Global impacts of marine heatwaves on coastal foundation species.

With increasingly intense marine heatwaves affecting nearshore regions, foundation species are coming under increasing stress. To better understand their impacts, we examine responses of critical, habitat-forming foundation species (macroalgae, seagrass, corals) to marine heatwaves in 1322 shallow coastal areas located across 85 marine ecoregions. We find compelling evidence that intense, summer marine heatwaves play a significant role in the decline of foundation species globally. Critically, detrimental effects increase towards species warm-range edges and over time. We also identify several ecoregions where foundation species don't respond to marine heatwaves, suggestive of some resilience to warming events. Cumulative marine heatwave intensity, absolute temperature, and location within a species' range are key factors mediating impacts. Our results suggest many coastal ecosystems are losing foundation species, potentially impacting associated biodiversity, ecological function, and ecosystem services provision. Understanding relationships between marine heatwaves and foundation species offers the potential to predict impacts that are critical for developing management and adaptation approaches.

Plasma pTau181 Reveals a Pathological Signature that Predicts Cognitive Outcomes in Lewy Body Disease.

OBJECTIVE: To determine whether plasma phosphorylated-Tau181 (pTau181) could be used as a diagnostic biomarker of concurrent Alzheimer's disease neuropathologic change (ADNC) or amyloidosis alone, as well as a prognostic, monitoring, and susceptibility/risk biomarker for clinical outcomes in Lewy body disease (LBD). METHODS: We studied 565 participants: 94 LBD with normal cognition, 83 LBD with abnormal cognition, 114 with Alzheimer's disease, and 274 cognitively normal. Plasma pTau181 levels were measured with the Lumipulse G platform. Diagnostic accuracy for concurrent ADNC and amyloidosis was assessed with Receiver Operating Characteristic curves in a subset of participants with CSF pTau181/Aß42, and CSF Aß42/Aß40 or amyloid-ß PET, respectively. Linear mixed effects models were used to examine the associations between baseline and longitudinal plasma pTau181 levels and clinical outcomes. RESULTS: Plasma pTau181 predicted concurrent ADNC and amyloidosis in LBD with abnormal cognition with 87% and 72% accuracy, respectively. In LBD patients with abnormal cognition, higher baseline plasma pTau181 was associated with worse baseline MoCA and CDR-SB, as well as accelerated decline in CDR-SB. Additionally, in this group, rapid increases in plasma pTau181 over 3 years predicted a faster decline in CDR-SB and memory. In LBD patients with normal cognition, there was no association between baseline or longitudinal plasma pTau181 levels and clinical outcomes; however, elevated pTau181 at baseline increased the risk of conversion to cognitive impairment. INTERPRETATION: Our findings suggest that plasma pTau181 is a promising biomarker for concurrent ADNC and amyloidosis in LBD. Furthermore, plasma pTau181 holds potential as a prognostic, monitoring, and susceptibility/risk biomarker, predicting disease progression in LBD. ANN NEUROL 2024.

Multiple biomarkers improve diagnostic accuracy across Lewy body and Alzheimer's disease spectra.

OBJECTIVE: More than half of neurodegenerative disease patients have multiple pathologies at autopsy; however, most receive one diagnosis during life. We used the α-synuclein seed amplification assay (αSyn-SAA) and CSF biomarkers for amyloidosis and Alzheimer's disease (AD) neuropathological change (ADNC) to determine the frequency of co-pathologies in participants clinically diagnosed with Lewy body (LB) disease or AD. METHODS: Using receiver operating characteristic analyses on retrospective CSF samples from 150 participants determined αSyn-SAA accuracy, sensitivity, and specificity for identifying clinically defined LB disease and predicting future change in clinical diagnosis. CSF biomarkers helped determine the frequency of concomitant Lewy body pathology, ADNC, and/or amyloidosis in participants with LB disease and AD, across clinical spectra. RESULTS: Following a decade-long follow-up, the clinically or autopsy-defined diagnosis changed for nine participants. αSyn-SAA demonstrated improved accuracy (91.3%), sensitivity (89.3%), and specificity (93.3%) for identifying LB disease compared to all non-LB disease, highlighting the limitations of clinical diagnosis alone. When examining biomarkers of co-pathology, amyloidosis was present in 18%, 48%, and 71% (χ2(2) = 13.56, p = 0.001) and AD biomarkers were present in 0%, 8.7%, and 42.9% (χ2(2) = 18.44, p < 0.001) of LB disease participants with different stages of cognitive impairment respectively. Co-occurring biomarkers for αSyn-SAA and amyloidosis were present in 12% and 14% of AD compared to 43% and 57% LB disease participants with different stages of cognitive impairment (χ2(3) = 13.87, p = 0.003). INTERPRETATION: Our study shows that using a combination of αSyn-SAA and AD biomarkers can identify people with αSyn, ADNC, and co-pathology better and earlier than traditional clinical diagnostic criteria alone.

