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Biology subjects

Silveira, P. P.

Publications and source records attributed to Silveira, P. P..

12 recordsLinked to original sources

Multilevel sex-specific neurobiological signatures of early life adversity

Stress exposure early in life is an established risk factor for adult psychiatric illness, yet these disorders - including anxiety disorders and depression - show significant sex-dependence in prevalence, symptomatology, and treatment response. The biology underlying these differences remains largely unexplored and may contribute to the clinical heterogeneity in anxiety and depression. Here, we characterize the lasting impact of developmental stress on adulthood neurobiology and behavior in mice by combining analyses of multiple levels of brain function, including whole-brain c-Fos mapping, manganese-enhanced MRI and transcriptomics with advanced behavioral phenotyping. Across levels of investigation, we find distinct and often opposite effects of developmental stress depending on sex. These results together showcase the strong influence of sex on how early life adversity affects the onset of stress-related disorders. This work emphasizes the necessity of considering sex when investigating developmental and neurobiological underpinnings of stress-related disorders and displays a vast range of lasting effects of developmental stress on the brain, which provides a valuable resource for future studies aiming to improve psychiatric treatments.

neuroscience↗

A glucocorticoid-responsive polygenic signature in the anterior cingulate cortex moderates the association of early-life adversity and vulnerability for depression

Stress exposure is a major risk factor for psychopathology, yet how stress mediators shape long-term psychiatric vulnerability in humans remains unclear. Glucocorticoids, central effectors of the stress response, regulate gene expression through tissue-specific transcriptional programs, suggesting that glucocorticoid-responsive networks may shape sensitivity to adversity. Using RNA-sequencing following chronic glucocorticoid exposure in a non-human primate model, we identified a gene co-expression network specific to the anterior cingulate cortex (ACC) that was highly preserved across human post-mortem brain datasets relevant to depression. We derived an expression-based polygenic score (ePGS) reflecting genetic variation in network activity and tested its interaction with adversity in the UK Biobank. The ACC-specific glucocorticoid-responsive ePGS moderated the association between adversity and depressive symptoms in adult females, with the strongest effects for early-life adversity. Network genes were enriched for neurodevelopmental processes and showed stronger co-expression during childhood, highlighting a developmentally sensitive, region-specific mechanism linking stress exposure to depression risk.

neuroscience↗

Insulin modulates mPFC gene expression and emotional behavior in a sex-specific manner following fetal growth restriction

Exposure to prenatal adversity (e.g., stress, malnutrition) is a major risk factor for lifelong vulnerability to neuropsychiatric and metabolic disorders, and alterations in the function of peripheral hormones in the brain are suggested as a possible and unexplored mechanism. Although insulin is well known for its peripheral metabolic functions, it also influences brain development and emotional regulation, particularly within the medial prefrontal cortex (mPFC). Here, we identify insulin signaling as a key mechanistic link between prenatal stress and long-term alterations in brain function and behavior. Using a validated rat model of prenatal adversity (prenatal food restriction, FR), we found that insulin administration selectively modulates gene expression in FR animals at P0, P21 and P90, affecting pathways involved in neurodevelopment and stress regulation, such as Wnt/{beta}-catenin signaling. Targeted insulin infusion into the mPFC of adult animals reversed behavioral phenotypes induced by FR in a sex- and context-dependent manner, decreasing emotional reactivity to environmental cues. These findings offer novel insight into the neurodevelopmental role of insulin and suggest that insulin signaling may serve as a therapeutic target to mitigate the long-term brain and behavioral consequences of prenatal adversity.

genomics↗

Expression based polygenic scores - A gene network perspective to capture individual differences in biological processes.

Incorporating functional aspects into polygenic scores may accelerate early diagnosis and the discovery of therapeutic targets. Yet, existing polygenic scores summarize information from genome wide statistical associations between SNPs and phenotypes. We developed the novel biologically informed, expression-based polygenic scores (ePRS or ePGS). The method characterizes tissue specific gene co-expression networks from genome-wide RNA sequencing data and incorporates this information into polygenic scores. Performance and characteristics of the ePGS were compared to traditional polygenic risk score (PRS). We observed that ePGS differs from PRS for aggregating information on; i. the relation between different genes (co-expression); ii. the levels of tissue-specific gene expression; iii. the genetic variation of the target sample; iv. the tissue-specific effect size of the association between genotyping and gene expression; v. the portability across different ancestries. Variations in the ePGS represent individual variations in the expression of a tissue-specific gene co-expression network, and this methodology may profoundly influence the way we study human disease biology.

