Publications by authors named "Cordova-Palomera A"

Article Synopsis
  • - The text discusses the challenges of detecting complex genetic interactions (epistasis) that influence human traits, pointing out that traditional regression methods struggle with high-order interactions in large genomic datasets due to computational limitations and inadequacies in modeling biological interactions properly.
  • - It introduces the epiTree pipeline, built on a framework called Predictability, Computability, Stability (PCS), which utilizes tree-based models to identify higher-order interactions in genomic data by selecting relevant variants based on tissue-specific gene expression and employing iterative random forests.
  • - The efficacy of the epiTree pipeline is validated through two case studies from the UK Biobank, demonstrating its ability to reveal both known and novel genetic interactions in predicting traits like red hair and multiple sclerosis, thus potentially
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As findings on the epidemiological and genetic risk factors for coronavirus disease-19 (COVID-19) continue to accrue, their joint power and significance for prospective clinical applications remains virtually unexplored. Severity of symptoms in individuals affected by COVID-19 spans a broad spectrum, reflective of heterogeneous host susceptibilities across the population. Here, we assessed the utility of epidemiological risk factors to predict disease severity prospectively, and interrogated genetic information (polygenic scores) to evaluate whether they can provide further insights into symptom heterogeneity.

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Article Synopsis
  • Congenital heart disease (CHD) has a strong genetic component, yet previous research has struggled to pinpoint inherited risks due to limited analysis of common variants in small groups of people.
  • A large study involving 55,342 participants reanalyzed genetic data, identifying 16 new genetic locations associated with different types of CHD, including 12 rare variants with notable effects.
  • The findings indicate that while each type of CHD is heritable, they appear to have distinct genetic risks, underscoring the complexity of CHD genetics.
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Parkinson's disease (PD) treatments modify disease symptoms but have not been shown to slow progression, characterized by gradual and varied motor and non-motor changes overtime. Variation in PD progression hampers clinical research, resulting in long and expensive clinical trials prone to failure. Development of models for short-term PD progression prediction could be useful for shortening the time required to detect disease-modifying drug effects in clinical studies.

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Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), a respiratory illness that can result in hospitalization or death. We used exome sequence data to investigate associations between rare genetic variants and seven COVID-19 outcomes in 586,157 individuals, including 20,952 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome wide or when specifically focusing on (1) 13 interferon pathway genes in which rare deleterious variants have been reported in individuals with severe COVID-19, (2) 281 genes located in susceptibility loci identified by the COVID-19 Host Genetics Initiative, or (3) 32 additional genes of immunologic relevance and/or therapeutic potential.

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Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease-19 (COVID-19), a respiratory illness that can result in hospitalization or death. We investigated associations between rare genetic variants and seven COVID-19 outcomes in 543,213 individuals, including 8,248 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome-wide or when specifically focusing on (i) 14 interferon pathway genes in which rare deleterious variants have been reported in severe COVID-19 patients; (ii) 167 genes located in COVID-19 GWAS risk loci; or (iii) 32 additional genes of immunologic relevance and/or therapeutic potential.

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Background: The aortic valve is an important determinant of cardiovascular physiology and anatomic location of common human diseases.

Methods: From a sample of 34 287 white British ancestry participants, we estimated functional aortic valve area by planimetry from prospectively obtained cardiac magnetic resonance imaging sequences of the aortic valve. Aortic valve area measurements were submitted to genome-wide association testing, followed by polygenic risk scoring and phenome-wide screening, to identify genetic comorbidities.

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Monozygotic (MZ) twin studies constitute a key resource for the dissection of environmental and biological risk factors for human complex disorders. Given that epigenetic differences accumulate throughout the lifespan, the assessment of MZ twin pairs discordant for depression offers a genetically informative design to explore DNA methylation while accounting for the typical confounders of the field, shared by co-twins of a pair. In this review, we systematically evaluate all twin studies published to date assessing DNA methylation in association with depressive phenotypes.

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Article Synopsis
  • Sensitivity to external environments is crucial for adaptation, but it can also lead to negative effects in bad conditions.
  • This study uses a new method to analyze genetic and neuroanatomical data from 25,575 individuals to explore variability in key brain features.
  • Findings reveal specific genetic loci linked to differences in thalamus volume and cortical thickness, highlighting a genetic basis for brain structure variability and its implications for brain and mental health research.
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Congenital heart disease is the most common birth defect in newborns and the leading cause of death in infancy, affecting nearly 1% of live births. A locus in chromosome 4p16, adjacent to MSX1 and STX18, has been associated with atrial septal defects (ASD) in multiple European and Chinese cohorts. Here, genotyping data from the UK Biobank was used to test for associations between this locus and congenital heart disease in adult survivors of left ventricular outflow tract obstruction (n = 164) and ASD (n = 223), with a control sample of 332,788 individuals, and a meta-analysis of the new and existing ASD data was performed.

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Common risk factors for psychiatric and other brain disorders are likely to converge on biological pathways influencing the development and maintenance of brain structure and function across life. Using structural MRI data from 45,615 individuals aged 3-96 years, we demonstrate distinct patterns of apparent brain aging in several brain disorders and reveal genetic pleiotropy between apparent brain aging in healthy individuals and common brain disorders.

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Importance: Between-individual variability in brain structure is determined by gene-environment interactions, possibly reflecting differential sensitivity to environmental and genetic perturbations. Magnetic resonance imaging (MRI) studies have revealed thinner cortices and smaller subcortical volumes in patients with schizophrenia. However, group-level comparisons may mask considerable within-group heterogeneity, which has largely remained unnoticed in the literature.