TREM1 disrupts myeloid bioenergetics and cognitive function in aging and Alzheimer disease mouse models.

Human genetics implicate defective myeloid responses in the development of late-onset Alzheimer disease. A decline in peripheral and brain myeloid metabolism, triggering maladaptive immune responses, is a feature of aging. The role of TREM1, a pro-inflammatory factor, in neurodegenerative diseases is unclear. Here we show that Trem1 deficiency prevents age-dependent changes in myeloid metabolism, inflammation and hippocampal memory function in mice. Trem1 deficiency rescues age-associated declines in ribose 5-phosphate. In vitro, Trem1-deficient microglia are resistant to amyloid-ß42 oligomer-induced bioenergetic changes, suggesting that amyloid-ß42 oligomer stimulation disrupts homeostatic microglial metabolism and immune function via TREM1. In the 5XFAD mouse model, Trem1 haploinsufficiency prevents spatial memory loss, preserves homeostatic microglial morphology, and reduces neuritic dystrophy and changes in the disease-associated microglial transcriptomic signature. In aging APPSwe mice, Trem1 deficiency prevents hippocampal memory decline while restoring synaptic mitochondrial function and cerebral glucose uptake. In postmortem Alzheimer disease brain, TREM1 colocalizes with Iba1+ cells around amyloid plaques and its expression is associated with Alzheimer disease clinical and neuropathological severity. Our results suggest that TREM1 promotes cognitive decline in aging and in the context of amyloid pathology.

Multi-cohort cerebrospinal fluid proteomics identifies robust molecular signatures for asymptomatic and symptomatic Alzheimer's disease.

Changes in Amyloid-ß (A), hyperphosphorylated Tau (T) in brain and cerebrospinal fluid (CSF) precedes AD symptoms, making CSF proteome a potential avenue to understand the pathophysiology and facilitate reliable diagnostics and therapies. Using the AT framework and a three-stage study design (discovery, replication, and meta-analysis), we identified 2,173 proteins dysregulated in AD, that were further validated in a third totally independent cohort. Machine learning was implemented to create and validate highly accurate and replicable (AUC>0.90) models that predict AD biomarker positivity and clinical status. These models can also identify people that will convert to AD and those AD cases with faster progression. The associated proteins cluster in four different protein pseudo-trajectories groups spanning the AD continuum and were enrichment in specific pathways including neuronal death, apoptosis and tau phosphorylation (early stages), microglia dysregulation and endolysosomal dysfuncton(mid-stages), brain plasticity and longevity (mid-stages) and late microglia-neuron crosstalk (late stages).

Post-translational modifications linked to preclinical Alzheimer's disease-related pathological and cognitive changes.

INTRODUCTION: In this study, we leverage proteomic techniques to identify communities of proteins underlying Alzheimer's disease (AD) risk among clinically unimpaired (CU) older adults. METHODS: We constructed a protein co-expression network using 3869 cerebrospinal fluid (CSF) proteins quantified by SomaLogic, Inc., in a cohort of participants along the AD clinical spectrum. We then replicated this network in an independent cohort of CU older adults and related these modules to clinically-relevant outcomes. RESULTS: We discovered modules enriched for phosphorylation and ubiquitination that were associated with abnormal amyloid status, as well as p-tau181 (M4: ß = 2.44, p < 0.001, M7: ß = 2.57, p < 0.001) and executive function performance (M4: ß = -2.00, p = 0.005, M7: ß = -2.39, p < 0.001). DISCUSSION: In leveraging CSF proteomic data from individuals spanning the clinical spectrum of AD, we highlight the importance of post-translational modifications for early cognitive and pathological changes.