bioinformatics↗

Effects of prenatal maternal immune activation and exposure to circadian disruption during adolescence: exploring the two-hit model of neurodevelopmental disorders

BackgroundAround 80% of individuals with neurodevelopmental disorders (NDDs) such as schizophrenia and autism spectrum disorders experience disruptions in sleep/circadian rhythms. We explored whether prenatal infection, an established risk factor for NDDs, and environmental circadian disruption synergistically induced sex-specific deficits in mice. MethodsA maternal immune activation (MIA) protocol was used by injecting pregnant mice (at E9.5) with a viral mimic poly IC or saline. Then, juvenile/adolescent offspring (3-7 weeks old) were subjected to either standard lighting (12:12LD) or constant light (LL). ResultsWe found interactions of the two factors on behaviors related to cognition, anxiety, and sociability. Also, poly IC exposure led to a more activated profile of hippocampal microglia in males only, while LL diminished these effects. Using RNA sequencing in the dorsal hippocampus, we found that poly IC exposure led to many differentially expressed genes in males (but not females), and fewer differentially expressed genes were observed after LL exposure. Using the WGCNA analysis, we found several significant gene modules positively associated with poly IC (in comparison to saline exposure) and LL (in comparison to LD exposure) in males, and less so in females. Interestingly, many of the identified hub bottleneck genes were homologous to human genes associated with both sleep/circadian rhythms and neurodevelopmental disorders as identified by GWA studies. ConclusionsOur work demonstrates that in a mouse model of prenatal infection, disruptions in circadian rhythms induced by LL play a role in modulating the effects of MIA at behavioral, cellular, and molecular levels.

neuroscience↗

Social isolation is linked to classical risk factors of Alzheimer's disease-related dementias

Alzheimers disease and related dementias is a major public health burden - compounding over upcoming years due to longevity. Recently, clinical evidence hinted at the experience of social isolation in expediting dementia onset. In 502,506 UK Biobank participants and 30,097 participants from the Canadian Longitudinal Study of Aging, we revisited traditional risk factors for developing dementia in the context of loneliness and lacking social support. Across these measures of subjective and objective social deprivation, we have identified strong links between individuals social capital and various indicators of Alzheimers disease and related dementias risk, which replicated across both population cohorts. The quality and quantity of daily social encounters had deep connections with key aetiopathological factors, which represent 1) personal habits and lifestyle factors, 2) physical health, 3) mental health, and 4) societal and external factors. Our population-scale assessment suggest that social lifestyle determinants are linked to most neurodegeneration risk factors, highlighting them promising targets for preventive clinical action.

neuroscience↗

Epigenetic signatures of chronic social stress in stress-susceptible animals

Exposure of mice to chronic social defeat stress (CSDS) produces depressive- and anxiety-like behaviors and widespread transcriptomic changes in several brain regions in susceptible animals. Here we present the first study of genome-wide cytosine methylation patterns of mice susceptible to CSDS using whole-genome bisulfite sequencing on DNA from the nucleus accumbens, a critical region for CSDS effects on behavior. We found extensive evidence for differential methylation following exposure to CSDS in susceptible animals, with a greater proportion of CG hypermethylation than hypomethylation in CSDS-susceptible mice compared to non-stressed controls; non-CG methylation shows the opposite trend. Several genes previously implicated in the effects of CSDS are among those with the greatest number of differentially methylated sites, including estrogen receptor alpha (Esr1), the deleted in colorectal cancer (Dcc) gene and Cacna1c, which has been associated with a range of psychiatric conditions. Informatic analysis of DM sites revealed a gene network with {beta}-catenin as the hub gene of a network that included the {beta}-catenin-related WNT/frizzled signaling pathway as well as both Esr1 and Dcc. Finally, we found considerable overlap between DM genes associated with CSDS in susceptible animals and those associated with human neuroticism in a genome-wide association study. Analysis of these overlapping genes revealed WNT signaling as the top pathway, which features {beta}-catenin as the primary hub gene. These findings reveal a striking convergence between the molecular pathways identified through either transcriptional or epigenomic analyses of the mouse model of susceptibility to chronic stress and the genomic architecture of increased stress susceptibility reflected in neuroticism in humans.

neuroscience↗

End-to-end assessment of fecal bacteriome analysis: from sample processing to DNA sequencing and bioinformatics results

