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.

Climate‐related variation of metabolic rate across the distribution of a broadly tolerant invasive forest pest - Sean D. Powers; Lily M. Thompson; Dylan Parry; Kristine L. Grayson; Eloy Martinez; Salvatore J. Agosta (Journal of Biogeography, 2024)
Aim Metabolic rate is a widely studied physiological species trait related to energetics, climate, and geographical distributions. Hypotheses have been proposed to explain variation in metabolic rate, but evidence has been mixed due to the limited sampling scope of intraspecific studies. Successful biological invasions offer a unique opportunity to examine the development of intraspecific physiological variation and how it relates to climate, invasive spread and species range limits. The aim of this study was to determine if metabolic rate variation across the spongy moth invasive range was consistent with a pattern of adaptation to local climate. Location Northeastern United States of America. Taxon Lymantria dispar dispar L. (Lepidoptera: Erebidae). Methods Larvae were sourced from 14 populations across the invasion front and interior of the current L. d. dispar invasive range and were reared at a constant temperature. Routine metabolic rates (RMR) of larvae were assayed at three ecologically relevant temperatures. These data were analysed to determine if there were differences in RMR and temperature sensitivity of RMR among populations. Population‐level variation in RMR was then analysed as a function of local climate and geographical position to test for patterns consistent with local adaptation. Results Larval RMR showed significant variation among populations across all assay temperatures, but there was no difference in temperature sensitivity (i.e. slope). This variation followed a positive latitudinal cline with RMR increasing from the southern range to the north. This cline also showed a significant relationship with local climate variables. Main Conclusions Larval metabolic rate variation was consistent with a pattern of adaptation by L. d. dispar to divergent climates across its invasive range. These results indicated that thermal adaptation of whole‐organism physiology may play a key role in promoting species spread and expansion for biological invasions like L. d. dispar .

Climate‐related geographical variation in performance traits across the invasion front of a widespread non‐native insect - Lily M. Thompson; Sean D. Powers; Ashley Appolon; Petra Hafker; Lelia Milner; Dylan Parry; Salvatore J. Agosta; Kristine L. Grayson (Journal of Biogeography, 2021)
Aim Invasive species are ideal systems for testing geographical differences in performance traits and measuring evolutionary responses as a species spreads across divergent climates and habitats. The European gypsy moth, Lymantria dispar dispar L. (Lepidoptera: Erebidae), is a generalist forest defoliator introduced to Medford, Massachusetts, USA in 1869. The invasion front extends from Minnesota to North Carolina and the ability of this species to adapt to local climate may contribute to its continuing spread. We evaluated the performance of populations along the climatic gradient of the invasion front to test for a relationship between climate and ecologically important performance traits. Location Eastern United States of America Taxon Lymantria dispar dispar L. (Lepidoptera: Erebidae) Methods Insects from 14 populations across the US invasion front and interior of the invasive range were reared from hatch to adult emergence in six constant temperature treatments. The responses of survival, pupal mass and larval development time were analysed as a function of source climate (annual mean normal temperature), rearing temperature and their interaction using multiple polynomial regression. Results With the exception of female development time, there were no significant interactions between source climate and rearing temperature, indicating little divergence in the shape of thermal reaction norms among populations. Source population and rearing temperature were significant predictors of survival and pupal mass. Independent of rearing temperature, populations from warmer climates had lower survival than those from colder climates, but attained larger body size despite similar development times. Larval development time was dependent on rearing temperature, but there were not consistent relationships with source climate. Main Conclusions Thermal adaptation can be an important factor shaping the spread of invasive species, particularly in the context of climate change. Our results suggest that L. d. dispar is highly plastic, but has undergone climate‐related adaptation in thermal performance and life‐history traits as it spread across North America.

Evolutionary genomics of gypsy moth populations sampled along a latitudinal gradient - Christopher J. Friedline; Trevor M. Faske; Brandon M. Lind; Erin M. Hobson; Dylan Parry; Rodney J. Dyer; Derek M. Johnson; Lily M. Thompson; Kristine L. Grayson; Andrew J. Eckert (Molecular Ecology, 2019)
The European gypsy moth ( Lymantria dispar L.) was first introduced to Massachusetts in 1869 and within 150 years has spread throughout eastern North America. This large‐scale invasion across a heterogeneous landscape allows examination of the genetic signatures of adaptation potentially associated with rapid geographical spread. We tested the hypothesis that spatially divergent natural selection has driven observed changes in three developmental traits that were measured in a common garden for 165 adult moths sampled from six populations across a latitudinal gradient covering the entirety of the range. We generated genotype data for 91,468 single nucleotide polymorphisms based on double digest restriction‐site associated DNA sequencing and used these data to discover genome‐wide associations for each trait, as well as to test for signatures of selection on the discovered architectures. Genetic structure across the introduced range of gypsy moth was low in magnitude ( F ST = 0.069), with signatures of bottlenecks and spatial expansion apparent in the rare portion of the allele frequency spectrum. Results from applications of Bayesian sparse linear mixed models were consistent with the presumed polygenic architectures of each trait. Further analyses indicated spatially divergent natural selection acting on larval development time and pupal mass, with the linkage disequilibrium component of this test acting as the main driver of observed patterns. The populations most important for these signals were two range‐edge populations established less than 30 generations ago. We discuss the importance of rapid polygenic adaptation to the ability of non‐native species to invade novel environments.

Can gypsy moth stand the heat? A reciprocal transplant experiment with an invasive forest pest across its southern range margin - Trevor M. Faske; Lily M. Thompson; Nana Banahene; Andi Levorse; Melisa Quiroga Herrera; Kayla Sherman; Sarah E. Timko; Banruo Yang; David R. Gray; Dylan Parry; Patrick C. Tobin; Andrew J. Eckert; et al. (Biological Invasions, 2019)

Plant defense against generalist herbivores in the forest understory: a phylogenetic comparison of native and invasive species - Elise D. Hinman; Jason D. Fridley; Dylan Parry (Biological Invasions, 2019)

Biotic resistance and the spatiotemporal distribution of an invading woodwasp, Sirex noctilio - Christopher J. Foelker; Dylan Parry; Melissa K. Fierke (Biological Invasions, 2018)

All quiet on the western front? Using phenological inference to detect the presence of a latent gypsy moth invasion in Northern Minnesota - Patrick C. Tobin; Kimberly Thielen Cremers; Lucia Hunt; Dylan Parry (Biological Invasions, 2016)

Beyond Pandora’s Box: quantitatively evaluating non-target effects of parasitoids in classical biological control - Dylan Parry (Biological Invasions, 2009)

Repeated insect defoliation effects on growth, nitrogen acquisition, carbohydrates, and root demography of poplars - Kevin R. Kosola; Donald I. Dickmann; Eldor A. Paul; Dylan Parry (Oecologia, 2001)