Regional impact assessment of air quality improvement: The air quality lifecourse assessment tool (AQ-LAT) for the West Midlands combined authority (WMCA).

Poor air quality is the largest environmental health risk in England. In the West Midlands, UK, ∼2.9 million people are affected by air pollution with an average loss in life expectancy of up to 6 months. The 2021 Environment Act established a legal framework for local authorities in England to develop regional air quality plans, generating a policy need for predictive environmental impact assessment tools. In this context, we developed a novel Air Quality Lifecourse Assessment Tool (AQ-LAT) to estimate electoral ward-level impacts of PM2.5 and NO2 exposure on outcomes of interest to local authorities, namely morbidity (asthma, coronary heart disease (CHD), stroke, lung cancer), mortality, and associated healthcare costs. We apply the Tool to assess the health economic burden of air pollutant exposure and estimate benefits that would be generated by meeting WHO 2021 Global Air Quality Guidelines (AQGs) (annual average concentrations) for NO2 (10 µg/m3) and PM2.5 (5 µg/m3) in the West Midlands Combined Authority Area. All West Midlands residents live in areas which exceed WHO AQGs, with 2070 deaths, 2070 asthma diagnoses, 770 CHD diagnoses, 170 lung cancers and 650 strokes attributable to air pollution exposure annually. Reducing PM2.5 and NO2 concentrations to WHO AQGs would save 10,700 lives reducing regional mortality by 1.8%, gaining 92,000 quality-adjusted life years (QALYs), and preventing 20,500 asthma, 7400 CHD, 1400 lung cancer, and 5700 stroke diagnoses, with economic benefits of £3.2 billion over 20 years. Significantly, we estimate 30% of QALY gains relate to reduced disease burden. The AQ-LAT has major potential to be replicated across local authorities in England and applied to inform regional investment decisions.

Issues, Challenges and Opportunities for Economic Evaluations of Orphan Drugs in Rare Diseases: An Umbrella Review.

BACKGROUND AND OBJECTIVES: There are significant challenges when obtaining clinical and economic evidence for health technology assessments of rare diseases. Many of them have been highlighted in previous systematic reviews but they have not been summarised in a comprehensive manner. For all stakeholders working with rare diseases, it is important to be aware and understand these issues. The objective of this review is to identify the main challenges for the economic evaluation of orphan drugs in rare diseases. METHODS: An umbrella review of systematic reviews of economic studies concerned with orphan and ultra-orphan drugs was conducted. Studies that were not systematic reviews, or on advanced therapeutic medicinal products, personalised medicines or other interventions that were not considered orphan drugs were excluded. The database searches included publications from 2010 to 2023, and were conducted in MEDLINE, EMBASE and the Cochrane library using filters for systematic reviews, and economic evaluations and models. These filters were combined with search terms for rare diseases and orphan drugs. A hand search supplemented the literature searches. The findings were reported by a compliant Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram. RESULTS: Two hundred and eighty-two records were identified from the literature searches, of which 64 were duplicates, whereas five reviews were identified from the hand search. A total of 36 reviews were included after screening against inclusion/exclusion criteria, 35 from literature searches and one from hand searching. Of those studies 1, 27 and 8 were low, moderate and high quality, respectively. The reviews highlight the scarcity of evidence for health economic parameters, for example, clinical effectiveness, costs, quality of life and the natural history of disease. Health economic evaluations such as cost-effectiveness and budget-impact analyses were scarce, and generally low-to-moderate quality. The causes were limited health economic parameters, together with publications bias, especially for cost-effectiveness analyses. CONCLUSIONS: The results highlighted issues around a considerable paucity of evidence for economic evaluations and few cost-effectiveness analyses, supporting the notion that a paucity of evidence makes economic evaluations of rare diseases more challenging compared with more prevalent diseases. Furthermore, we provide recommendations for more sustainable approaches in economic evaluations of rare diseases.

The association of neighborhood socioeconomic status with executive function and processing speed in cognitively normal Mexican Americans elders from the Health and Aging Brains Study - Health Disparities cohort.