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Background: Accumulating evidence supports cerebellar involvement in mental disorders, such as schizophrenia, bipolar disorder, depression, anxiety disorders, and attention-deficit/hyperactivity disorder. However, little is known about the cerebellum in developmental stages of these disorders. In particular, whether cerebellar morphology is associated with early expression of specific symptom domains remains unclear.

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Oxytocin is a neuropeptide involved in animal and human reproductive and social behavior. Three oxytocin signaling genes have been frequently implicated in human social behavior: OXT (structural gene for oxytocin), OXTR (oxytocin receptor), and CD38 (oxytocin secretion). Here, we characterized the distribution of OXT, OXTR, and CD38 mRNA across the human brain by creating voxel-by-voxel volumetric expression maps, and identified putative gene pathway interactions by comparing gene expression patterns across 20,737 genes.

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Loss of function variants in NOTCH1 cause left ventricular outflow tract obstructive defects (LVOTO). However, the risk conferred by rare and noncoding variants in NOTCH1 for LVOTO remains largely uncharacterized. In a cohort of 49 families affected by hypoplastic left heart syndrome, a severe form of LVOTO, we discovered predicted loss of function NOTCH1 variants in 6% of individuals.

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Recent discoveries highlight the importance of stochastic epigenetic changes, as indexed by epigenetic outlier DNA methylation signatures, as a valuable tool to understand aberrant cell function and subsequent human pathology. There is evidence of such changes in different complex disorders as diverse as cancer, obesity and, to a lesser extent, depression. The current study was aimed at identifying outlying DNA methylation signatures of depressive psychopathology.

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The hippocampus is a heterogeneous structure, comprising histologically distinguishable subfields. These subfields are differentially involved in memory consolidation, spatial navigation and pattern separation, complex functions often impaired in individuals with brain disorders characterized by reduced hippocampal volume, including Alzheimer's disease (AD) and schizophrenia. Given the structural and functional heterogeneity of the hippocampal formation, we sought to characterize the subfields' genetic architecture.

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Supported by histological and genetic evidence implicating myelin, neuroinflammation and oligodendrocyte dysfunction in schizophrenia spectrum disorders (SZ), diffusion tensor imaging (DTI) studies have consistently shown white matter (WM) abnormalities when compared to healthy controls (HC). The diagnostic specificity remains unclear, with bipolar disorders (BD) frequently conceptualized as a less severe clinical manifestation along a psychotic spectrum. Further, the age-related dynamics and possible sex differences of WM abnormalities in SZ and BD are currently understudied.

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Background: Depression is a complex disorder with large interindividual variability in symptom profiles that often occur alongside symptoms of other psychiatric domains, such as anxiety. A dimensional and symptom-based approach may help refine the characterization of depressive and anxiety disorders and thus aid in establishing robust biomarkers. We use resting-state functional magnetic resonance imaging to assess the brain functional connectivity correlates of a symptom-based clustering of individuals.

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Cognitive and brain development are determined by dynamic interactions between genes and environment across the lifespan. Aside from marker-by-marker analyses of polymorphisms, biologically meaningful features of the whole genome (derived from the combined effect of individual markers) have been postulated to inform on human phenotypes including cognitive traits and their underlying biological substrate. Here, estimates of inbreeding and genetic susceptibility for schizophrenia calculated from genome-wide data-runs of homozygosity (ROH) and schizophrenia polygenic risk score (PGRS)-are analyzed in relation to cognitive abilities (n = 4183) and brain structure (n = 516) in a general-population sample of European-ancestry participants aged 8-22, from the Philadelphia Neurodevelopmental Cohort.

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Among the major psychiatric disorders, anxious-depressive disorders stand out as one of the more prevalent and more frequently associated with hypothalamic-pituitary-adrenal (HPA) axis abnormalities. Methylation at the exon 1 of the glucocorticoid receptor gene NR3C1 has been associated with both early stress exposure and risk for developing a psychiatric disorder; however, other NR3C1 promoter regions have been underexplored. Exon 1 emerges as a suggestive new target in stress-related disorders epigenetically sensitive to early adversity.

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Importance: Many mental disorders emerge during adolescence, which may reflect a cost of the potential for brain plasticity offered during this period. Brain dysconnectivity has been proposed as a common factor across diagnostic categories.

Objective: To investigate the hypothesis that brain dysconnectivity is a transdiagnostic phenotype in adolescence with increased susceptibility and symptoms of psychiatric disease.

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Alzheimer's disease (AD) is a debilitating age-related neurodegenerative disorder. Accurate identification of individuals at risk is complicated as AD shares cognitive and brain features with aging. We applied linked independent component analysis (LICA) on three complementary measures of gray matter structure: cortical thickness, area and gray matter density of 137 AD, 78 mild (MCI) and 38 subjective cognitive impairment patients, and 355 healthy adults aged 18-78 years to identify dissociable multivariate morphological patterns sensitive to age and diagnosis.

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Although cerebellar involvement across a wide range of cognitive and neuropsychiatric phenotypes is increasingly being recognized, previous large-scale studies in schizophrenia (SZ) have primarily focused on supratentorial structures. Hence, the across-sample reproducibility, regional distribution, associations with cerebrocortical morphology and effect sizes of cerebellar relative to cerebral morphological differences in SZ are unknown. We addressed these questions in 983 patients with SZ spectrum disorders and 1349 healthy controls (HCs) from 14 international samples, using state-of-the-art image analysis pipelines optimized for both the cerebellum and the cerebrum.

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