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The rapid increase in lipidomic studies has led to a collaborative effort within the community to establish standards and criteria for producing, documenting, and disseminating data. Creating a dynamic easy-to-use checklist that condenses key information about lipidomic experiments into common terminology will enhance the field's consistency, comparability, and repeatability. Here, we describe the structure and rationale of the established Lipidomics Minimal Reporting Checklist to increase transparency in lipidomics research.

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The metabotropic glutamate receptors (mGluRs) are neuromodulatory family C G protein coupled receptors which assemble as dimers and allosterically couple extracellular ligand binding domains (LBDs) to transmembrane domains (TMDs) to drive intracellular signaling. Pharmacologically, mGluRs can be targeted at the LBDs by glutamate and synthetic orthosteric compounds or at the TMDs by allosteric modulators. Despite the potential of allosteric compounds as therapeutics, an understanding of the functional and structural basis of their effects is limited. Here we use multiple approaches to dissect the functional and structural effects of orthosteric versus allosteric ligands. We find, using electrophysiological and live cell imaging assays, that both agonists and positive allosteric modulators (PAMs) can drive activation and internalization of group II and III mGluRs. The effects of PAMs are pleiotropic, boosting the maximal response to orthosteric agonists and serving independently as internalization-biased agonists across mGluR subtypes. Motivated by this and intersubunit FRET analyses, we determine cryo-electron microscopy structures of mGluR3 in the presence of either an agonist or antagonist alone or in combination with a PAM. These structures reveal PAM-driven re-shaping of intra- and inter-subunit conformations and provide evidence for a rolling TMD dimer interface activation pathway that controls G protein and beta-arrestin coupling.

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Inflammation is an important factor in Alzheimer's disease (AD). An NMR measurement in plasma, glycoprotein acetyls (GlycA), captures the overall level of protein production and glycosylation implicated in systemic inflammation. With its additional advantage of reducing biological variability, GlycA might be useful in monitoring the relationship between peripheral inflammation and brain changes relevant to AD. However, the associations between GlycA and these brain changes have not been fully evaluated. Here, we performed Spearman's correlation analyses to evaluate these associations cross-sectionally and determined whether GlycA can inform AD-relevant longitudinal measurements among participants in the Alzheimer's Disease Neuroimaging Initiative (n = 1506), with additional linear models and stratification analyses to evaluate the influences of sex or diagnosis status and confirm findings from Spearman's correlation analyses. We found that GlycA was elevated in AD patients compared to cognitively normal participants. GlycA correlated negatively with multiple concurrent regional brain volumes in females diagnosed with late mild cognitive impairment (LMCI) or AD. Baseline GlycA level was associated with executive function decline at 3-9 year follow-up in participants diagnosed with LMCI at baseline, with similar but not identical trends observed in the future decline of memory and entorhinal cortex volume. Results here indicated that GlycA is an inflammatory biomarker relevant to AD pathogenesis and that the stage of LMCI might be relevant to inflammation-related intervention.

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Alzheimer's disease (AD) is influenced by a variety of modifiable risk factors, including a person's dietary habits. While the ketogenic diet (KD) holds promise in reducing metabolic risks and potentially affecting AD progression, only a few studies have explored KD's metabolic impact, especially on blood and cerebrospinal fluid (CSF). Our study involved participants at risk for AD, either cognitively normal or with mild cognitive impairment. The participants consumed both a modified Mediterranean Ketogenic Diet (MMKD) and the American Heart Association diet (AHAD) for 6 weeks each, separated by a 6-week washout period. We employed nuclear magnetic resonance (NMR)-based metabolomics to profile serum and CSF and metagenomics profiling on fecal samples. While the AHAD induced no notable metabolic changes, MMKD led to significant alterations in both serum and CSF. These changes included improved modifiable risk factors, like increased HDL-C and reduced BMI, reversed serum metabolic disturbances linked to AD such as a microbiome-mediated increase in valine levels, and a reduction in systemic inflammation. Additionally, the MMKD was linked to increased amino acid levels in the CSF, a breakdown of branched-chain amino acids (BCAAs), and decreased valine levels. Importantly, we observed a strong correlation between metabolic changes in the CSF and serum, suggesting a systemic regulation of metabolism. Our findings highlight that MMKD can improve AD-related risk factors, reverse some metabolic disturbances associated with AD, and align metabolic changes across the blood-CSF barrier.

