Biology subjects

Jimenez-Conde, J.

Publications and source records attributed to Jimenez-Conde, J..

5 recordsLinked to original sources

bioRxiv2025

Biological age acceleration is more prevalent in men than in women at time of spontaneous intracerebral hemorrhage

ObjectiveSpontaneous intracerebral hemorrhage (ICH) occurs later in life in women compared to men. Although previous studies have demonstrated epigenetic age acceleration (EAA) differences in ischemic stroke (IS) patients - a measure of an individuals biological aging -it remains unknown whether this sex dimorphism also applies to ICH patients. Approach and ResultsWe joined two ICH cohorts (N= 200, 45% women: 76.8{+/-}13 years; 55% men: 67.9{+/-}14 years). DNAm levels were obtained from whole blood samples using Illumina EPIC array. We evaluated three age-predictor clocks (Horvath, Hannum and Zang-BLUP) and one health-status clock (Levine) and their respective EAA metrics including extrinsic EAA (EEAA) and intrinsic EAA (IEAA) measures. We compared aging measures between women and men, then performed an ICH-subtype stratification, a specificity analysis evaluating sex differences in non-stroke samples (N= 350, 54% women 60.8{+/-}8 years, men: 60.8{+/-}10 years) and replication of previous result in a new IS cohort (N= 657, 43% women 73.6{+/-}12 years, men: 70.1{+/-}11 years). Women at time of ICH present lower EAA values than men (Horvath-EAA, p-value=1x10-04; Hannum-EAA, p-value=8.1x10-06; BLUP-EAA, p-value=4.4x10-04) as well as lower extrinsic EAA values (Horvath-IEAA, p-value=3.1x10-03; Hannum-IEAA, p-value=6.5x10-04). These differences seemed to be driven by differences in deep-ICH patients. Non-ICH females have lower acceleration values (Hannum-EAA: -10,37) than non-ICH men (Hannum-EAA: -8,01), but the differences are smaller than in ICH cases (ICH-women Hannum-EAA: -9,26, ICH-men Hannum-EAA: -2,6). This pattern was consistent in the IS cohort, where women were chronologically older than men but had similar biological age and significantly lower epigenetic age acceleration across multiple measures (Horvath-EAA, p = 2.6x10-3; Hannum-EAA, p = 7.1x10-3; Horvath-IEAA, p = 1.6x10-2; Hannum-IEAA, p = 4.5x10-2). ConclusionThis study shows that biological age difference between women and men are not exclusive of ischemic stroke but also observed in ICH.

neuroscience↗

bioRxiv2020

Sex-specific lesion topographies explain outcomesafter acute ischemic stroke

Acute ischemic stroke affects men and women differently in many ways. In particular, women are oftentimes reported to experience a higher acute stroke severity than men. Here, we derived a low-dimensional representation of anatomical stroke lesions and designed a sex-aware Bayesian hierarchical modelling framework for a large-scale, well phenotyped stroke cohort. This framework was tailored to carefully estimate possible sex differences in lesion patterns explaining acute stroke severity (NIHSS) in 1,058 patients (39% female). Anatomical regions known to subserve motor and language functions emerged as relevant regions for both men and women. Female patients, however, presented a more widespread pattern of stroke severity-relevant lesions than male patients. Furthermore, particularly lesions in the posterior circulation of the left hemisphere underlay a higher stroke severity exclusively in women. These sex-sensitive lesion pattern effects could be discovered and subsequently robustly replicated in two large independent, multisite lesion datasets. The constellation of findings has several important conceptual and clinical implications: 1) suggesting sex-specific functional cerebral asymmetries, and 2) motivating a sex-stratified approach to management of acute ischemic stroke. To go beyond sex-averaged stroke research, future studies should explicitly test whether acute therapies administered on the basis of sex-specific cutoff volumes of salvageable tissue will lead to improved outcomes in women after acute ischemic stroke.

neuroscience↗

bioRxiv2019

Identification of 20 novel loci associated to ischemic stroke. Epigenome-Wide Association Study

