Analysis of second-generation epigenetic clocks reveals further associations between disproportionate biological ageing and hippocampal volume - Lidija Milicic; Michael Vacher; Vincent Doré; Pierrick Bourgeat; Rosita Shishegar; James D. Doecke; Paul Maruff; Christopher C. Rowe; Victor L. Villemagne; Michael Weiner; Paul Aisen; Ronald Petersen; et al. (GeroScience, 2026)

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.

Beyond strength: dietary nitrate augments self-selected functional mobility after resistance training in middle-aged adults - Brandon M. Peoples; Mason C. McIntosh; Kenneth D. Harrison; Bria R. Smith; Keven G. Santamaria Guzman; Silvia E. Campos-Vargas; Damaris C. Cifuentes; Breanna J. Mueller; Andreas N. Kavazis; Darren T. Beck; Michael D. Roberts; Jaimie A. Roper (GeroScience, 2025)
This study aimed to assess whether dietary nitrate supplementation with resistance training (RT) augments gait performance and functional mobility in inactive middle-aged and older adults. We hypothesized that combining nitrate-rich beetroot juice (BRJ) with RT would yield improvements in gait and functional mobility compared to RT with nitrate-depleted beetroot juice placebo (PLA) supplementation. In this 12-week, randomized, double-blind, placebo-controlled pilot trial, 28 healthy, inactive adults (56 ± 7 years) were assigned to either a BRJ (~ 12.8 mmol nitrate/day) or PLA group while completing a supervised, full-body RT program (2×/week). Pre- and post-intervention assessments included the instrumented stand and walk (iSAW), 6-min walk test (i6MWT), and timed up and go (iTUG) tests. Supplement adherence, training compliance, and volume were equivalent between groups. ANCOVA analyses controlling baseline values revealed significant between-group differences favoring the BRJ group for gait speed (adjusted means: 1.38 vs 1.27 m/s, p = .010), stride length ( p < .001), and iTUG duration ( p < .05). Within-group analyses confirmed that the BRJ group experienced significant improvements in gait speed ( p < 0.001) and iTUG duration ( p < 0.05), while the PLA group showed no functional changes, indicating that 12 weeks of RT alone was insufficient to improve functional mobility in our sample despite equivalent training responses ( p > .05). In our middle-aged sample, supplementing dietary nitrate alongside RT led to clinically meaningful improvements in functional mobility during self-selected conditions, exceeding the gains from 12 weeks of twice-weekly RT alone. Preliminary descriptive analyses revealed sex-specific group-level differences that might suggest emerging trends. Although no inferential statistics were conducted, the patterns provide potential directions for future research investigating the effects of RT in middle-aged adults. Graphical Abstract

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.

Life-history guilds of fishes associated with estuaries: opportunism versus dependency - Alan K. Whitfield; Kenneth W. Able; Mario Barletta; Stephen J.M. Blaber; Trevor D. Harrison (Estuarine, Coastal and Shelf Science, 2023)

Quantifying spatial extents of artificial versus natural reefs in the seascape - D’amy N. Steward; Avery B. Paxton; Nathan M. Bacheler; Christina M. Schobernd; Keith Mille; Jeffrey Renchen; Zach Harrison; Jordan Byrum; Robert Martore; Cameron Brinton; Kenneth L. Riley; J. Christopher Taylor; et al. (Frontiers in Marine Science, 2022)
With increasing human uses of the ocean, existing seascapes containing natural habitats, such as biogenic reefs or plant-dominated systems, are supplemented by novel, human-made habitats ranging from artificial reefs to energy extraction infrastructure and shoreline installments. Despite the mixture of natural and artificial habitats across seascapes, the distribution and extent of these two types of structured habitats are not well understood but are necessary pieces of information for ocean planning and resource management decisions. Through a case study, we quantified the amount of seafloor in the southeastern US (SEUS; 103,220 km 2 in the Atlantic Ocean; 10 – 200 m depth) covered by artificial reefs and natural reefs. We developed multiple data-driven approaches to quantify the extent of artificial reefs within state-managed artificial reef programs, and then drew from seafloor maps and published geological and predictive seafloor habitat models to develop three estimates of natural reef extent. Comparisons of the extent of natural and artificial reefs revealed that artificial reefs account for substantially less habitat (average of two estimates 3 km 2 ; <0.01% of SEUS) in the region than natural reefs (average of three estimates 2,654 km 2 ; 2.57% of SEUS) and that this pattern holds across finer regional groupings (e.g., states, depth bins). Our overall estimates suggest that artificial reef coverage is several orders of magnitude less than natural reef coverage. While expansive seafloor mapping and characterization efforts are still needed in SEUS waters, our results fill information gaps regarding the extent of artificial and natural reef habitats in the region, providing support for ecosystem-based management, and demonstrating an approach applicable to other regions.

Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume - Lidija Milicic; Michael Vacher; Tenielle Porter; Vincent Doré; Samantha C. Burnham; Pierrick Bourgeat; Rosita Shishegar; James Doecke; Nicola J. Armstrong; Rick Tankard; Paul Maruff; Colin L. Masters; et al. (GeroScience, 2022)
The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes.

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity - Chiara Fallerini; Nicola Picchiotti; Margherita Baldassarri; Kristina Zguro; Sergio Daga; Francesca Fava; Elisa Benetti; Sara Amitrano; Mirella Bruttini; Maria Palmieri; Susanna Croci; Mirjam Lista; et al. (Human Genetics, 2022)
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.