INTRODUCTION: Neighborhood socioeconomic status (NSES) has been linked with overall health, and this study will evaluate whether NSES is cross-sectionally associated with cognition in non-Hispanic Whites (NHW) and Mexican Americans (MA) from the Health and Aging Brain: Health Disparities Study (HABS-HD). METHODS: The HABS-HD is a longitudinal study conducted at the University of North Texas Health Science Center. The final sample analyzed (n=1312) were 50 years or older, with unimpaired cognition, and underwent an interview, neuropsychological examination, imaging, and blood draw. NSES was measured using the national area deprivation index (ADI) percentile ranking, which considered socioeconomic variables. Executive function and processing speed were assessed by the trail making tests (A and B) and the digit-symbol substitution test, respectively. Linear regression was used to assess the association of ADI and cognitive measures. RESULTS: MA were younger, more likely to be female, less educated, had higher ADI scores, performed worse on trails B (all p<0.05), and have lower prevalence of APOE4+ (p<0.001), when compared to NHW. A higher percentage of MA lived in the most deprived neighborhoods than NHW. For NHW, ADI did not predict trails B or DSS scores, after adjusting for demographic variables and APOE4. For MA, ADI predicted trails A, trails B, and DSS after adjusting for demographic covariates and APOE4 status. CONCLUSION: Our study revealed that living in an area of higher deprivation was associated with lower cognitive function in MA but not in NHW, which is important to consider in future interventions to slow cognitive decline.

Large-scale Pan-cancer Cell Line Screening Identifies Actionable and Effective Drug Combinations.

Oncology drug combinations can improve therapeutic responses and increase treatment options for patients. The number of possible combinations is vast and responses can be context-specific. Systematic screens can identify clinically relevant, actionable combinations in defined patient subtypes. We present data for 109 anticancer drug combinations from AstraZeneca's oncology small molecule portfolio screened in 755 pan-cancer cell lines. Combinations were screened in a 7 × 7 concentration matrix, with more than 4 million measurements of sensitivity, producing an exceptionally data-rich resource. We implement a new approach using combination Emax (viability effect) and highest single agent (HSA) to assess combination benefit. We designed a clinical translatability workflow to identify combinations with clearly defined patient populations, rationale for tolerability based on tumor type and combination-specific "emergent" biomarkers, and exposures relevant to clinical doses. We describe three actionable combinations in defined cancer types, confirmed in vitro and in vivo, with a focus on hematologic cancers and apoptotic targets. SIGNIFICANCE: We present the largest cancer drug combination screen published to date with 7 × 7 concentration response matrices for 109 combinations in more than 750 cell lines, complemented by multi-omics predictors of response and identification of "emergent" combination biomarkers. We prioritize hits to optimize clinical translatability, and experimentally validate novel combination hypotheses. This article is featured in Selected Articles from This Issue, p. 695.

Functional EPAS1/HIF2A missense variant is associated with hematocrit in Andean highlanders.

Hypoxia-inducible factor pathway genes are linked to adaptation in both human and nonhuman highland species. EPAS1, a notable target of hypoxia adaptation, is associated with relatively lower hemoglobin concentration in Tibetans. We provide evidence for an association between an adaptive EPAS1 variant (rs570553380) and the same phenotype of relatively low hematocrit in Andean highlanders. This Andean-specific missense variant is present at a modest frequency in Andeans and absent in other human populations and vertebrate species except the coelacanth. CRISPR-base-edited human cells with this variant exhibit shifts in hypoxia-regulated gene expression, while metabolomic analyses reveal both genotype and phenotype associations and validation in a lowland population. Although this genocopy of relatively lower hematocrit in Andean highlanders parallels well-replicated findings in Tibetans, it likely involves distinct pathway responses based on a protein-coding versus noncoding variants, respectively. These findings illuminate how unique variants at EPAS1 contribute to the same phenotype in Tibetans and a subset of Andean highlanders despite distinct evolutionary trajectories.

Correction: Plasmids manipulate bacterial behaviour through translational regulatory crosstalk.

[This corrects the article DOI: 10.1371/journal.pbio.3001988.].

Exploiting lung adaptation and phage steering to clear pan-resistant Pseudomonas aeruginosa infections in vivo.

