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Lowe Syndrome is a developmental disorder characterized by eye, kidney, and neurological pathologies, and is caused by mutations in the phosphatidylinositol-5-phosphatase OCRL. OCRL plays diverse roles in endocytic and endolysosomal trafficking, cytokinesis, and ciliogenesis, but it is unclear which of these cellular functions underlie specific patient symptoms. Here, we show that mutation of Drosophila OCRL causes cell-autonomous activation of hemocytes, which are macrophage-like cells of the innate immune system. Among many cell biological defects that we identified in docrl mutant hemocytes, we pinpointed the cause of innate immune cell activation to reduced Rab11-dependent recycling traffic and concomitantly increased Rab7-dependent late endosome traffic. Loss of docrl amplifies multiple immune-relevant signals, including Toll, Jun kinase, and STAT, and leads to Rab11-sensitive mis-sorting and excessive secretion of the Toll ligand Spåtzle. Thus, docrl regulation of endosomal traffic maintains hemocytes in a poised, but quiescent state, suggesting mechanisms by which endosomal misregulation of signaling may contribute to symptoms of Lowe syndrome.

The Biofluid Biomarkers Best Practices Workgroup of the National Alzheimer's Coordinating Center–Alzheimer's Disease Research Center (ADRC) Biomarker Core Steering Committee was convened to update pre‐analytical handling guidelines for biofluid biomarkers, focusing on cerebrospinal fluid (CSF) and blood. We reviewed current literature pertinent to best practices for biomarker studies and surveyed the ADRCs for biomarker analytes, platforms, and protocols used at each center. Across 37 ADRCs, 16 CSF and 28 plasma/serum analytes were reported to be studied at multiple centers. The pre‐analytical handling steps and concerns related to each, as supported by empirical studies and expert opinion, were integrated to generate a revised guideline document. The guideline aimed to standardize steps in biospecimen and biomarker analyte collection, storage, and pre‐analytical handling across the ADRCs. The 2025 ADRC guidelines represent the current working knowledge on biomarker best practices, providing guidance and harmonized protocols, and promoting robust analysis and reporting of composite data. Highlights The largest source of laboratory variance in analyte measurement is from delays in processing; thus, there is a need for standardized processing and centrifugation protocols. Tube types matter, as does dead volume in stored biospecimen aliquots. Standardized ATN analyte assays, including pT217‐tau, are stable at 4°C for short periods, cell free. Most proteins withstand two or more freeze‐thaws before activity‐integrity loss. Operational bench time should be standardized to avoid temporal variance between runs.

Neuropsychiatric symptoms are uncommon at Alzheimer's Disease (AD) dementia diagnosis but are exhibited by nearly everyone during the course of dementia. Depressive symptoms are common in AD dementia. We sought to determine correlations between memory, executive functioning, language, neuropsychiatric symptoms, and depressive symptoms at AD dementia diagnosis, and to characterize neuropsychiatric and depressive symptoms across groups defined by substantial relative cognitive impairments, using data from the National Alzheimer's Coordinating Center (NACC). Using confirmatory factor analysis, we derived composite Neuropsychiatric Inventory Questionnaire (NPI-Q) and Geriatric Depression Scale (excluding the memory question) scores. We defined a reference category of people with AD dementia whose memory, executive functioning, and language scores were similar to each other. Other groups were defined based on relative differences in cognitive domain scores. We used multinomial logistic regression to test if neuropsychiatric and depressive symptoms differed across groups. Our sample included the diagnosis visit for 7,747 people with AD dementia and CDR = 1 (Table 1). Correlations between cognitive domains ranged from +0.29 to +0.50. Correlations between cognitive domains and NPI-Q composite scores ranged from -0.02 to +0.04 and with depressive symptoms from -0.09 to +0.14. The correlation between depressive symptoms and the NPI-Q composite was +0.17. We did not find a difference in NPI-Q composite scores across groups, but depressive symptom score differed across groups (p<0.0001), with higher scores in people with relatively greater executive functioning impairments and lower scores in people with relatively greater memory impairments, compared to people with similar domain scores (Figure 1, Table 2). Composite scores for depressive and neuropsychiatric symptoms facilitate well-powered investigations of relationships with these clinically salient factors. Neuropsychiatric symptoms had trivial correlations with cognitive domain scores at AD dementia diagnosis, and did not differ across groups defined by substantial relative cognitive impairments. Depressive symptoms were weakly correlated with cognitive domain scores, and differed across groups defined by substantial relative cognitive impairments. More research is warranted to further characterize depression and neuropsychiatric symptoms over the course of AD dementia.