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BACKGROUND: Accurate risk stratification is vital for primary prevention of cardiovascular disease (CVD). However, traditional tools such as the Framingham Risk Score (FRS) may underperform within the diverse intermediate-risk group, which includes individuals requiring distinct management strategies. OBJECTIVES: This study aimed to develop a lipidomic-enhanced risk score (LRS), specifically targeting risk prediction and reclassification within the intermediate group, benchmarked against the FRS. METHODS: The LRS was developed via a machine learning workflow using ridge regression on the Australian Diabetes, Obesity, and Lifestyle Study (AusDiab; n = 10,339). It was externally validated with the Busselton Health Study (n = 4,492), and its predictive utility for coronary artery calcium scoring (CACS)-based outcomes was independently validated in the BioHEART cohort (n = 994). RESULTS: LRS significantly improved discrimination metrics for the intermediate-risk group in both AusDiab and Busselton Health Study cohorts (all P < 0.001), increasing the area under the curve for CVD events by 0.114 (95% CI: 0.1123-0.1157) and 0.077 (95% CI: 0.0755-0.0785), with a net reclassification improvement of 0.36 (95% CI: 0.21-0.51) and 0.33 (95% CI: 0.15-0.49), respectively. For CACS-based outcomes in BioHEART, LRS achieved a significant area under the curve improvement of 0.02 over the FRS (0.76 vs 0.74; P < 1.0 × 10-5). A simplified, clinically applicable version of LRS was also created that had comparable performance to the original LRS. CONCLUSIONS: LRS, augmenting the FRS, presents potential to improve intermediate-risk stratification and to predict atherosclerotic markers using a simple blood test, suitable for clinical application. This could facilitate the triage of individuals for noninvasive imaging such as CACS, fostering precision medicine in CVD prevention and management.

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PURPOSE: Intense androgen deprivation therapy (ADT) with androgen receptor pathway inhibitors (ARPIs) before radical prostatectomy (RP) produced favorable pathologic responses in approximately 20% of patients. The molecular reason for the low rate of response remains unclear. Lipid metabolism is known to influence androgen receptor signaling and ARPI efficacy. The aim of the study was to identify circulating lipid profiles associated with ADT/ARPI resistance in localized prostate cancer. MATERIALS AND METHODS: Two independent experimental approaches were used. Experiment 1: Post hoc analysis of the association between plasma lipidomic profiles and ADT/ARPI response was performed on patients (n = 104) from two phase II trials of neoadjuvant ADT/ARPI. Response to ADT/ARPI was defined by pathologic response. Experiment 2: Patient-derived tumor explants from RP (n = 105) were cultured in enzalutamide for 48 hours. Explant response to enzalutamide was evaluated against pre-RP plasma lipidomic profiles (n = 105) and prostate tissue lipidomic profiles (n = 36). Response was defined by Ki67 (cell proliferation marker) fold difference between enzalutamide and vehicle-treated explants. In both experiments, associations between lipid profiles and ADT/ARPI response were analyzed by latent class analysis. RESULTS: Pretreatment plasma lipid profiles classified each experimental cohort into two groups with differences in ADT/ARPI response rates. The response rates of the groups were 9.6% versus 29% in experiment 1 (chi-squared test P = .012) and 49% versus 70% in experiment 2 (chi-squared test P = .037). In both experiments, the group with a higher incidence of ADT/ARPI resistance had higher plasma levels of sphingomyelin, glycosylceramides, free fatty acids, acylcarnitines, cholesterol esters, and alkyl/alkenyl-phosphatidylcholine and lower plasma levels of triacylglycerols, diacylglycerols, and phosphoethanolamine (t-test P < .05). CONCLUSION: Pretreatment circulating lipid profiles are associated with ADT/ARPI resistance in localized cancer in both human cohorts and explant models.