Pseudomonas aeruginosa is a major nosocomial pathogen that causes severe disease including sepsis. Carbapenem-resistant P. aeruginosa is recognised by the World Health Organisation as a priority 1 pathogen, with urgent need for new therapeutics. As such, there is renewed interest in using bacteriophages as a therapeutic. However, the dynamics of treating pan-resistant P. aeruginosa with phage in vivo are poorly understood. Using a pan-resistant P. aeruginosa in vivo infection model, phage therapy displays strong therapeutic potential, clearing infection from the blood, kidneys, and spleen. Remaining bacteria in the lungs and liver displays phage resistance due to limiting phage adsorption. Yet, resistance to phage results in re-sensitisation to a wide range of antibiotics. In this work, we use phage steering in vivo, pre-exposing a pan resistant P. aeruginosa infection with a phage cocktail to re-sensitise bacteria to antibiotics, clearing the infection from all organs.

Basal Cell Carcinoma With Metastasis to the Thoracic Spine: An Uncommon Case Report and Review of the Literature.

Basal cell carcinoma is an exceedingly rare cause of spinal metastatic disease for which the treatment algorithm is poorly defined. We present a positive patient outcome after treatment of T8 metastatic basal with posterior decompression and fusion followed by later anterior reconstruction, in addition to targeted radiation therapy and pharmacologic therapy. In general, a personalized and comprehensive treatment approach should be used, incorporating surgical, oncologic, and pharmacologic methods as able. Moreover, primary preventive medical and mental health care can help prevent delayed presentation and increased access to timely care.

Multi-layered genome defences in bacteria.

Bacteria have evolved a variety of defence mechanisms to protect against mobile genetic elements, including restriction-modification systems and CRISPR-Cas. In recent years, dozens of previously unknown defence systems (DSs) have been discovered. Notably, diverse DSs often coexist within the same genome, and some co-occur at frequencies significantly higher than would be expected by chance, implying potential synergistic interactions. Recent studies have provided evidence of defence mechanisms that enhance or complement one another. Here, we review the interactions between DSs at the mechanistic, regulatory, ecological and evolutionary levels.

The bidirectional relationship between head injuries and conduct problems: longitudinal modelling of a population-based birth cohort study.

Childhood head injuries and conduct problems increase the risk of aggression and criminality and are well-known correlates. However, the direction and timing of their association and the role of their demographic risk factors remain unclear. This study investigates the bidirectional links between both from 3 to 17 years while revealing common and unique demographic risks. A total of 8,603 participants (50.2% female; 83% White ethnicity) from the Millennium Cohort Study were analysed at 6 timepoints from age 3 to 17. Conduct problems were parent-reported for ages 3 to 17 using the Strengths and Difficulties Questionnaire (SDQ) and head injuries at ages 3 to 14. A cross-lagged path model estimated the longitudinal bidirectional effects between the two whilst salient demographic risks were modelled cumulatively at three ecological levels (child, mother, and household). Conduct problems at age 5 promoted head injuries between 5 and 7 (Z = 0.07; SE = 0.03; 95% CI, 0.02-0.13), and head injuries at ages 7 to 11 promoted conduct problems at age 14 (ß = .0.06; SE = .0.03; 95% CI, 0.01-0.12). Head injuries were associated with direct child-level risk at age 3, whereas conduct problems were associated with direct risks from all ecological levels until 17 years. The findings suggest a sensitive period at 5-11 years for the bidirectional relationship shared between head injuries and conduct problems. They suggest that demographic risks for increased head injuries play an earlier role than they do for conduct problems. Both findings have implications for intervention timing.

Longitudinal predictors of health-related quality of life in isolated dystonia.

