Interpretable deep learning reveals spatiotemporal MRI features of brain aging that align with neurodegeneration - Nikhil N. Chaudhari; Owen M. Vega; Phoebe Imms; Jaron M. Kawamura; Nahian F. Chowdhury; Tamara Jafar; Andrei Irimia; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; et al. (GeroScience, 2026)
Cortical thinning and atrophy are hallmarks of brain aging that have been characterized using magnetic resonance imaging (MRI). Brain aging involves many neuroanatomic features whose effects on brain structure remain unexplored. To address this challenge, we trained interpretable deep neural networks (DNNs) to estimate brain age (BA) from T 1 -weighted ( T 1 w) MRI. By identifying MRI features unapparent to humans, DNNs can find aging-related structural alterations above and beyond cortical thickness and atrophy. Using a novel approach to DNN interpretability, we mapped brain aging progression in 25,539 cognitively normal UK Biobank adults aged 45–83 years. Cortical aging is found to involve anatomic features becoming prominent during the 50s within frontolateral, mesolimbic, cuneal, and occipitotemporal regions. From these foci, aging-related features propagate to adjacent areas at rates peaking in the 60s. Cortical thinning and atrophy do not trend closely with neurodegeneration, but important DNN-identifiable anatomic features have spatiotemporal dynamics that match those of amyloid or tau. Our results challenge the assumption that MRI cannot map anatomic features trending with neurodegeneration. Interpretable DNNs can empower MRI to quantify anatomic aging as a process of spatial feature expansion from focal regions into nearby structures in the sequence of neurodegenerative pathology. Traditional morphometrics explain only ∼1% of variance in DNN-identifiable features, which clarifies why the former are insensitive to anatomic changes involving neurodegeneration. Our results conceptualize brain aging in the context of spatial and temporal parallels between anatomic senescence and neuropathology. These findings may help to map cognitively normal adults’ neurodegenerative anatomy even without PET measurements. Graphical Abstract

Sex and APOE genotype specific brain regional vulnerability to Alzheimer's Disease - Qi Zeng; Minghui Wang; Erming Wang; Xianxiao Zhou; Peng Xu; Vahram Haroutunian; Dongming Cai; Bin Zhang; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; et al. (GeroScience, 2026)
Alzheimer’s disease (AD) disproportionately affects women and carriers of the apolipoprotein E ε4 allele (APOE4), yet little is known about how sex and APOE interact to influence white matter (WM) integrity during disease progression. We integrated diffusion MRI and matched blood transcriptomic data to investigate these interactions and their underlying biological mechanisms. WM microstructure was quantified using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI), and regional vulnerability was assessed with a composite vulnerability score (CVS) derived from associations between diffusion features and AD severity across clinical traits in each of the four sex-APOE groups (female or male, with or without APOE4). Brain parcellation with the Eve atlas revealed regions consistently affected across sex-APOE groups (e.g., parahippocampal and superior temporal gyri) and regions specific to individual groups (e.g., the cingulum in females with APOE4 and the middle frontal gyrus in males without APOE4). Gene co-expression network analysis of the matched blood expression data identified gene subnetworks linked to group-specific regional vulnerability, including a muscle tissue morphogenesis module regulated by NEURL1B and HIST1H2BN associated with middle frontal gyrus vulnerability. These findings demonstrate that sex and APOE genotype jointly shape region-specific WM vulnerability and its molecular signatures in AD. Understanding these interactions provides novel mechanistic insights and may inform precision approaches to drug development, biomarker discovery, and clinical trial design for AD.

Predicting the progression of MCI and Alzheimer’s disease on structural brain integrity and other features with machine learning - Marthe Mieling; Mushfa Yousuf; Nico Bunzeck; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; Susan Landau; Monica Rivera-Mindt; Leslie M. Shaw; Edward B. Lee; et al. (GeroScience, 2025)
Machine learning (ML) on structural MRI data shows high potential for classifying Alzheimer’s disease (AD) progression, but the specific contribution of brain regions, demographics, and proteinopathy remains unclear. Using Alzheimer’s Disease Neuroimaging Initiative (ADNI) data, we applied an extreme gradient-boosting algorithm and SHAP (SHapley Additive exPlanations) values to classify cognitively normal (CN) older adults, those with mild cognitive impairment (MCI) and AD dementia patients. Features included structural MRI, CSF status, demographics, and genetic data. Analyses comprised one cross-sectional multi-class classification (CN vs. MCI vs. AD dementia, n = 568) and two longitudinal binary-class classifications (CN-to-MCI converters vs. CN stable, n = 92; MCI-to-AD converters vs. MCI stable, n = 378). All classifications achieved 70–77% accuracy and 61–83% precision. Key features were CSF status, hippocampal volume, entorhinal thickness, and amygdala volume, with a clear dissociation: hippocampal properties contributed to the conversion to MCI, while the entorhinal cortex characterized the conversion to AD dementia. The findings highlight explainable, trajectory-specific insights into AD progression.