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G protein-coupled receptors (GPCRs) control intracellular signaling cascades via agonist-dependent coupling to intracellular transducers including heterotrimeric G proteins, GPCR kinases (GRKs), and arrestins. In addition to their critical interactions with the transmembrane core of active GPCRs, all three classes of transducers have also been reported to interact with receptor C-terminal domains (CTDs). An underexplored aspect of GPCR CTDs is their possible role as lipid sensors given their proximity to the membrane. CTD-membrane interactions have the potential to control the accessibility of key regulatory CTD residues to downstream effectors and transducers. Here, we report that the CTDs of two closely related family C GPCRs, metabotropic glutamate receptor 2 (mGluR2) and mGluR3, bind to membranes and that this interaction can regulate receptor function. We first characterize CTD structure with NMR spectroscopy, revealing lipid composition-dependent modes of membrane binding. Using molecular dynamics simulations and structure-guided mutagenesis, we then identify key conserved residues and cancer-associated mutations that modulate CTD-membrane binding. Finally, we provide evidence that mGluR3 transducer coupling is controlled by CTD-membrane interactions in live cells, which may be subject to regulation by CTD phosphorylation and changes in membrane composition. This work reveals an additional mechanism of GPCR modulation, suggesting that CTD-membrane binding may be a general regulatory mode throughout the broad GPCR superfamily.

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BACKGROUND: Decreased levels of circulating ethanolamine plasmalogens [PE(P)], and a concurrent increase in phosphatidylethanolamine (PE) are consistently reported in various cardiometabolic conditions. Here we devised, a plasmalogen score (Pls Score) that mirrors a metabolic signal that encompasses the levels of PE(P) and PE and captures the natural variation in circulating plasmalogens and perturbations in their metabolism associated with disease, diet, and lifestyle. METHODS: We utilised, plasma lipidomes from the Australian Obesity, Diabetes and Lifestyle study (AusDiab; n = 10,339, 55% women) a nationwide cohort, to devise the Pls Score and validated this in the Busselton Health Study (BHS; n = 4,492, 56% women, serum lipidome) and in a placebo-controlled crossover trial involving Shark Liver Oil (SLO) supplementation (n = 10, 100% men). We examined the association of the Pls Score with cardiometabolic risk factors, type 2 diabetes mellitus (T2DM), cardiovascular disease and all-cause mortality (over 17 years). FINDINGS: In a model, adjusted for age, sex and BMI, individuals in the top quintile of the Pls Score (Q5) relative to Q1 had an OR of 0.31 (95% CI 0.21-0.43), 0.39 (95% CI 0.25-0.61) and 0.42 (95% CI 0.30-0.57) for prevalent T2DM, incident T2DM and prevalent cardiovascular disease respectively, and a 34% lower mortality risk (HR = 0.66; 95% CI 0.56-0.78). Significant associations between diet and lifestyle habits and Pls Score exist and these were validated through dietary supplementation of SLO that resulted in a marked change in the Pls Score. INTERPRETATION: The Pls Score as a measure that captures the natural variation in circulating plasmalogens, was not only inversely related to cardiometabolic risk and all-cause mortality but also associate with diet and lifestyle. Our results support the potential utility of the Pls Score as a biomarker for metabolic health and its responsiveness to dietary interventions. Further research is warranted to explore the underlying mechanisms and optimise the practical implementation of the Pls Score in clinical and population settings. FUNDING: National Health and Medical Research Council (NHMRC grant 233200), National Health and Medical Research Council of Australia (Project grant APP1101320), Health Promotion Foundation of Western Australia, and National Health and Medical Research Council of Australia Senior Research Fellowship (#1042095).