OBJECTIVE: To determine longitudinal predictors of health-related quality of life (HR-QoL) in an international multicenter cohort of patients with isolated dystonia. METHODS: Out of 603 dystonia patients prospectively enrolled in the Natural History Dystonia Coalition study, 155 were assessed three times within 2 years for HR-QoL, symptoms of depression, generalized anxiety disorder (GAD), and social anxiety disorder (SAD), as well as dystonia severity and dystonic tremor. In addition, the impact of botulinum neurotoxin (BoNT) injections on HR-QoL was evaluated after 1 year. RESULTS: Depressive symptoms at baseline predicted lower HR-QoL on all subscales after 2 years (all p ≤ 0.001). Higher GAD scores at baseline predicted lower HR-QoL related to general health, pain and emotional well-being, whereas higher SAD scores predicted higher pain-related QoL after 2 years (all p ≤ 0.006). Dystonia severity at baseline predicted social functioning (p = 0.002). Neither dystonic tremor, age, or sex predicted HR-QoL at 2 years. Two latent categories were revealed across the three-time points: Category 1 with higher total HR-QoL scores (mean HR-QoL = 74.4% ± 16.1), susceptible to symptoms of depression and SAD, and Category 2 with lower total HR-QoL scores (mean HR-QoL = 45.5% ± 17.6), susceptible to symptoms of GAD. HR-QoL improved over the course of 1 year irrespective of the use of BoNT. CONCLUSION: The longitudinal impact of psychiatric symptoms on HR-QoL emphasizes the importance of incorporating mental health treatment, in particular also the therapy of anxiety disorders, into treatment regimens for dystonia.

IMG/PR: a database of plasmids from genomes and metagenomes with rich annotations and metadata.

Plasmids are mobile genetic elements found in many clades of Archaea and Bacteria. They drive horizontal gene transfer, impacting ecological and evolutionary processes within microbial communities, and hold substantial importance in human health and biotechnology. To support plasmid research and provide scientists with data of an unprecedented diversity of plasmid sequences, we introduce the IMG/PR database, a new resource encompassing 699 973 plasmid sequences derived from genomes, metagenomes and metatranscriptomes. IMG/PR is the first database to provide data of plasmid that were systematically identified from diverse microbiome samples. IMG/PR plasmids are associated with rich metadata that includes geographical and ecosystem information, host taxonomy, similarity to other plasmids, functional annotation, presence of genes involved in conjugation and antibiotic resistance. The database offers diverse methods for exploring its extensive plasmid collection, enabling users to navigate plasmids through metadata-centric queries, plasmid comparisons and BLAST searches. The web interface for IMG/PR is accessible at https://img.jgi.doe.gov/pr. Plasmid metadata and sequences can be downloaded from https://genome.jgi.doe.gov/portal/IMG_PR.

NHC Carbene-Metal Complex Ligand Binding Energies.

The ligand binding energies (LBEs) of N-heterocyclic carbenes (NHCs) and CH2 and CF2 adducts with group 1, 2, 10, and 11 metals and complexes with metals from these groups are predicted at the coupled cluster CCSD(T) level of theory by using density functional theory optimized geometries. The differences in LBEs as a function of the metal and the types of bonding interactions as well as the type of carbene are described. The bonding between the alkali cations and alkaline earth dications is predominantly ionic with a linear correlation between the LBEs and the cation hardness. In contrast, the bonding behaviors of the group 10 and 11 metals and metal complexes have only a weak, indirect correlation between the LBEs and the metal hardness. The difference in bonding behavior between the groups of metals arises due to the accessibility of electron donation between the ligand and the metal in the transition metal complexes, which results in more covalent-like bonding behavior. The presence of the methyl groups on the NHC nitrogen results in only slightly more delocalized charge from the metal onto the ring, but there is significant redistribution of the charge on the ring. Saturation of the NHC ring had a much smaller effect on how the charge was distributed on the ring. The analysis of the bonding behavior of NHCs with various metal groups enables improved understanding of carbene-metal interactions to inform rational design of NHC-based systems.

Adolescent delinquency following co-occurring childhood head injuries and conduct problem symptoms: findings from a UK longitudinal birth cohort.