Organ aging signatures in the plasma proteome track health and disease.

Animal studies show aging varies between individuals as well as between organs within an individual1-4, but whether this is true in humans and its effect on age-related diseases is unknown. We utilized levels of human blood plasma proteins originating from specific organs to measure organ-specific aging differences in living individuals. Using machine learning models, we analysed aging in 11 major organs and estimated organ age reproducibly in five independent cohorts encompassing 5,676 adults across the human lifespan. We discovered nearly 20% of the population show strongly accelerated age in one organ and 1.7% are multi-organ agers. Accelerated organ aging confers 20-50% higher mortality risk, and organ-specific diseases relate to faster aging of those organs. We find individuals with accelerated heart aging have a 250% increased heart failure risk and accelerated brain and vascular aging predict Alzheimer's disease (AD) progression independently from and as strongly as plasma pTau-181 (ref. 5), the current best blood-based biomarker for AD. Our models link vascular calcification, extracellular matrix alterations and synaptic protein shedding to early cognitive decline. We introduce a simple and interpretable method to study organ aging using plasma proteomics data, predicting diseases and aging effects.

Home Gardening of Yellow Cassava and Orange Maize for the Prevention of Nutritional Blindness in Children: An Economic Evaluation and Value of Information Analysis.

OBJECTIVES: Vitamin A deficiency is the leading cause of childhood blindness worldwide, affecting mostly Sub-Saharan Africa. We aimed to predict the cost-effectiveness of home gardening (HG) of yellow cassava and orange maize to prevent nutritional blindness in children below 5 years and to assess the likely value of obtaining additional information in reducing uncertainty surrounding its cost-effectiveness. METHODS: We developed a Markov model and carried out probabilistic sensitivity analysis with a value of information analysis. We costed resources from a societal perspective and outcomes were measured in disability-adjusted life years (DALYs). RESULTS: HG was estimated to cost an additional Intl$395.00 per DALY averted, with a 72.27% likelihood of being cost-effective at a threshold of Intl$2800 per DALY. The expected value of information was estimated to be Intl$29 843.50 for 1 child or Intl$925 billion for 31 million Nigerian children affected by the decision. Further research is only worthwhile for 1 parameter (relative risk of low serum retinol; expected value of perfect parameter information Intl$29 854.53 per child and Intl$925 billion for 31 million children). CONCLUSION: HG of yellow cassava and orange maize is expected to be highly cost-effective in preventing nutritional blindness in Nigerian children. Worthwhile further research includes a cost analysis of the intervention and a high-quality randomized trial to assess the effectiveness of HG on serum retinol levels in young children.

Consolidated Health Economic Evaluation Reporting Standards - Value of Information (CHEERS-VOI): Explanation and Elaboration.

OBJECTIVES: Although the ISPOR Value of Information (VOI) Task Force's reports outline VOI concepts and provide good-practice recommendations, there is no guidance for reporting VOI analyses. VOI analyses are usually performed alongside economic evaluations for which the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022 Statement provides reporting guidelines. Thus, we developed the CHEERS-VOI checklist to provide reporting guidance and checklist to support the transparent, reproducible, and high-quality reporting of VOI analyses. METHODS: A comprehensive literature review generated a list of 26 candidate reporting items. These candidate items underwent a Delphi procedure with Delphi participants through 3 survey rounds. Participants rated each item on a 9-point Likert scale to indicate its relevance when reporting the minimal, essential information about VOI methods and provided comments. The Delphi results were reviewed at 2-day consensus meetings and the checklist was finalized using anonymous voting. RESULTS: We had 30, 25, and 24 Delphi respondents in rounds 1, 2, and 3, respectively. After incorporating revisions recommended by the Delphi participants, all 26 candidate items proceeded to the 2-day consensus meetings. The final CHEERS-VOI checklist includes all CHEERS items, but 7 items require elaboration when reporting VOI. Further, 6 new items were added to report information relevant only to VOI (eg, VOI methods applied). CONCLUSIONS: The CHEERS-VOI checklist should be used when a VOI analysis is performed alongside economic evaluations. The CHEERS-VOI checklist will help decision makers, analysts and peer reviewers in the assessment and interpretation of VOI analyses and thereby increase transparency and rigor in decision making.