Antimicrobial activity of the Flo peptide produced in Scenedesmus acutus and Nannochloropsis oculata - Saraí Damaris Dávalos-Guzmán; Fidel Martinez-Gutierrez; Luzmila Martínez-González; Jesús Josafath Quezada-Rivera; Ana Cecilia Lorenzo-Leal; Horacio Bach; José Francisco Morales-Domínguez; Ruth Elena Soria-Guerra (World Journal of Microbiology and Biotechnology, 2023)

Ligand-based virtual screening, molecular docking, and molecular dynamics of eugenol analogs as potential acetylcholinesterase inhibitors with biological activity against Spodoptera frugiperda - Domingo Méndez-Álvarez; Verónica Herrera-Mayorga; Alfredo Juárez-Saldivar; Alma D. Paz-González; Eyra Ortiz-Pérez; Debasish Bandyopadhyay; Horacio Pérez-Sánchez; Gildardo Rivera (Molecular Diversity, 2022)

Being Isolated and Protected Is Better Than Just Being Isolated: A Case Study From the Alacranes Reef, Mexico - Fabio Favoretto; Ismael Mascareñas-Osorio; Lorena León-Deniz; Carlos González-Salas; Horacio Pérez-España; Mariana Rivera-Higueras; Miguel-Ángel Ruiz-Zárate; Alejandro Vega-Zepeda; Harold Villegas-Hernández; Octavio Aburto-Oropeza (Frontiers in Marine Science, 2020)

Williams–Beuren syndrome in Mexican patients confirmed by FISH and assessed by aCGH - Azubel Ramírez-Velazco; Thania Alejandra Aguayo-Orozco; Luis Figuera; Horacio Rivera; Luis Jave-Suárez; Adriana Aguilar-Lemarroy; Luis A. Torres-Reyes; Carlos Córdova-Fletes; Patricio Barros-Núñez; Saturnino Delgadillo-Pérez; Ingrid Patricia Dávalos-Rodríguez; José Elías García-Ortiz; et al. (Journal of Genetics, 2019)

Evolutionary Analysis of Pectin Lyases of the Genus Colletotrichum - Alicia Lara-Márquez; Ken Oyama; María G. Zavala-Páramo; Maria G. Villa-Rivera; Ulises Conejo-Saucedo; Horacio Cano-Camacho (Journal of Molecular Evolution, 2017)

Protein homology modeling, docking, and phylogenetic analyses of an endo-1,4-β-xylanase GH11 of Colletotrichum lindemuthianum - Ulises Conejo-Saucedo; Horacio Cano-Camacho; Maria G. Villa-Rivera; Alicia Lara-Márquez; Everardo López-Romero; María G. Zavala-Páramo (Mycological Progress, 2017)

Two further triple-X/rea(X) females in an inv(X)(p22q22) family - HORACIO RIVERA; ANA I. VÁSQUEZ-VELÁSQUEZ; MARIA G. DOMÍNGUEZ-QUEZADA; AZUBEL RAMÍREZ-VELAZCO (Journal of Genetics, 2016)

De novo dir dup/del of 18q characterized by SNP arrays and FISH in a girl child with mixed phenotypes - CARLOS CÓRDOVA-FLETES; ENRIQUE SÁINZ-GONZÁLEZ; ROBERTO IVÁN AVENDAÑO-GÁLVEZ; AZUBEL RAMÍREZ-VELAZCO; HORACIO RIVERA; ROCÍO ORTIZ-LÓPEZ; ELIAKYM ARÁMBULA-MERAZ; VERÓNICA JUDITH PICOS-CÁRDENAS (Journal of Genetics, 2014)

Concurrent psu dic(21)(q22.3) and t(13;17)(q14.1;p12) in a mosaic Down’s syndrome patient: review of thirty-one similar dicentrics - HORACIO RIVERA; ANA I. VÁSQUEZ-VELÁSQUEZ (Journal of Genetics, 2014)

Erratum to: Cell Culture Protection and in vivo Neuroprotective Capacity of Flavonoids - Federico Dajas; Felicia Rivera; Fernanda Blasina; Florencia Arredondo; Carolina Echeverry; Laura Lafon; Andrea Morquio; Horacio Heinzen (Neurotoxicity Research, 2013)

De novo inv(17)(p11.2q21.3) in an intellectually disabled girl: appraisal of 21 inv(17) constitutional instances - MIRIAM PARTIDA-PÉREZ; MARÍA G. DOMÍNGUEZ; VIVIAN ALEJANDRA NEIRA; LUIS E. FIGUERA; HORACIO RIVERA (Journal of Genetics, 2012)

Familial whole-arm translocations (1;19), (9;13), and (12;21): a review of 101 constitutional exchanges - Alejandra Vázquez-Cárdenas; Ana I. Vásquez-Velásquez; Patricio Barros-Núñez; Johana Mantilla-Capacho; Mariano Rocchi; Horacio Rivera (Journal of Applied Genetics, 2007)

A 9p13→p24 duplication coupled with a whole 22q translocation onto 9p24 - Horacio Rivera; Ana I. Vásquez-Velásquez; María de Lourdes Ramírez-Dueńas; Luis Eduardo Becerra-Solano (Journal of Applied Genetics, 2007)

Cell culture protection andin vivo neuroprotective capacity of flavonoids - Federico Dajas; Felicia Rivera; Fernanda Blasina; Florencia Arredondo; Carolina Echeverry; Laura Lafon; Andrea Morquio; Horacio Heizen (Neurotoxicity Research, 2003)

Chromosome 9qh inversions may not be true inversions - Horacio Rivera; Melva Gutiérrez-Angulo; Juan Ramón González-Garcia (Human Genetics, 1999)