Childhood conduct problems and head injuries share a bidirectional association, but how this affects the risk of adolescent delinquency is unknown. Due to their similar underlying mechanisms (i.e. increased impulsivity), this study aims to identify whether their co-occurrence increases the risk of adolescent delinquency. Data was obtained from 11,272 children at age 14 and 10,244 at age 17 years enrolled in the UK Millennium Cohort Study. Conduct problem symptoms (via the Strengths and Difficulties Questionnaire) and head injuries were parent reported from ages 3 to 14 years. Delinquency was self-reported at ages 14 and 17 including substance use, criminality, and antisocial behaviour. Incident rate ratios (IRR) were estimated for delinquency at ages 14 and 17 by childhood conduct problem and head injury status. Co-occurring head injuries and high conduct problem symptoms presented the greatest risk for overall delinquency and substance use at age 14 compared to those with the presence of one or neither (IRRs from 1.20 to 1.60). At age 17, conduct problems (with or without co-occurring head injuries) presented the greatest risk for overall delinquency, substance use, and antisocial behaviour. There was no evidence for an increased risk of delinquency at ages 14 or 17 following a head injury only. Whilst these findings suggest childhood head injuries alone do not increase the risk of adolescent delinquency, when co-occurring alongside high conduct problem symptoms there is a heightened earlier risk. These results provide further insight into adolescent delinquency and the outcomes of co-occurring childhood head injury and conduct problem symptoms.

Comorbidities Incorporated to Improve Prediction for Prevalent Mild Cognitive Impairment and Alzheimer's Disease in the HABS-HD Study.

BACKGROUND: Blood biomarkers have the potential to transform Alzheimer's disease (AD) diagnosis and monitoring, yet their integration with common medical comorbidities remains insufficiently explored. OBJECTIVE: This study aims to enhance blood biomarkers' sensitivity, specificity, and predictive performance by incorporating comorbidities. We assess this integration's efficacy in diagnostic classification using machine learning, hypothesizing that it can identify a confident set of predictive features. METHODS: We analyzed data from 1,705 participants in the Health and Aging Brain Study-Health Disparities, including 116 AD patients, 261 with mild cognitive impairment, and 1,328 cognitively normal controls. Blood samples were assayed using electrochemiluminescence and single molecule array technology, alongside comorbidity data gathered through clinical interviews and medical records. We visually explored blood biomarker and comorbidity characteristics, developed a Feature Importance and SVM-based Leave-One-Out Recursive Feature Elimination (FI-SVM-RFE-LOO) method to optimize feature selection, and compared four models: Biomarker Only, Comorbidity Only, Biomarker and Comorbidity, and Feature-Selected Biomarker and Comorbidity. RESULTS: The combination model incorporating 17 blood biomarkers and 12 comorbidity variables outperformed single-modal models, with NPV12 at 92.78%, AUC at 67.59%, and Sensitivity at 65.70%. Feature selection led to 22 chosen features, resulting in the highest performance, with NPV12 at 93.76%, AUC at 69.22%, and Sensitivity at 70.69%. Additionally, interpretative machine learning highlighted factors contributing to improved prediction performance. CONCLUSIONS: In conclusion, combining feature-selected biomarkers and comorbidities enhances prediction performance, while feature selection optimizes their integration. These findings hold promise for understanding AD pathophysiology and advancing preventive treatments.

Increasing the π-Expansive Ligands in Ruthenium(II) Polypyridyl Complexes: Synthesis, Characterization, and Biological Evaluation for Photodynamic Therapy Applications.

Lack of selectivity is one of the main issues with currently used chemotherapies, causing damage not only to altered cells but also to healthy cells. Over the last decades, photodynamic therapy (PDT) has increased as a promising therapeutic tool due to its potential to treat diseases like cancer or bacterial infections with a high spatiotemporal control. Ruthenium(II) polypyridyl compounds are gaining attention for their application as photosensitizers (PSs) since they are generally nontoxic in dark conditions, while they show remarkable toxicity after light irradiation. In this work, four Ru(II) polypyridyl compounds with sterically expansive ligands were studied as PDT agents. The Ru(II) complexes were synthesized using an alternative route to those described in the literature, which resulted in an improvement of the synthesis yields. Solid-state structures of compounds [Ru(DIP)2phen]Cl2 and [Ru(dppz)2phen](PF6)2 have also been obtained. It is well-known that compound [Ru(dppz)(phen)2]Cl2 binds to DNA by intercalation. Therefore, we used [Ru(dppz)2phen]Cl2 as a model for DNA interaction studies, showing that it stabilized two different sequences of duplex DNA. Most of the synthesized Ru(II) derivatives showed very promising singlet oxygen quantum yields, together with noteworthy photocytotoxic properties against two different cancer cell lines, with IC50 in the micro- or even nanomolar range (0.06-7 µM). Confocal microscopy studies showed that [Ru(DIP)2phen]Cl2 and [Ru(DIP)2TAP]Cl2 accumulate preferentially in mitochondria, while no mitochondrial internalization was observed for the other compounds. Although [Ru(dppn)2phen](PF6)2 did not accumulate in mitochondria, it interestingly triggered an impairment in mitochondrial respiration after light irradiation. Among others, [Ru(dppn)2phen](PF6)2 stands out for its very good IC50 values, correlated with a very high singlet oxygen quantum yield and mitochondrial respiration disruption.