The presence of multiple pathologies is the largest predictor of dementia. A major gap in the field is the in vivo detection of mixed pathologies and their antecedents. The Alzheimer's Disease Research Centers (ADRCs) are uniquely positioned to address this gap. The ADRCs longitudinally follow ≈ 17,000 participants, ranging from cognitively unimpaired to dementia, arising from Alzheimer's disease (AD) and related dementias (ADRD; e.g., AD, Lewy body disorders, vascular). Motivated by the Alzheimer's Disease Neuroimaging Initiative's (ADNI) impact, the ADRC Consortium for Clarity in ADRD Research Through Imaging (CLARiTI) was formed. Leveraging existing ADRC infrastructure, CLARiTI will integrate standardized imaging and plasma collection to characterize mixed pathologies and use community‐engaged research methods to ensure that ≥ 25% of the sample is from underrepresented populations (e.g., ethnoculturally minoritized, low education). The resulting ADRD profiles, within a more diverse sample, will provide key resources for ADRCs and an unprecedented, more generalizable publicly available imaging‐plasma dataset. Highlights In vivo detection of mixed pathologies is critical for Alzheimer's disease and related dementias research. The Alzheimer's Disease Research Centers (ADRCs) are uniquely positioned to address gaps related to mixed pathologies. The ADRC Consortium for Clarity in ADRD Research Through Imaging (CLARiTI) will enhance this national program by adding standardized imaging and plasma collection to existing ADRC infrastructure. This effort will provide key resources for ADRCs and an unprecedented publicly available imaging–plasma–neuropath dataset.

Limbic free‐water (FW)–corrected white matter (WM) integrity is heritable in late‐life aging Six genome‐wide loci discovered for limbic WM traits in Alzheimer's disease (AD)–enriched cohorts Chr18 locus implicates CDH19 , linking oligodendrocyte biology to WM microstructure RORA , FAM107B , and KC6 expression tracks cognitive decline and AD neuropathology

Cerebrovascular pathology frequently co-occurs with Alzheimer's disease (AD) pathology and the combinations of these forms of pathology may underly AD dementia. Sex hormones influence many aspects of cerebrovascular systems and may contribute to cerebrovascular pathology, but many studies of aging and AD do not measure hormones. Therefore, in this study, we explored whether a polygenic score predicting sex hormone levels relates to cerebrovascular pathology in the AD brain. Sex-specific Polygenic Risk Scores (PRS) of the sex hormones testosterone (N : 146,339; N : 142,778) and estradiol N 147,690; N 163,985) were built using a linkage-disequilibrium (LD) clumping method from published sex-stratified GWAS from UK Biobank, using individuals with an age range of 40-69 years old. Each PRS was scaled before analysis. Genetic data and harmonized cerebrovascular pathology data were leveraged from non-Hispanic White autopsy participants from three independent studies of aging and AD: Adult Changes in Thought (ACT), the National Alzheimer's Coordinating Center (NACC), and the Religious Orders Study/Rush Memory and Aging Project (ROSMAP) (N : 4,269; N : 4,609). Characteristics of the participants are described in Table 1. Sex-specific logistic regression models were used to evaluate whether each PRS relate to cerebrovascular disease (CVD) outcomes, including presence or absence of macroscopic infarcts, microinfarcts, atherosclerosis, or arteriolosclerosis. Covariates included age at death, last clinical diagnosis before death, and education. Higher genetically predicted levels of testosterone in males were associated with the presence of macroscopic infarcts (Table 2; b = 0.11, p = 0.03). Interestingly, higher genetically predicted levels of estradiol in males were associated with the presence of arteriolosclerosis (Table 2; b = 0.13, p = 0.02). No significant associations were observed for the other CVD outcomes in men and none in women. Significant results did not survive corrections for multiple comparisons. The results show that a PRS of sex hormones can be used to explore the effect of sex hormone levels on cerebrovascular pathology as it pertains to AD. The results also support the need for more studies investigating the role of sex hormones on sex-specific phenotypes of cerebrovascular pathology in the presence of AD. Future work is needed to better understand the mechanisms behind the observed associations.

Cardio and cerebrovascular risk factors (CVRFs) increase the risk of cerebrovascular disease and clinical Alzheimer's Disease (AD), and over 70% of the patients with AD coincident cerebrovascular pathology. We previously found that FMNL2 interacts with a burden score of hypertension, diabetes, heart disease, and body mass index (BMI) by altering the normal astroglial-vascular mechanisms that underly amyloid clearance. Stroke, defined by history of a clinical stroke or brain imaging, is a moderately robust risk factor for AD and dementia. The goal here was to identify genes that interact with CVRFs, incorporating stroke as an additional factor, on AD in multi-ethnic cohorts. We conducted a genome-wide gene-CVRF score interaction analysis for AD, in 7,939 AD patients and 9,631 controls from eight multi-ethnic cohorts of non-Hispanic Whites, African Americans, and Hispanics including ADNI, NACC, NOMAS, WHICAP, EFIGA, and ROSMAP. A CVRF score was created from the first principal component of history of clinical stroke, hypertension, diabetes, and heart disease, and measured BMI. Gene-based interaction test was performed with the adaptive gene-environment interaction test. Results were summarized using a meta-analysis. We investigated the association of pathological AD, amyloid-β, or brain infarcts with gene expression and protein expression from the frontal cortex in ROSMAP using a generalized linear model. Age, sex, and the first three principal components were adjusted in the models. The interaction of CVRF score with FMNL2 on AD (p = 1.02E-05) was identified and additional genes were identified to interact with CVRF score, including SLC22A14 (p = 1.44E-06), AMMECR1L (p = 2.74E-06), PRG3 (p = 2.76E-06), CFAP99 (p = 5.22E-06), ADPGK-AS1 (p = 8.58E-06) and BRINP1 (p = 6.29E-06). ADPGK-AS1 and FMNL2 gene expressions were associated with pathological AD (p = 0.004 and p = 0.0002). FMNL2 and BRINP1 gene expressions were higher in the brains of patients with brain infarcts (p = 0.025 and p = 0.006). BRINP1 protein expression was associated with pathological AD (p = 0.0002) and was higher in the brains of patients with brain infarcts (p = 0.022). We identified novel candidate genes that interact with CVRFs on AD in multi-ethnic cohorts. Understanding the interplay between genes, CVRFs, and AD has the potential to reveal novel molecular targets for prevention and treatment for AD.