Proteogenomic analysis of human cerebrospinal fluid identifies neurologically relevant regulation and informs causal proteins for Alzheimer's disease.

The integration of quantitative trait loci (QTL) with disease genome-wide association studies (GWAS) has proven successful at prioritizing candidate genes at disease-associated loci. QTL mapping has mainly been focused on multi-tissue expression QTL or plasma protein QTL (pQTL). Here we generated the largest-to-date cerebrospinal fluid (CSF) pQTL atlas by analyzing 7,028 proteins in 3,107 samples. We identified 3,373 independent study-wide associations for 1,961 proteins, including 2,448 novel pQTLs of which 1,585 are unique to CSF, demonstrating unique genetic regulation of the CSF proteome. In addition to the established chr6p22.2-21.32 HLA region, we identified pleiotropic regions on chr3q28 near OSTN and chr19q13.32 near APOE that were enriched for neuron-specificity and neurological development. We also integrated this pQTL atlas with the latest Alzheimer's disease (AD) GWAS through PWAS, colocalization and Mendelian Randomization and identified 42 putative causal proteins for AD, 15 of which have drugs available. Finally, we developed a proteomics-based risk score for AD that outperforms genetics-based polygenic risk scores. These findings will be instrumental to further understand the biology and identify causal and druggable proteins for brain and neurological traits.

PET imaging of TREM1 identifies CNS-infiltrating myeloid cells in a mouse model of multiple sclerosis.

Multiple sclerosis (MS) is an immune-mediated demyelinating disease of the central nervous system (CNS) that causes substantial morbidity and diminished quality of life. Evidence highlights the central role of myeloid lineage cells in the initiation and progression of MS. However, existing imaging strategies for detecting myeloid cells in the CNS cannot distinguish between beneficial and harmful immune responses. Thus, imaging strategies that specifically identify myeloid cells and their activation states are critical for MS disease staging and monitoring of therapeutic responses. We hypothesized that positron emission tomography (PET) imaging of triggering receptor expressed on myeloid cells 1 (TREM1) could be used to monitor deleterious innate immune responses and disease progression in the experimental autoimmune encephalomyelitis (EAE) mouse model of MS. We first validated TREM1 as a specific marker of proinflammatory, CNS-infiltrating, peripheral myeloid cells in mice with EAE. We show that the 64Cu-radiolabeled TREM1 antibody-based PET tracer monitored active disease with 14- to 17-fold higher sensitivity than translocator protein 18 kDa (TSPO)-PET imaging, the established approach for detecting neuroinflammation in vivo. We illustrate the therapeutic potential of attenuating TREM1 signaling both genetically and pharmacologically in the EAE mice and show that TREM1-PET imaging detected responses to an FDA-approved MS therapy with siponimod (BAF312) in these animals. Last, we observed TREM1+ cells in clinical brain biopsy samples from two treatment-naïve patients with MS but not in healthy control brain tissue. Thus, TREM1-PET imaging has potential for aiding in the diagnosis of MS and monitoring of therapeutic responses to drug treatment.

Biogeography and evolution of social parasitism in Australian Myrmecia bulldog ants revealed by phylogenomics.