The global abundance of tree palms - Robert Muscarella; Thaise Emilio; Oliver L. Phillips; Simon L. Lewis; Ferry Slik; William J. Baker; Thomas L. P. Couvreur; Wolf L. Eiserhardt; Jens‐Christian Svenning; Kofi Affum‐Baffoe; Shin‐Ichiro Aiba; Everton C. de Almeida; et al. (Global Ecology and Biogeography, 2020)
Aim Palms are an iconic, diverse and often abundant component of tropical ecosystems that provide many ecosystem services. Being monocots, tree palms are evolutionarily, morphologically and physiologically distinct from other trees, and these differences have important consequences for ecosystem services (e.g., carbon sequestration and storage) and in terms of responses to climate change. We quantified global patterns of tree palm relative abundance to help improve understanding of tropical forests and reduce uncertainty about these ecosystems under climate change. Location Tropical and subtropical moist forests. Time period Current. Major taxa studied Palms (Arecaceae). Methods We assembled a pantropical dataset of 2,548 forest plots (covering 1,191 ha) and quantified tree palm (i.e., ≥10 cm diameter at breast height) abundance relative to co‐occurring non‐palm trees. We compared the relative abundance of tree palms across biogeographical realms and tested for associations with palaeoclimate stability, current climate, edaphic conditions and metrics of forest structure. Results On average, the relative abundance of tree palms was more than five times larger between Neotropical locations and other biogeographical realms. Tree palms were absent in most locations outside the Neotropics but present in >80% of Neotropical locations. The relative abundance of tree palms was more strongly associated with local conditions (e.g., higher mean annual precipitation, lower soil fertility, shallower water table and lower plot mean wood density) than metrics of long‐term climate stability. Life‐form diversity also influenced the patterns; palm assemblages outside the Neotropics comprise many non‐tree (e.g., climbing) palms. Finally, we show that tree palms can influence estimates of above‐ground biomass, but the magnitude and direction of the effect require additional work. Conclusions Tree palms are not only quintessentially tropical, but they are also overwhelmingly Neotropical. Future work to understand the contributions of tree palms to biomass estimates and carbon cycling will be particularly crucial in Neotropical forests.

TRY plant trait database – enhanced coverage and open access - Jens Kattge; Gerhard Bönisch; Sandra Díaz; Sandra Lavorel; Iain Colin Prentice; Paul Leadley; Susanne Tautenhahn; Gijsbert D. A. Werner; Tuomas Aakala; Mehdi Abedi; Alicia T. R. Acosta; George C. Adamidis; et al. (Global Change Biology, 2020)
Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Correction to: Genetic variant predictors of gene expression provide new insight into risk of colorectal cancer - Stephanie A. Bien; Yu-Ru Su; David V. Conti; Tabitha A. Harrison; Conghui Qu; Xingyi Guo; Yingchang Lu; Demetrius Albanes; Paul L. Auer; Barbara L. Banbury; Sonja I. Berndt; Stéphane Bézieau; et al. (Human Genetics, 2019)

Genetic variant predictors of gene expression provide new insight into risk of colorectal cancer - Stephanie A. Bien; Yu-Ru Su; David V. Conti; Tabitha A. Harrison; Conghui Qu; Xingyi Guo; Yingchang Lu; Demetrius Albanes; Paul L. Auer; Barbara L. Banbury; Sonja I. Berndt; Stéphane Bézieau; et al. (Human Genetics, 2019)

Pacific Rim Forestry / Silviculture and Forest Ecology - Vishal Singh Negi; Archana Pal; Ratnesh Singh; Dulal Borthakur; Archana Pala; Vishal Singh Negi; Dulal Borthakur; Isabel Rushanaedy; Tyler Jones; Nicklos Dudley; Dulal Borthakur; Jannai Yafuso; et al. (Journal of Forestry, 2011)
Leucaena leucocephala (leucaena) is an important agroforestry tree of tropics and subtropics due to its protein rich foliages, ability to grow on poor soils, and high level of tolerance to various stresses including drought and diseases. We hypothesized that leucaena have a unique set of genes which confer tolerance to various abiotic and biotic stresses and these genes are either absent or not expressed in other legumes that are susceptible to these stress conditions. Interspecies suppression subtractive hybridization (iSSH) was performed to identify some unique genes from leucaena using cDNAs from leucaena and Acacia confusa (acacia) as the tester and driver, respectively. We identified 100 leucaena genes showing homology to various plant genes with known functions, of which 23 genes had homology to various stress-related proteins including chitinase, PR-10 protein, wound-stress protein, type-2 metallothionein, thaumatin-like protein, disease resistance response protein, cysteine proteinase, and kunitz trypsin inhibitor. We also identified 50 leucaena genes which either had homology to hypothetical proteins (HyPs) or had no homology at all. Putative functions of 15 HyPs were predicted using conserved domain and PSI-BLAST analyses. Linear motif analyses identified 17 HyPs with MAPK recognition motif, which is involved in signaling pathways, including stress responses. This study identified 23 known and some putative unique stress-related genes from leucaena which may serve as a useful source of stress-tolerance genes for tree and crop improvement in the future.

Symbiosis research, technology, and education: Proceedings of the 6th International Symbiosis Society Congress held in Madison Wisconsin, USA, August 2009 - Heidi Goodrich-Blair; Jean-Michel Ané; James D. Bever; Seth R. Bordenstein; Monika Bright; John M. Chaston; Keith Clay; Cameron R. Currie; Angela E. Douglas; Nicole Gerardo; Maria J. Harrison; Ruth E. Ley; et al. (Symbiosis, 2010)