Biology subjects

Valero, S.

Publications and source records attributed to Valero, S..

4 recordsLinked to original sources

bioRxiv2024

Contextual Neural Dynamics During Time Perception in Primate Ventral Premotor Cortex

Understanding how time perception adapts to cognitive demands remains a significant challenge. In some contexts, the brain encodes time categorically (as "long" or "short"), while in others, it encodes precise time intervals on a continuous scale. Although the ventral premotor cortex (VPC) is known for its role in complex temporal processes, such as speech, its specific involvement in time estimation remains underexplored. In this study, we investigated how the VPC processes temporal information during a time interval comparison task (TICT) and a time interval categorization task (TCT) in primates. We found a notable heterogeneity in neuronal responses associated with time perception across both tasks. While most neurons responded during time interval presentation, a smaller subset retained this information during the working memory periods. Population-level analysis revealed distinct dynamics between tasks: in TICT, population activity exhibited a linear and parametric relationship with interval duration, whereas in TCT, neuronal activity diverged into two distinct dynamics corresponding to the interval categories. During delay periods, these categorical or parametric representations remained consistent within each task context. This contextual shift underscores the VPCs adaptive role in interval estimation and highlights how temporal representations are modulated by cognitive demands. Significance StatementThe neural representation of time has long intrigued neuroscientists, particularly how it adapts to cognitive demands. Depending on the task, the brain encodes time either categorically ("long" or "short") or as precise intervals. While the ventral premotor cortex (VPC) is known for its role in temporal processes, its role in time estimation remains underexplored. Here, we examined how the VPC processes temporal information in primates during a time interval comparison task (TICT) and a categorization task (TCT). The VPC exhibited heterogeneous neuronal responses with distinct dynamics: a linear, parametric relationship in TICT and bifurcated dynamics in TCT. These representations remained consistent during delay periods, underscoring the VPCs adaptive role in time interval estimation.

neuroscience↗

bioRxiv2020

Autosomal Recessive Alzheimer disease (arAD): homozygosity mapping of genomic regions containing arAD loci

Long runs of homozygosity (ROH) are contiguous stretches of homozygous genotypes, which are a footprint of recent inbreeding and recessive inheritance. The presence of recessive loci is suggested for Alzheimers disease (AD). However, the search for recessive variants has been poorly assessed to date. To investigate homozygosity in AD, we performed a fine-scale ROH analysis including 21,100 individuals from 10 cohorts of European ancestry (11,919 AD cases and 9,181 controls). We detected an increase of homozygosity in AD cases compared to controls [{beta}FROH (CI95%) = 0.051 (0.023 - 0.078); P = 3.25 x 10-4]. ROHs increasing the risk of AD (OR > 1) were significantly overrepresented compared to ROHs increasing protection (p < 2.20 x 10-16). The top associated ROH with AD risk ({beta} (CI95%) = 1.09 (0.48 - 1.48), p value = 9.03 x 10-4) was detected upstream the HS3ST1 locus (chr4:11,189,482-11,305,456), previously related to AD. Next, to construct a homozygosity map of AD cases, we selected ROHs shared by inbred AD cases extracted from an outbred population. We used whole-exome sequencing data from 1,449 individuals from the Knight-ADRC-NIA-LOAD (KANL) cohort to identify potential recessive variants in candidate ROHs. We detected a candidate marker, rs117458494, mapped in the SPON1 locus, which has been previously associated with amyloid metabolism. Here, we provide a research framework to look for recessive variants in AD using outbred populations. Our results showed that AD cases have enriched homozygosity, suggesting that recessive effects may explain a proportion of AD heritability.

genetics↗

bioRxiv2019

Genome-wide association analysis of dementia and its clinical endophenotypes reveal novel loci associated with Alzheimer disease and three causality networks of AD: the GR@ACE project.

BackgroundGenetics plays a major role in Alzheimers Disease (AD). To date, 40 genes associated with AD have been identified, although most remain undiscovered. Clinical, neuropathological and genetic variability might impact genetic discoveries and complicate dissection of the biological pathways underlying AD. MethodsGR@ACE is a genome-wide study of dementia and its clinical endophenotypes that encompasses 4,120 cases and 3,289 controls from Spain. GR@ACE phenotypes were defined according to ADs clinical certainty and the presence of vascular co-morbidity. To explore whether clinical endophenotypes reflect variation in underlying biological pathways, we first assessed the impact of known AD loci across endophenotypes to generate three loci categories. Next, we incorporated gene co-expression data and conducted pathway analysis on each category. To assess the impact of heterogeneity in the GWAS findings, the GR@ACE series were meta-analyzed with: 1) genotype-level data from dbGaP (N=21,235); and 2) summary statistics from IGAP Stages I and II (n=61,571 and n=81,455 respectively). FindingsWe classified known AD loci in three categories, which might reflect the disease clinical heterogeneity, from vascular and mixed forms to pure AD pathology. Immune system pathways were detected in all categories. Intriguingly, vascular processes were only detected as a causal mechanism in probable AD. A meta-analysis of GR@ACE with additional GWAS datasets revealed the ANKRD31-rs4704171 signal in the HMGCR genomic region. We confirmed NDUFAF6-rs10098778 and SCIMP-rs7225151, which were previously detected by IGAP, to be suggestive signals. We also confirmed CD33-rs3865444 to be genome-wide significant. InterpretationThe regulation of vasculature is a prominent causal component of probable AD. In that context, cerebral amyloid angiopathy, the unique identified link between the vascular and amyloid hypotheses, deserves further investigation. The GR@ACE meta-analysis revealed novel AD genetic signals. GWAS results are strongly driven by the presence of clinical heterogeneity in the AD series. FundingGrifols SA, Fundacion bancaria "La Caixa", Fundacio ACE and ISCIII (Instituto de Salud Carlos III).

neuroscience↗

bioRxiv2018

Genome Wide Meta-Analysis identifies new loci associated with cardiac phenotypes and uncovers a common genetic signature shared by heart function and Alzheimer’s disease

AimsEchocardiography has become an indispensable tool for the study of heart performance, improving the monitoring of individuals with cardiac diseases. Diverse genetic factors associated with echocardiographic measures of heart structure and functions have been previously reported. The impact of several apoptotic genes in heart development identified in experimental models prompted us to assess their potential association with indicators of human cardiac function. This study started with the aim to investigate the possible association of variants of apoptotic genes with echocardiographic traits and to identify new genetic markers associated with cardiac function.\n\nMethods and resultsGenome wide data from different studies were obtained from public repositories. After quality control and imputation, association analyses confirm the role of caspases and other apoptosis related genes with cardiac phenotypes. Moreover, enrichment analysis showed an over-representation of genes, including some apoptotic regulators, associated with Alzheimers disease (AD). We further explored this unexpected observation which was confirmed by genetic correlation analyses.\n\nConclusionsOur findings show the association of apoptotic gene variants with echocardiographic indicators of heart function and reveal a novel potential genetic link between echocardiographic measures in healthy populations and cognitive decline later on in life. These findings may have important implications for preventative strategies combating Alzheimers disease.

genetics↗