Studying the historical biogeography and life history transitions from eusocial colony life to social parasitism contributes to our understanding of the evolutionary mechanisms generating biodiversity in eusocial insects. The ants in the genus Myrmecia are a well-suited system for testing evolutionary hypotheses about how their species diversity was assembled through time because the genus is endemic to Australia with the single exception of the species M. apicalis inhabiting the Pacific Island of New Caledonia, and because at least one social parasite species exists in the genus. However, the evolutionary mechanisms underlying the disjunct biogeographic distribution of M. apicalis and the life history transition(s) to social parasitism remain unexplored. To study the biogeographic origin of the isolated, oceanic species M. apicalis and to reveal the origin and evolution of social parasitism in the genus, we reconstructed a comprehensive phylogeny of the ant subfamily Myrmeciinae. We utilized Ultra Conserved Elements (UCEs) as molecular markers to generate a molecular genetic dataset consisting of 2,287 loci per taxon on average for 66 out of the 93 known Myrmecia species as well as for the sister lineage Nothomyrmecia macrops and selected outgroups. Our time-calibrated phylogeny inferred that: (i) stem Myrmeciinae originated during the Paleocene âˆ¼ 58 Ma ago; (ii) the current disjunct biogeographic distribution of M. apicalis was driven by long-distance dispersal from Australia to New Caledonia during the Miocene âˆ¼ 14 Ma ago; (iii) the single social parasite species, M. inquilina, evolved directly from one of the two known host species, M. nigriceps, in sympatry via the intraspecific route of social parasite evolution; and (iv) 5 of the 9 previously established taxonomic species groups are non-monophyletic. We suggest minor changes to reconcile the molecular phylogenetic results with the taxonomic classification. Our study enhances our understanding of the evolution and biogeography of Australian bulldog ants, contributes to our knowledge about the evolution of social parasitism in ants, and provides a solid phylogenetic foundation for future inquiries into the biology, taxonomy, and classification of Myrmeciinae.

Cost-Effectiveness and Value of Information Analysis of an Ambient Intelligent Geriatric Management (AmbIGeM) System Compared to Usual Care to Prevent Falls in Older People in Hospitals.

BACKGROUND: The Ambient Intelligent Geriatric Management (AmbIGeM) system combines wearable sensors with artificial intelligence to trigger alerts to hospital staff before a fall. A clinical trial found no effect across a heterogenous population, but reported a reduction in the injurious falls rate in a post hoc analysis of patients on Geriatric Evaluation Management Unit (GEMU) wards. Cost-effectiveness and Value of Information (VoI) analyses of the AmbIGeM system in GEMU wards was undertaken. METHODS: An Australian health-care system perspective and 5-year time horizon were used for the cost-effectiveness analysis. Implementation costs, inpatient costs and falls data were collected. Injurious falls were defined as causing bruising, laceration, fracture, loss of consciousness, or if the patient reported persistent pain. To compare costs and outcomes, generalised linear regression models were used to adjust for baseline differences between the intervention and usual care groups. Bootstrapping was used to represent uncertainty. For the VoI analysis, 10,000 different sample sizes with randomly sampled values ranging from 1 to 50,000 were tested to estimate the optimal sample size of a new trial that maximised the Expected Net Benefits of Sampling. RESULTS: An adjusted 0.036 fewer injurious falls (adjusted rate ratio of 0.56) and AUD$4554 lower costs were seen in the intervention group. However, uncertainty that the intervention is cost effective for the prevention of an injurious fall was present at all monetary values of this effectiveness outcome. A new trial with a sample of 4376 patients was estimated to maximise the Expected Net Benefit of Sampling, generating a net benefit of AUD$186,632 at a benefit-to-cost ratio of 1.1. CONCLUSIONS: The benefits to cost ratio suggests that a new trial of the AmbIGeM system in GEMU wards may not be high-value compared to other potential trials, and that the system should be implemented. However, a broader analysis of options for preventing falls in GEMU is required to fully inform decision making. TRIAL REGISTRATION: Australian and New Zealand Clinical Trial Registry (ACTRN 12617000981325).

Performance of a fully-automated Lumipulse plasma phospho-tau181 assay for Alzheimer's disease.