Background Increasing underrepresented racial and ethnic minority group (URG) participation in early‐stage Alzheimer’s disease and related dementias (ADRD) research is critical to inclusive characterization of underlying pathology and testing of disease‐modifying treatments. One promising recruitment strategy to accelerate URG participation is for healthcare professionals (HCPs) to facilitate referrals. The use of HCP‐facilitated recruitment strategies across the Alzheimer’s Disease Research Center (ADRC) network, a major referral source for ADRD multisite observational and clinical trials, has not been examined. We hypothesized that there would be interest in the development of scalable HCP‐facilitated recruitment strategies to accelerate URG participation across the ADRC network. Methods We emailed Outreach, Recruitment and Engagement (ORE) Cores within the NIA‐funded ADRC network to complete a web‐based REDCap™ survey on their current HCP‐facilitated recruitment strategies for URG participants, resources enhancing use of these strategies, and their interest in strategy development. We conducted descriptive statistics using SPSS 29.0. Results Out of 37 ADRCs, 27 (73.0%) completed the survey. Although the majority of ADRCs (66.7%, N = 18) reported HCPs referring URG participants (Table 1), they mostly relied on HCP faculty based at the ADRC (48.1%, N = 13) or the ADRC affiliated academic medical center (51.9%, N = 14) (Table 2). Nearly all (92.5%, N = 25) ORE Cores expressed interest in participating in or learning more about future efforts to develop HCP‐facilitated recruitment strategies for increasing URG participation. Resources which would increase use of HCP‐facilitated strategies for URG referrals included guidance on outreach and engagement strategies (70.4%, N = 19), culturally tailored resources for HCPs to refer participants (59.3%, N = 16), technology and informatic recruitment strategies (63.0%, N = 17), and staff effort (63.0%, N = 17) (Table 3). Conclusions Our survey identified key opportunities to develop novel scalable HCP‐facilitated recruitment strategies to accelerate URG participation. Although most ORE Cores expressed interest in expanding their HCP‐facilitated recruitment strategies to have more inclusive research participation, there is need for both higher‐level strategic guidance and ready‐to‐use resources to implement these strategies. Future studies will need to develop and test scalable HCP‐facilitated strategies and resources to systematically accelerate URG research participation.

Background Despite recognition of the need to increase underrepresented groups (URG) engagement in Alzheimer’s disease and related dementias (ADRD) studies, enrollment remains low. As a first step in examining these disparities, these analyses aimed to compare referral sources for Alzheimer’s Disease Research Centers (ADRC) enrollment of URG participants. Method These analyses included data from 48,330 participants across 46 ADRCs, obtained through the National Alzheimer’s Coordinating Center Uniform Data Set. Generalized logistic regression models with generalized estimating equations were used to examine the association of racial/ethnic group and professional vs non‐professional referral source. The ‘professional’ category included referrals made by healthcare professionals or ADRC staff, while the ‘non‐professional’ category included referrals made by self, family or friends. This association was examined across the entire sample, and then individuals who had completed magnetic resonance imaging (MRI). The analyses were adjusted for age, gender, education, visit year, and categorical CDR with random site effect to adjust for study site. Result Descriptive statistics are shown in Table 1. Non‐Hispanic Black and Asian participants were less likely to have completed an MRI. Across the entire sample, Non‐Hispanic Black and Non‐Hispanic Asian participants were less likely to be referred by a professional contact than Non‐Hispanic White participants (Table 2). In those who had completed an MRI, there were no significant differences across the racial groups, although we note that the sample sizes for those with MRI were much smaller (Table 3). Results for both analyses were similar when only participants who had a diagnosis of MCI or dementia and a global CDR of 0.5 or 1 at baseline were included. Conclusion One major factor leading to lower rates of URG participation in ADRD research is disproportionately fewer healthcare professional referrals. To develop and optimize ADRC recruitment strategies, future studies are needed to explore reasons for differences in URG referrals by healthcare professionals and non‐professionals.