RationaleDNA methylation is dynamic, varies throughout the life course, and its levels are influenced by lifestyle and environmental factors, as well as by genetic variation. The leading genetic variants at stroke risk loci identified to date explain roughly 1-2% of stroke heritability. Most of these single nucleotide polymorphisms are situated within a regulatory sequence marked by DNase I hypersensitivity sites, which would indicate involvement of an epigenetic mechanism. ObjectiveTo detect epigenetic variants associated to stroke occurrence and stroke subtypes. Methods and ResultsA two-stage case-control epigenome-wide association study was designed. The discovery sample with 401 samples included 218 ischemic stroke (IS) patients, assessed at Hospital del Mar (Barcelona, Spain) and 183 controls from the REGICOR cohort. In two independent samples (N=226 and N=166), we replicated 22 CpG sites differentially methylated in IS in 21 loci, including 2 CpGs in locus ZFHX3, which includes known genetic variants associated with stroke. The pathways associated to these loci are inflammation and angiogenesis. The meta-analysis identified 384 differentially methylated CpGs, including loci of known stroke and vascular risk genetic variants, enriched by loci involved in lipid metabolism, adipogenesis, circadian clock, and glycolysis pathways. Stratification analysis by stroke subtypes revealed distinct methylation patterns. ConclusionsWe identified a set of 22 CpGs in 21 loci associated with IS. Our analysis suggests that DNA methylation changes may contribute to orchestrating gene expression that contributes to IS.

genetics↗

bioRxiv2019

White Matter Hyperintensity Quantification in Large-Scale Clinical Acute Ischemic Stroke Cohorts - The MRI-GENIE Study

White matter hyperintensity (WMH) burden is a critically important cerebrovascular phenotype linked to prediction of diagnosis and prognosis of diseases, such as acute ischemic stroke (AIS). However, current approaches to its quantification on clinical MRI often rely on time intensive manual delineation of the disease on T2 fluid attenuated inverse recovery (FLAIR), which hinders high-throughput analyses such as genetic discovery. In this work, we present a fully automated pipeline for quantification of WMH in clinical large-scale studies of AIS. The pipeline incorporates automated brain extraction, intensity normalization and WMH segmentation using spatial priors. We first propose a brain extraction algorithm based on a fully convolutional deep learning architecture, specifically designed for clinical FLAIR images. We demonstrate that our method for brain extraction outperforms two commonly used and publicly available methods on clinical quality images in a set of 144 subject scans across 12 acquisition centers, based on dice coefficient (median 0.95; inter-quartile range 0.94-0.95) and Pearson correlation of total brain volume (r=0.90). Subsequently, we apply it to the large-scale clinical multi-site MRI-GENIE study (N=2783) and identify a decrease in total brain volume of -2.4cc/year. Additionally, we show that the resulting total brain volumes can successfully be used for quality control of image preprocessing. Finally, we obtain WMH volumes by building on an existing automatic WMH segmentation algorithm that delineates and distinguishes between different cerebrovascular pathologies. The learning method mimics expert knowledge of the spatial distribution of the WMH burden using a convolutional auto-encoder. This enables successful computation of WMH volumes of 2,533 clinical AIS patients. We utilize these results to demonstrate the increase of WMH burden with age (0.950 cc/year) and show that single site estimates can be biased by the number of subjects recruited.

neuroscience↗

bioRxiv2018

The Subtype Specificity of Genetic Loci Associated with Stroke in 16,664 cases and 32,792 controls

BackgroundGenome-wide association studies have identified multiple loci associated with stroke. However, the specific stroke subtypes affected, and whether loci influence both ischaemic and haemorrhagic stroke, remains unknown. For loci associated with stroke, we aimed to infer the combination of stroke subtypes likely to be affected, and in doing so assess the extent to which such loci have homogeneous effects across stroke subtypes.\n\nMethodsWe performed Bayesian multinomial regression in 16,664 stroke cases and 32,792 controls of European ancestry to determine the most likely combination of stroke subtypes affected for loci with published genome-wide stroke associations, using model selection. Cases were subtyped under two commonly used stroke classification systems, Trial of Org 10172 Acute Stroke Treatment (TOAST) and Causative Classification of Stroke (CCS). All individuals had genotypes imputed to the Haplotype Reference Consortium 1.1 Panel.\n\nResultsSixteen loci were considered for analysis. Seven loci influenced both haemorrhagic and ischaemic stroke, three of which influenced ischaemic and haemorrhagic subtypes under both TOAST and CCS. Under CCS, 4 loci influenced both small vessel stroke and intracerebral haemorrhage. An EDNRA locus demonstrated opposing effects on ischaemic and haemorrhagic stroke. No loci were predicted to influence all stroke subtypes in the same direction and only one locus (12q24) was predicted to influence all ischaemic stroke subtypes.\n\nConclusionsHeterogeneity in the influence of stroke-associated loci on stroke subtypes is pervasive, reflecting differing causal pathways. However, overlap exists between haemorrhagic and ischaemic stroke, which may reflect shared pathobiology predisposing to small vessel arteriopathy. Stroke is a complex, heterogeneous disorder requiring tailored analytic strategies to decipher genetic mechanisms.

genetics↗