might also change reward systems, which are also structurally affected in patients with depressive syndrome.

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PREDICTIVE PERFORMANCE OF A POLYGENIC RISK SCORE FOR INCIDENT ISCHEMIC STROKE IN A HEALTHY OLDER POPULATION

Journal of the American College of Cardiology ◽

10.1016/s0735-1097(21)02829-1 ◽

2021 ◽

Vol 77 (18) ◽

pp. 1471

Author(s):

Johannes Neumann ◽

Moeen Riaz ◽

Andrew Bakshi ◽

Galina Polekhina ◽

Le Thao ◽

...

Keyword(s):

Ischemic Stroke ◽

Risk Score ◽

Predictive Performance ◽

Polygenic Risk Score ◽

Older Population ◽

Polygenic Risk

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O58. Childhood Urbanization Affects Prefrontal Cortical Responses to Trait Anxiety and Interacts With Polygenic Risk for Depression

Biological Psychiatry ◽

10.1016/j.biopsych.2019.03.323 ◽

2019 ◽

Vol 85 (10) ◽

pp. S129

Author(s):

Xiao Zhang ◽

Hao Yan ◽

Hao Yu ◽

Xin Zhao ◽

Shefali Shah ◽

...

Keyword(s):

Trait Anxiety ◽

Polygenic Risk ◽

Prefrontal Cortical ◽

Cortical Responses ◽

Risk For Depression

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Polygenic Risk Scores Augment Stroke Subtyping

Neurology Genetics ◽

10.1212/nxg.0000000000000560 ◽

2021 ◽

Vol 7 (2) ◽

pp. e560

Author(s):

Jiang Li ◽

Durgesh P. Chaudhary ◽

Ayesha Khan ◽

Christoph Griessenauer ◽

David J. Carey ◽

...

Keyword(s):

Ischemic Stroke ◽

Genetic Correlation ◽

Genome Wide Association Study ◽

Low Frequency ◽

European Ancestry ◽

Risk Scores ◽

Polygenic Risk Score ◽

Large Artery ◽

Polygenic Risk ◽

Gene Sets

ObjectiveTo determine whether the polygenic risk score (PRS) derived from MEGASTROKE is associated with ischemic stroke (IS) and its subtypes in an independent tertiary health care system and to identify the PRS derived from gene sets of known biological pathways associated with IS.MethodsControls (n = 19,806/7,484, age ≥69/79 years) and cases (n = 1,184/951 for discovery/replication) of acute IS with European ancestry and clinical risk factors were identified by leveraging the Geisinger Electronic Health Record and chart review confirmation. All Geisinger MyCode patients with age ≥69/79 years and without any stroke-related diagnostic codes were included as low risk control. Genetic heritability and genetic correlation between Geisinger and MEGASTROKE (EUR) were calculated using the summary statistics of the genome-wide association study by linkage disequilibrium score regression. All PRS for any stroke (AS), any ischemic stroke (AIS), large artery stroke (LAS), cardioembolic stroke (CES), and small vessel stroke (SVS) were constructed by PRSice-2.ResultsA moderate heritability (10%–20%) for Geisinger sample as well as the genetic correlation between MEGASTROKE and the Geisinger cohort was identified. Variation of all 5 PRS significantly explained some of the phenotypic variations of Geisinger IS, and the R2 increased by raising the cutoff for the age of controls. PRSLAS, PRSCES, and PRSSVS derived from low-frequency common variants provided the best fit for modeling (R2 = 0.015 for PRSLAS). Gene sets analyses highlighted the association of PRS with Gene Ontology terms (vascular endothelial growth factor, amyloid precursor protein, and atherosclerosis). The PRSLAS, PRSCES, and PRSSVS explained the most variance of the corresponding subtypes of Geisinger IS suggesting shared etiologies and corroborated Geisinger TOAST subtyping.ConclusionsWe provide the first evidence that PRSs derived from MEGASTROKE have value in identifying shared etiologies and determining stroke subtypes.

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Does Childhood Trauma Moderate Polygenic Risk for Depression? A Meta-analysis of 5765 Subjects From the Psychiatric Genomics Consortium

Biological Psychiatry ◽

10.1016/j.biopsych.2017.09.009 ◽

2018 ◽

Vol 84 (2) ◽

pp. 138-147 ◽

Cited By ~ 31

Author(s):

Wouter J. Peyrot ◽

Sandra Van der Auwera ◽

Yuri Milaneschi ◽

Conor V. Dolan ◽

Pamela A.F. Madden ◽

...

Keyword(s):

Childhood Trauma ◽

Meta Analysis ◽

Polygenic Risk ◽

Risk For Depression

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Polygenic risk for depression and the neural correlates of working memory in healthy subjects

Progress in Neuro-Psychopharmacology and Biological Psychiatry ◽

10.1016/j.pnpbp.2017.06.010 ◽

2017 ◽

Vol 79 ◽

pp. 67-76 ◽

Cited By ~ 9

Author(s):

Dilara Yüksel ◽

Bruno Dietsche ◽

Andreas J. Forstner ◽

Stephanie H. Witt ◽

Robert Maier ◽

...