Intestinal microbiome, comprising the whole microbiota, their genes and genomes living in the human gut have significant roles in promoting health or disease status. As many studies showed so far, identifying the bacterial components of the microbiome can reveal important biomarkers to help in the disease comprehension to a further adequate treatment. However, the human nature is quite variable considering the genetic components associated with life styles, directly reflecting on the gut microbiome. Thus, it is extremely important to know the populational microbiome background in order to draw conclusions regarding the health and disease conditions. Also, methodological best practices and knowledge about the methods being used are essential for the results quality and applicability with clinical relevance. In this way, we standardized the sample collection and processing methods used for the Probiome assay, a test developed to identify the Brazilian bacteriome from stool samples. EncodeTools Metabarcode pipeline of analysis was developed to obtain the best result from the samples. This pipeline uses the information of amplicon single variants (ASVs) in 100% identical oligotype clusters, and performs a de novo taxonomical assignment based on similarity for unknown sequences. To better comprehend the results obtained in Probiome assays, is essential to know the intestinal bacteriome diversity of Brazilians. Thus, we applied the standardized methods herein developed and began characterizing our populational data to allow a better understanding of the Brazilian bacteriome profiles and how they can be related to other microbiome studies.

microbiology↗

Genomic Surveillance of Yellow Fever Virus Epidemic Waves in Sao Paulo, Brazil, 2017 - 2018

Sao Paulo (SP), a densely inhabited state in southeast Brazil that contains the fourth most populated city in the world, recently experienced its largest yellow fever virus (YFV) outbreak in decades. YFV does not normally circulate extensively in SP, so most people were unvaccinated when the outbreak began. Surveillance in non-human primates (NHPs) is important for determining the magnitude and geographic extent of an epizootic, thereby helping to evaluate the risk of YFV spillover to humans. Data from infected NHPs can give more accurate insights into YFV spread than when using data from human cases alone. To contextualise human cases, identify epizootic foci and uncover the rate and direction of YFV spread in SP, we generated and analysed virus genomic data and epizootic case data from NHP in SP. We report the occurrence of three spatiotemporally distinct phases of the outbreak in SP prior to February 2018. We generated 51 new virus genomes from YFV positive cases identified in 23 different municipalities in SP, mostly sampled from non-human primates between October 2016 and January 2018. Although we observe substantial heterogeneity in lineage dispersal velocities between phylogenetic branches, continuous phylogeographic analyses of generated YFV genomes suggest that YFV lineages spread in Sao Paulo state at a mean rate of approximately 1km per day during all phases of the outbreak. Viral lineages from the first epizootic phase in northern Sao Paulo subsequently dispersed towards the south of the state to cause the second and third epizootic phases there. This alters our understanding of how YFV was introduced into the densely populated south of SP state. Our results shed light on the sylvatic transmission of yellow fever in highly fragmented forested regions in SP state and highlight the importance of continued surveillance of zoonotic pathogens in sentinel species. Authors SummarySince July 2016, the southeast region of Brazil has experienced the largest yellow fever virus (YFV) outbreak in decades. Sao Paulo is the most densely populated state in southeast Brazil. The outbreak has caused serious public health concern in the state, as YFV does not normally circulate widely there and most of the 21 million inhabitants were correspondingly unvaccinated against YFV when the outbreak began. In Brazil, YFV typically circulates among non-human primates, and human cases represent isolated spillover events from this predominantly sylvatic cycle. Understanding the epidemiological dynamics and spread of YFV in non-human primates is therefore critical for contextualising human cases, and guiding vaccination strategies that can better protect local human populations. Here, we aim to contextualise human cases, identify epizootic foci and uncover the rate and direction of YFV spread in SP. We analyse the geographic and temporal distribution of observed cases of YFV in non-human primates in Sao Paulo state, and identify three distinct phases of the epizootic. We generate sequence data from 51 YFV-positive cases and perform phylogenetic and phylogeographic analyses aimed at understanding the spatial spread of YFV in Sao Paulo state. Analyses of these data indicate that YFV spread from the north of Sao Paulo state into more densely populated southern regions. Although we observe substantial heterogeneity in the rate at which different sampled YFV lineages spread, the typical rate of spread was low with a mean rate of ~1 km per day. This is consistent with a scenario in which the majority of transmission events occurred between non-human primates and sylvatic vectors across forested patches. Article Summary LineGenomic surveillance of yellow fever in Sao Paulo during the 2016-2018 epizootic

epidemiology↗

Chikungunya virus outbreak in the Amazon region: replacement of the Asian genotype by an ECSA lineage