Molecular landscape and functional characterization of centrosome amplification in ovarian cancer.

High-grade serous ovarian carcinoma (HGSOC) is characterised by poor outcome and extreme chromosome instability (CIN). Therapies targeting centrosome amplification (CA), a key mediator of chromosome missegregation, may have significant clinical utility in HGSOC. However, the prevalence of CA in HGSOC, its relationship to genomic biomarkers of CIN and its potential impact on therapeutic response have not been defined. Using high-throughput multi-regional microscopy on 287 clinical HGSOC tissues and 73 cell lines models, here we show that CA through centriole overduplication is a highly recurrent and heterogeneous feature of HGSOC and strongly associated with CIN and genome subclonality. Cell-based studies showed that high-prevalence CA is phenocopied in ovarian cancer cell lines, and that high CA is associated with increased multi-treatment resistance; most notably to paclitaxel, the commonest treatment used in HGSOC. CA in HGSOC may therefore present a potential driver of tumour evolution and a powerful biomarker for response to standard-of-care treatment.

Linked head injury and conduct problem symptom pathways from early childhood to adolescence and their associated risks: Evidence from the millennium cohort study.

Conduct problems and head injuries increase the risk of delinquency and share a bidirectional association. However, how they link across development is unknown. The present study aimed to identify their linked developmental pathways and associated risk factors. Latent class analysis was modeled from Millennium Cohort Study data (n = 8,600) to identify linked pathways of conduct problem symptoms and head injuries. Head injuries were parent-reported from ages 3 to 14 and conduct problems from ages 3 to 17 using the Strengths and Difficulties Questionnaire (SDQ). Multinomial logistic regression then identified various risk factors associated with pathway membership. Four distinct pathways were identified. Most participants displayed low-level conduct problem symptoms and head injuries (n = 6,422; 74.7%). Three groups were characterized by clinically relevant levels of conduct problem symptoms and high-risk head injuries in childhood (n = 1,422; 16.5%), adolescence (n = 567; 6.6%), or persistent across development (n = 189; 2.2%). These clinically relevant pathways were associated with negative maternal parenting styles. These findings demonstrate how pathways of conduct problem symptoms are uniquely linked with distinct head injury pathways. Suggestions for general preventative intervention targets include early maternal negative parenting styles. Pathway-specific interventions are also required targeting cumulative risk at different ecological levels.

Precision Medicine for Preventing Alzheimer's Disease: Analysis of the ADAPT Study.

BACKGROUND: The Alzheimer's Disease Anti-inflammatory Prevention Trial (ADAPT) was the first-ever large-scale anti-inflammatory prevention trial targeting Alzheimer's disease. OBJECTIVE: The overall goal of this study was to evaluate predictive blood biomarker profiles that identified individuals most likely to be responders on NSAID treatment or placebo at 12 and 24 months. METHODS: Baseline (n = 193) and 12-month (n = 562) plasma samples were assayed. The predictive biomarker profile was generated using SVM analyses with response on treatment (yes/no) as the outcome variable. RESULTS: Baseline (AUC = 0.99) and 12-month (AUC = 0.99) predictive biomarker profiles were highly accurate in predicting response on Celecoxib arm at 12 and 24 months. The baseline (AUC = 0.95) and 12-month (AUC = 0.9) predictive biomarker profile predicting response on Naproxen were also highly accurate at 12 and 24 months. The baseline (AUC = 0.93) and 12-month (AUC = 0.99) predictive biomarker profile was also highly accurate in predicting response on placebo. As with our prior work, the profiles varied by treatment arm. CONCLUSIONS: The current results provide additional support for a precision medicine model for treating and preventing Alzheimer's disease.

