Publications by authors named "Felix Vaura"

Hypertension and hypertensive disorders of pregnancy (HDP) cause a significant burden of disease on societies and individuals by increasing cardiovascular disease risk. Environmental risk factors alone do not explain the observed sexual dimorphism in lifetime blood pressure (BP) trajectories nor inter-individual variation in HDP risk. In this short review, we focus on the genetics of hypertension-related sex differences and HDP and discuss the importance of genetics utilization for sex-specific hypertension risk prediction.

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Background: Preexisting hypertension increases risk for preeclampsia. We examined whether a generic blood pressure polygenic risk score (BP-PRS), compared with a preeclampsia-specific polygenic risk score (PE-PRS), could better predict hypertensive disorders of pregnancy.

Methods: Our study sample included 141 298 genotyped FinnGen study participants with at least one childbirth and followed from 1969 to 2021.

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Article Synopsis
  • Population isolates like Finland provide a unique advantage for genetic research by having concentrated deleterious alleles in low-frequency variants due to historical bottlenecks.
  • The FinnGen study aims to analyze data from 500,000 Finnish individuals, focusing on their genomes and health records, particularly as many participants are older and have disease-related data.
  • From the analysis of 224,737 participants and additional biobank data, researchers discovered 30 new associations and a total of 2,733 significant genetic links across various diseases, highlighting the importance of low-frequency variants in understanding common diseases.
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Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.

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Background: Hypertension comprises a heterogeneous range of phenotypes. We asked whether underlying genetic structure could explain a part of this heterogeneity.

Methods: Our study sample comprised N=198 148 FinnGen participants (56% women, mean age 58 years) and N=21 168 well-phenotyped FINRISK participants (53% women, mean age 50 years).

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Despite the well-known sex dimorphism in cardiovascular disease traits, the exact genetic, molecular, and cellular underpinnings of these differences are not well understood. A growing body of evidence currently points at the links between cardiovascular disease traits and the genome, epigenome, transcriptome, and metabolome. However, the sex-specific differences in these links remain largely unstudied due to challenges in bioinformatic methods, inadequate statistical power, analytic costs, and paucity of valid experimental models.

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Coronary procedures predispose patients to adverse events. To improve our understanding of the genetic factors underlying postoperative prognosis, we studied the association of polygenic risk scores (PRSs) with postprocedural complications in coronary patients who underwent revascularization. The study sample comprised 8,296, 6,132, and 13,082 patients who underwent percutaneous coronary intervention, coronary artery bypass grafting, or any revascularization, respectively.

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Article Synopsis
  • The HERMES consortium is focused on understanding the genomic and molecular factors that contribute to heart failure by analyzing data from a large number of studies worldwide.
  • It includes 51 studies from 11 countries, gathering data from over 68,000 heart failure cases and nearly 950,000 controls, with broad demographic representation and long follow-up periods.
  • The main goals are to identify genetic risk factors for heart failure, explore causal pathways, and create tools to help stratify patients and predict risks based on their genetic information.
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Purpose: Macrophages are critical in driving an immunosuppressive tumor microenvironment that counteracts the efficacy of T-cell-targeting therapies. Thus, agents able to reprogram macrophages toward a proinflammatory state hold promise as novel immunotherapies for solid cancers. Inhibition of the macrophage scavenger receptor Clever-1 has shown benefit in inducing CD8 T-cell-mediated antitumor responses in mouse models of cancer, which supports the clinical development of Clever-1-targeting antibodies for cancer treatment.

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Background: Synovial fluid bacterial culture is the cornerstone of confirmation or exclusion of periprosthetic joint infection (PJI). The aim of this study was to assess synovial fluid and serum biomarker patterns of patients with total joint arthroplasty (TJA), and the association of these patterns with PJI.

Methods: Synovial fluid and serum samples were collected from 35 patients who were admitted to the Arthroplasty Unit of the Department of Orthopaedics and Traumatology at Turku University Hospital.

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Although genetic risk scores have been used to predict hypertension, their utility in the clinical setting remains uncertain. Our study comprised N=218 792 FinnGen participants (mean age 58 years, 56% women) and N=22 624 well-phenotyped FINRISK participants (mean age 50 years, 53% women). We used public genome-wide association data to compute polygenic risk scores (PRSs) for systolic and diastolic blood pressure (BP).

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The current classification of hypertension does not reflect the heterogeneity in characteristics or cardiovascular outcomes of hypertensive individuals. Our objective was to identify distinct phenotypes of hypertensive individuals with potentially different cardiovascular risk profiles using data-driven cluster analysis. We performed clustering, a procedure that identifies groups with similar characteristics, in 3726 individuals (mean age 59.

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