Keyword(s):

Working Memory ◽

Healthy Subjects ◽

Neural Correlates ◽

Polygenic Risk ◽

Risk For Depression

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Combining Clinical and Polygenic Risk Improves Stroke Prediction Among Individuals with Atrial Fibrillation

Circulation Genomic and Precision Medicine ◽

10.1161/circgen.120.003168 ◽

2021 ◽

Author(s):

Jack W. O'Sullivan ◽

Anna Shcherbina ◽

Johanne M. Justesen ◽

Mintu Turakhia ◽

Marco Perez ◽

...

Keyword(s):

Risk Factors ◽

Atrial Fibrillation ◽

Ischemic Stroke ◽

Predictive Ability ◽

Clinical Risk Factors ◽

Risk Scores ◽

Polygenic Risk ◽

Clinical Risk ◽

Increased Risk ◽

The Uk

Background - Atrial fibrillation (AF) is associated with a five-fold increased risk of ischemic stroke. A portion of this risk is heritable, however current risk stratification tools (CHA 2 DS 2 -VASc) don't include family history or genetic risk. We hypothesized that we could improve ischemic stroke prediction in patients with AF by incorporating polygenic risk scores (PRS). Methods - Using data from the largest available GWAS in Europeans, we combined over half a million genetic variants to construct a PRS to predict ischemic stroke in patients with AF. We externally validated this PRS in independent data from the UK Biobank, both independently and integrated with clinical risk factors. The integrated PRS and clinical risk factors risk tool had the greatest predictive ability. Results - Compared with the currently recommended risk tool (CHA 2 DS 2 -VASc), the integrated tool significantly improved net reclassification (NRI: 2.3% (95%CI: 1.3% to 3.0%)), and fit (χ2 P =0.002). Using this improved tool, >115,000 people with AF would have improved risk classification in the US. Independently, PRS was a significant predictor of ischemic stroke in patients with AF prospectively (Hazard Ratio: 1.13 per 1 SD (95%CI: 1.06 to 1.23)). Lastly, polygenic risk scores were uncorrelated with clinical risk factors (Pearson's correlation coefficient: -0.018). Conclusions - In patients with AF, there appears to be a significant association between PRS and risk of ischemic stroke. The greatest predictive ability was found with the integration of PRS and clinical risk factors, however the prediction of stroke remains challenging.

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Predictive Performance of a Polygenic Risk Score for Incident Ischemic Stroke in a Healthy Older Population

Stroke ◽

10.1161/strokeaha.120.033670 ◽

2021 ◽

Author(s):

Johannes T. Neumann ◽

Moeen Riaz ◽

Andrew Bakshi ◽

Galina Polekhina ◽

Le T.P. Thao ◽

...

Keyword(s):

Risk Factors ◽

Ischemic Stroke ◽

Area Under The Curve ◽

Hazard Ratio ◽

Multivariable Model ◽

Older Population ◽

Conventional Model ◽

Polygenic Risk ◽

Stroke Subtypes ◽

Conventional Risk Factors

Background and Purpose: Polygenic risk scores (PRSs) can be used to predict ischemic stroke (IS). However, further validation of PRS performance is required in independent populations, particularly older adults in whom the majority of strokes occur. Methods: We predicted risk of incident IS events in a population of 12 792 healthy older individuals enrolled in the ASPREE trial (Aspirin in Reducing Events in the Elderly). The PRS was calculated using 3.6 million genetic variants. Participants had no previous history of cardiovascular events, dementia, or persistent physical disability at enrollment. The primary outcome was IS over 5 years, with stroke subtypes as secondary outcomes. A multivariable model including conventional risk factors was applied and reevaluated after adding PRS. Area under the curve and net reclassification were evaluated. Results: At baseline, mean population age was 75 years. In total, 173 incident IS events occurred over a median follow-up of 4.7 years. When PRS was added to the multivariable model as a continuous variable, it was independently associated with IS (hazard ratio, 1.41 [95% CI, 1.20–1.65] per SD of the PRS; P <0.001). The PRS alone was a better discriminator for IS events than most conventional risk factors. PRS as a categorical variable was a significant predictor in the highest tertile (hazard ratio, 1.74; P =0.004) compared with the lowest. The area under the curve of the conventional model was 66.6% (95% CI, 62.2–71.1) and after inclusion of the PRS, improved to 68.5 ([95% CI, 64.0–73.0] P =0.095). In subgroup analysis, the continuous PRS remained an independent predictor for large vessel and cardioembolic stroke subtypes but not for small vessel stroke. Reclassification was improved, as the continuous net reclassification index after adding PRS to the conventional model was 0.25 (95% CI, 0.17–0.43). Conclusions: PRS predicts incident IS in a healthy older population but only moderately improves prediction over conventional risk factors. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01038583.

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