BACKGROUND: The recent promise of disease-modifying therapies for Alzheimer's disease (AD) has reinforced the need for accurate biomarkers for early disease detection, diagnosis and treatment monitoring. Advances in the development of novel blood-based biomarkers for AD have revealed that plasma levels of tau phosphorylated at various residues are specific and sensitive to AD dementia. However, the currently available tests have shortcomings in access, throughput, and scalability that limit widespread implementation. METHODS: We evaluated the diagnostic and prognostic performance of a high-throughput and fully-automated Lumipulse plasma p-tau181 assay for the detection of AD. Plasma from older clinically unimpaired individuals (CU, n = 463) and patients with mild cognitive impairment (MCI, n = 107) or AD dementia (n = 78) were obtained from the longitudinal Stanford University Alzheimer's Disease Research Center (ADRC) and the Stanford Aging and Memory Study (SAMS) cohorts. We evaluated the discriminative accuracy of plasma p-tau181 for clinical AD diagnosis, association with amyloid ß peptides and p-tau181 concentrations in CSF, association with amyloid positron emission tomography (PET), and ability to predict longitudinal cognitive and functional change. RESULTS: The assay showed robust performance in differentiating AD from control participants (AUC 0.959, CI: 0.912 to 0.990), and was strongly associated with CSF p-tau181, CSF Aß42/Aß40 ratio, and amyloid-PET global SUVRs. Associations between plasma p-tau181 with CSF biomarkers were significant when examined separately in Aß+ and Aß- groups. Plasma p-tau181 significantly increased over time in CU and AD diagnostic groups. After controlling for clinical diagnosis, age, sex, and education, baseline plasma p-tau181 predicted change in MoCA overall and change in CDR Sum of Boxes in the AD group over follow-up of up to 5 years. CONCLUSIONS: This fully-automated and available blood-based biomarker assay therefore may be useful for early detection, diagnosis, prognosis, and treatment monitoring of AD.

α-Synuclein Seed Amplification in CSF and Brain from Patients with Different Brain Distributions of Pathological α-Synuclein in the Context of Co-Pathology and Non-LBD Diagnoses.

OBJECTIVE: The purpose of this study was to determine the sensitivity and specificity of α-synuclein seed amplification assay (αSyn-SAA) in antemortem and postmortem cerebrospinal fluid (CSF) of autopsy-confirmed patients with different distributions of pathological αSyn, co-pathologies, and clinical diagnoses. METHODS: The αSyn-SAA was used to test antemortem CSF samples from 119 subjects with a variety of clinical syndromes and standardized neuropathological examinations from Oregon Health and Science University (OHSU) and University of California San Diego (UCSD; 56 additional postmortem CSF samples available). The αSyn-SAA was also applied to frontal cortex and amygdala homogenates. Sensitivity and specificity were compared across distributions of αSyn pathology. Clinical data and co-pathologies were compared across αSyn-SAA positive and negative groups. RESULTS: Fifty-three individuals without and 66 with αSyn-pathology (neocortical [n = 38], limbic [n = 7], and amygdala-predominant [n = 21]) were included. There was a sensitivity of 97.8% and specificity of 98.1% of the αSyn-SAA to identify patients with limbic/neocortical pathology from antemortem CSF. Sensitivity to detect amygdala-predominant pathology was only 14.3%. Postmortem CSF and brain tissue αSyn-SAA analyses also showed higher assay positivity in samples from limbic/neocortical cases. INTERPRETATION: CSF αSyn-SAA reliably identifies αSyn seeds in patients with diffuse αSyn pathology in the context of co-pathology and non-Lewy body disease (LBD) diagnoses. The analysis of brain homogenates suggests that pathological αSyn in the amygdala might differ from pathological αSyn in the frontal cortex. The αSyn-SAA might facilitate the differential diagnosis of dementias with mixed pathologies. ANN NEUROL 2022;92:650-662.

Value of Information Analysis in Models to Inform Health Policy.

Value of information (VoI) is a decision-theoretic approach to estimating the expected benefits from collecting further information of different kinds, in scientific problems based on combining one or more sources of data. VoI methods can assess the sensitivity of models to different sources of uncertainty and help to set priorities for further data collection. They have been widely applied in healthcare policy making, but the ideas are general to a range of evidence synthesis and decision problems. This article gives a broad overview of VoI methods, explaining the principles behind them, the range of problems that can be tackled with them, and how they can be implemented, and discusses the ongoing challenges in the area.