BackgroundSince its first detection in the Caribbean in late 2013, chikungunya virus (CHIKV) has affected 51 countries in the Americas. The CHIKV epidemic in the Americas was caused by the CHIKV-Asian genotype. In August 2014, local transmission of the CHIKV-Asian genotype was detected in the Brazilian Amazon region. However, a distinct lineage, the CHIKV-East-Central-South-America (ECSA)-genotype, was detected nearly simultaneously in Feira de Santana, Bahia state, northeast Brazil. The genomic diversity and the dynamics of CHIKV in the Brazilian Amazon region remains poorly understood despite its importance to better understand the epidemiological spread and public health impact of CHIKV in the country.\n\nMethodology/Principal FindingsWe report a large CHIKV outbreak (5,928 notified cases between August 2014 and August 2018) in Boa vista municipality, capital city of Roraimas state, located in the Brazilian Amazon region. In just 48 hours, we generated 20 novel CHIKV-ECSA genomes from the Brazilian Amazon region using MinION portable genome sequencing. Phylogenetic analyses revealed that despite an early introduction of the Asian genotype in 2015 in Roraima, the large CHIKV outbreak in 2017 in Boa Vista was caused by an ECSA-lineage most likely introduced from northeastern Brazil.\n\nEpidemiological analyses suggest a basic reproductive number of R0 of 1.66, which translates in an estimated 39 (95% CI: 36 to 45) % of Roraimas population infected with CHIKV-ECSA. Finally, we find a strong association between Google search activity and the local laboratory-confirmed CHIKV cases in Roraima.\n\nConclusions/SignificanceThis study highlights the potential of combining traditional surveillance with portable genome sequencing technologies and digital epidemiology to inform public health surveillance in the Amazon region. Our data reveal a large CHIKV-ECSA outbreak in Boa Vista, limited potential for future CHIKV outbreaks, and indicate a replacement of the Asian genotype by the ECSA genotype in the Amazon region.\n\nAuthor SummaryUntil the end of 2017, Brazil notified the highest number of infections caused by chikungunya virus (CHIKV) in the Americas. We investigated a large CHIKV outbreak in Boa vista municipality in the Brazilian Amazon region. Rapid portable genome sequencing of 20 novel isolates and subsequent genetic analysis revealed that ECSA lineage was introduced from northeastern Brazil to Roraima around July 2016. Epidemiological analyses suggest a basic reproductive number of R0 of 1.66, which suggests that approximately 39% of Roraimas population was infected with CHIKV-ECSA. Given the dominance of the CHIKV-Asian genotype in the Americas, our data highlights the rapid spread of a less understood and poorly characterized CHIKV-ECSA genotype in Brazil. Investigations on potential associations between public health impact of CHIKV and genetic diversity of circulating strains are warranted to better evaluate its impact in Brazil and beyond.

epidemiology↗

Genomic and epidemiological monitoring of yellow fever virus transmission potential

The yellow fever virus (YFV) epidemic that began in Dec 2016 in Brazil is the largest in decades. The recent discovery of YFV in Brazilian Aedes sp. vectors highlights the urgent need to monitor the risk of re-establishment of domestic YFV transmission in the Americas. We use a suite of epidemiological, spatial and genomic approaches to characterize YFV transmission. We show that the age- and sex-distribution of human cases in Brazil is characteristic of sylvatic transmission. Analysis of YFV cases combined with genomes generated locally using a new protocol reveals an early phase of sylvatic YFV transmission restricted to Minas Gerais, followed in late 2016 by a rise in viral spillover to humans, and the southwards spatial expansion of the epidemic towards previously YFV-free areas. Our results establish a framework for monitoring YFV transmission in real-time, contributing to the global strategy of eliminating future yellow fever epidemics.

epidemiology↗

PRS-on-Spark: a novel, efficient and flexible approach for generating polygenic risk scores

MotivationPolygenic risk scores describe the genomic contribution to complex phenotypes and consistently account for a larger proportion of the variance than single nucleotide polymorphisms alone. However, there is little consensus on the optimal data input for generating polygenic risk scores and existing approaches largely preclude the use of imputed posterior probabilities and strand-ambiguous SNPs.\n\nResultsWe developed PRS-on-Spark (PRSoS) a polygenic risk score software implemented in Apache Spark and Python that accommodates a variety of data input (e.g., observed genotypes, imputed genotypes, or imputed posterior probabilities) and strand-ambiguous SNPs. We show that PRSoS is flexible and efficient and computes polygenic risk scores at a range of p-value thresholds more quickly than existing software (PRSice). We also show that the use of imputed posterior probabilities and the inclusion of strand-ambiguous SNPs increases the proportion of variance explained by polygenic risk scores for major depression.\n\nAvailability and ImplementationPRSoS is written in Apache Spark and Python and is freely available (see https://github.com/MeaneyLab/PRSoS).

bioinformatics↗