Evaluation of Neighborhood-Level Disadvantage and Cognition in Mexican American and Non-Hispanic White Adults 50 Years and Older in the US.

Importance: Understanding how socioeconomic factors are associated with cognitive aging is important for addressing health disparities in Alzheimer disease. Objective: To examine the association of neighborhood disadvantage with cognition among a multiethnic cohort of older adults. Design, Setting, and Participants: In this cross-sectional study, data were collected between September 1, 2017, and May 31, 2022. Participants were from the Health and Aging Brain Study-Health Disparities, which is a community-based single-center study in the Dallas/Fort Worth area of Texas. A total of 1614 Mexican American and non-Hispanic White adults 50 years and older were included. Exposure: Neighborhood disadvantage for participants' current residence was measured by the validated Area Deprivation Index (ADI); ADI Texas state deciles were converted to quintiles, with quintile 1 representing the least disadvantaged area and quintile 5 the most disadvantaged area. Covariates included age, sex, and educational level. Main Outcomes and Measures: Performance on cognitive tests assessing memory, language, attention, processing speed, and executive functioning; measures included the Spanish-English Verbal Learning Test (SEVLT) Learning and Delayed Recall subscales; Wechsler Memory Scale, third edition (WMS-III) Digit Span Forward, Digit Span Backward, and Logical Memory 1 and 2 subscales; Trail Making Test (TMT) parts A and B; Digit Symbol Substitution Test (DSST); Letter Fluency; and Animal Naming. Raw scores were used for analyses. Associations between neighborhood disadvantage and neuropsychological performance were examined via demographically adjusted linear regression models stratified by ethnic group. Results: Among 1614 older adults (mean [SD] age, 66.3 [8.7] years; 980 women [60.7%]), 853 were Mexican American (mean [SD] age, 63.9 [7.9] years; 566 women [66.4%]), and 761 were non-Hispanic White (mean [SD] age, 69.1 [8.7] years; 414 women [54.4%]). Older Mexican American adults were more likely to reside in the most disadvantaged areas (ADI quintiles 3-5), with 280 individuals (32.8%) living in ADI quintile 5, whereas a large proportion of older non-Hispanic White adults resided in ADI quintile 1 (296 individuals [38.9%]). Mexican American individuals living in more disadvantaged areas had worse performance than those living in ADI quintile 1 on 7 of 11 cognitive tests, including SEVLT Learning (ADI quintile 5: ß = -2.50; 95% CI, -4.46 to -0.54), SEVLT Delayed Recall (eg, ADI quintile 3: ß = -1.11; 95% CI, -1.97 to -0.24), WMS-III Digit Span Forward (eg, ADI quintile 4: ß = -1.14; 95% CI, -1.60 to -0.67), TMT part A (ADI quintile 5: ß = 7.85; 95% CI, 1.28-14.42), TMT part B (eg, ADI quintile 5: ß = 31.5; 95% CI, 12.16-51.35), Letter Fluency (ADI quintile 4: ß = -2.91; 95% CI, -5.39 to -0.43), and DSST (eg, ADI quintile 5: ß = -4.45; 95% CI, -6.77 to -2.14). In contrast, only non-Hispanic White individuals living in ADI quintile 4 had worse performance than those living in ADI quintile 1 on 4 of 11 cognitive tests, including SEVLT Learning (ß = -2.35; 95% CI, -4.40 to -0.30), SEVLT Delayed Recall (ß = -0.95; 95% CI, -1.73 to -0.17), TMT part B (ß = 15.95; 95% CI, 2.47-29.44), and DSST (ß = -3.96; 95% CI, -6.49 to -1.43). Conclusions and Relevance: In this cross-sectional study, aging in a disadvantaged area was associated with worse cognitive functioning, particularly for older Mexican American adults. Future studies examining the implications of exposure to neighborhood disadvantage across the life span will be important for improving cognitive outcomes in diverse populations.