Biology subjects

Benitez, A.

Publications and source records attributed to Benitez, A..

6 recordsLinked to original sources

bioRxiv2026

Greater Amyloid Burden in Cognitive Networks in Preclinical Alzheimer's Disease

BackgroundIn preclinical Alzheimers disease (pAD), regional patterns of amyloid-{beta} (A{beta}) deposition are well characterized but it is unclear how this process varies across functional networks. ObjectiveDetermine how A{beta} accumulation in functional networks ("network-amyloid burden" [NAB]) varies by age, network type (cognitive vs. non-cognitive), and A{beta} status (A{beta}+/A{beta}-), and relates to cognition. Methods157 cognitively unimpaired adults (45-84 years; n=28 A{beta}+ per neuroradiological read) underwent brain MRI, amyloid PET (18F-florbetapir), and neuropsychological testing. NAB was calculated as the mean standard uptake value ratio within 7 networks categorized as cognitive (fronto-parietal, default mode, ventral and dorsal attention, limbic) or non-cognitive (somato-motor, visual). Linear mixed models tested how NAB varies across age, networks (by type and each separately), A{beta} status, and their interactions, and relationships between NAB and cognition. ResultsNAB increased with age, most prominently in fronto-parietal and default mode networks. NAB was higher in cognitive than non-cognitive networks, and this difference was more pronounced in A{beta}+ individuals. NAB was not significantly associated with cognition. ConclusionsCognitive brain networks are more vulnerable to amyloid accumulation with aging and in pAD than non-cognitive networks. Cognitive NAB may be useful for early detection and as a target for intervention in pAD.

neuroscience↗

bioRxiv2025

Calibration of MRI-based reference intervals to new samples

Reference intervals, defined as intervals containing a new observation with a specified probability relative to reference data, would be clinically useful in assessing brain magnetic resonance imaging (MRI). Brain charts, which are estimates of MRI phenotypes across covariates such as age and sex, can be used to construct reference intervals. However, the reference data used to fit intervals often differs from a new sample in terms of study design, MRI acquisition, and image preprocessing. Application of MRI reference intervals to new samples remains a challenging problem. Here, we propose a new method called Reference interval calibration via conFormal prediction (ReForm) that adjusts reference intervals for a new sample. Our method builds on recent work in conformal prediction, which yields intervals with guaranteed coverage for new observations. Through resampling experiments in Lifespan Brain Chart Consortium cortical thickness data, we compare ReFormed reference intervals to refitting intervals, statistical harmonization methods, and model-based adjustment of intervals. Notably for patient privacy concerns, ReForm does not require sharing of reference data. Yet, our empirical results demonstrate that ReForm controls FPR similarly or better than alternative methods which require sharing reference data. Finally, we provide recommendations for practical applications of ReForm and an R package (https://github.com/andy1764/ReForm) for calibrating reference intervals using ReForm.

neuroscience↗

bioRxiv2025

ComBat-Predict enhances generalizability of neuroimaging models to new sites

Neuroimaging is vital in quantifying brain atrophy due to typical aging and due to neurodegenerative diseases. To collect large samples necessary to model lifespan brain development, research consortiums aggregate images acquired across multiple study sites. Previous studies have demonstrated that this multi-site study design can lead to site-related bias, necessitating harmonization of these "site effects". However, current methodologies are unable to generalize to new sites outside the original harmonized sample, limiting translation to new sites or clinical practice. Here, we propose a method called ComBat-Predict (CB-Predict) building upon the ComBat method for site effect adjustment, which extends to data from a new site with smaller sample sizes and unknown site effects. In data from the Alzheimers Disease Neuroimaging Initiative (ADNI), our proposed method mitigates bias and yields high accuracy in predicting cortical thickness measures when generalizing the model to new data. Furthermore, we demonstrate that our proposed harmonization method can reduce site-related variance in centile scores estimated using data from the Lifespan Brain Chart Consortium (LBCC). Altogether, our results demonstrate that CB-Predict effectively harmonizes new sites and thereby enables effective translation of neuroimaging models to additional samples.

neuroscience↗

bioRxiv2021

PyDesigner: A Pythonic Implementation of the DESIGNER Pipeline for Diffusion Tensor and Diffusional Kurtosis Imaging

PyDesigner is an open-source and containerized Python software package, adapted from the DESIGNER pipeline, for diffusion weighted magnetic resonance imaging preprocessing and tensor estimation. PyDesigner combines tools from FSL and MRtrix3 to reduce the effects of signal noise and imaging artifacts on multiple diffusion measures that can be derived from the diffusion and kurtosis tensors. This publication describes the main features of PyDesigner and highlights its ease of use across platforms, while examining its accuracy and robustness in deriving commonly used diffusion and kurtosis metrics.

neuroscience↗

bioRxiv2021

Integrated Genome and Transcriptome Analyses Reveal the Mechanism of Genome Instability in Ataxia with Oculomotor Apraxia 2

Mutations in the SETX gene, which encodes Senataxin, are associated with the progressive neurodegenerative diseases Ataxia with Oculomotor Apraxia 2 (AOA2) and Amyotrophic Lateral Sclerosis 4 (ALS4). To identify the causal defect in AOA2, patient-derived cells and SETX knockouts (human and mouse) were analyzed using integrated genomic and transcriptomic approaches. We observed a genome-wide increase in chromosome instability (gains and losses) within genes and at chromosome fragile sites, resulting in changes to gene expression profiles. Senataxin loss caused increased transcription stress near promoters that correlated with high GCskew and R-loop accumulation at promoter-proximal regions. Notably, the chromosomal regions with gains and losses overlapped with regions of elevated transcription stress. In the absence of Senataxin, we found that Cockayne Syndrome protein CSB was required for the recruitment of the transcription-coupled repair endonucleases (XPG and XPF) and recombination protein RAD52 to target and resolve transcription bubbles containing R-loops, leading to error prone repair and genomic instability. These results show that transcription stress is an important contributor to SETX mutation-associated chromosome fragility and AOA2.

molecular biology↗

bioRxiv2019

Genetic variation of Aedes aegypti populations from Ecuador

This is the first genetic analysis in Ecuador of Aedes aegypti using fragments of mitochondrial genes, NADH dehydrogenase subunit 4 (ND4) and cytochrome oxidase subunit I (COI). A total of 154 mosquitoes from 23 localities were collected in the Pacific coastal lowlands, Amazon basin lowlands, and the Galapagos Islands from 2012 to 2019. The analysis of fragments of the genes COI (672 bp) and ND4 (262 bp) and concatenated analysis of both COI and ND4 showed two haplotypes (H1, H2) present in Ecuador mainland and the Galapagos Islands. The phylogenetic analysis identified two well-supported clades. Combined analysis of both genes from ten localities also resulted in two haplotypes. Nucleotide diversity, neutrality tests (Tajimas test D, Fu and Lis F*and D*) and AMOVA analysis of the entire data set suggest balancing selection for both genes. The results indicate genetic variation without geographical restriction. COI-H1 grouped with sequences from the Americas, West and Central Africa, East Africa, Asia, and Australia. ND4-H1 grouped with similar sequences from the Americas, Asia and West Africa. COI-H2 grouped with sequences from Asia and the Americas. ND4-H2 grouped with sequences from the Americas. We report overlapping peaks in four sequences that suggest heteroplasmy in the individuals. The origin of the populations of Aedes aegypti in Ecuador show African genetic origin and are widely present in several countries in the Americas. One of the genetic variants is more common in all the localities and the two haplotypes are distributed indistinctly in the three geographical sampled areas in Ecuador.

genetics↗