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BACKGROUND: Metabolic ageing biomarkers may capture the age-related shifts in metabolism, offering a precise representation of an individual's overall metabolic health. METHODS: Utilising comprehensive lipidomic datasets from two large independent population cohorts in Australia (n = 14,833, including 6630 males, 8203 females), we employed different machine learning models, to predict age, and calculated metabolic age scores (mAge). Furthermore, we defined the difference between mAge and age, termed mAgeΔ, which allow us to identify individuals sharing similar age but differing in their metabolic health status. FINDINGS: Upon stratification of the population into quintiles by mAgeΔ, we observed that participants in the top quintile group (Q5) were more likely to have cardiovascular disease (OR = 2.13, 95% CI = 1.62-2.83), had a 2.01-fold increased risk of 12-year incident cardiovascular events (HR = 2.01, 95% CI = 1.45-2.57), and a 1.56-fold increased risk of 17-year all-cause mortality (HR = 1.56, 95% CI = 1.34-1.79), relative to the individuals in the bottom quintile group (Q1). Survival analysis further revealed that men in the Q5 group faced the challenge of reaching a median survival rate due to cardiovascular events more than six years earlier and reaching a median survival rate due to all-cause mortality more than four years earlier than men in the Q1 group. INTERPRETATION: Our findings demonstrate that the mAge score captures age-related metabolic changes, predicts health outcomes, and has the potential to identify individuals at increased risk of metabolic diseases. FUNDING: The specific funding of this article is provided in the acknowledgements section.

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An animal's skin provides a first point of contact with the sensory environment, including noxious cues that elicit protective behavioral responses. Nociceptive somatosensory neurons densely innervate and intimately interact with epidermal cells to receive these cues, however the mechanisms by which epidermal interactions shape processing of noxious inputs is still poorly understood. Here, we identify a role for dendrite intercalation between epidermal cells in tuning sensitivity of Drosophila larvae to noxious mechanical stimuli. In wild-type larvae, dendrites of nociceptive class IV da neurons intercalate between epidermal cells at apodemes, which function as body wall muscle attachment sites, but not at other sites in the epidermis. From a genetic screen we identified miR-14 as a regulator of dendrite positioning in the epidermis: miR-14 is expressed broadly in the epidermis but not in apodemes, and miR-14 inactivation leads to excessive apical dendrite intercalation between epidermal cells. We found that miR-14 regulates expression and distribution of the epidermal Innexins ogre and Inx2 and that these epidermal gap junction proteins restrict epidermal dendrite intercalation. Finally, we found that altering the extent of epidermal dendrite intercalation had corresponding effects on nociception: increasing epidermal intercalation sensitized larvae to noxious mechanical inputs and increased mechanically evoked calcium responses in nociceptive neurons, whereas reducing epidermal dendrite intercalation had the opposite effects. Altogether, these studies identify epidermal dendrite intercalation as a mechanism for mechanical coupling of nociceptive neurons to the epidermis, with nociceptive sensitivity tuned by the extent of intercalation.

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The cellular lipidome comprises thousands of unique lipid species. Here, using mass spectrometry-based targeted lipidomics, we characterize the lipid landscape of human and mouse immune cells ( www.cellularlipidatlas.com ). Using this resource, we show that immune cells have unique lipidomic signatures and that processes such as activation, maturation and development impact immune cell lipid composition. To demonstrate the potential of this resource to provide insights into immune cell biology, we determine how a cell-specific lipid trait-differences in the abundance of polyunsaturated fatty acid-containing glycerophospholipids (PUFA-PLs)-influences immune cell biology. First, we show that differences in PUFA-PL content underpin the differential susceptibility of immune cells to ferroptosis. Second, we show that low PUFA-PL content promotes resistance to ferroptosis in activated neutrophils. In summary, we show that the lipid landscape is a defining feature of immune cell identity and that cell-specific lipid phenotypes underpin aspects of immune cell physiology.

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BACKGROUND: L-[methyl-11C]-methionine-positron emission tomography (Met-PET) is a potentially important imaging adjunct in the diagnostic workup of pituitary adenomas, including somatotroph tumors. Met-PET can identify residual or occult disease and make definitive therapies accessible to a subgroup of patients who would otherwise require lifelong medical therapy. However, existing data on its use are still limited to small case series. Here, we report the largest single-center experience (n = 61) in acromegaly. METHODS: A total of 189 cases of acromegaly were referred to our national Met-PET service in the last 12 years. For this analysis, we have reviewed outcomes in those 61 patients managed exclusively by our multidisciplinary team (single center, single surgeon). Referral indications were as follows: indeterminate magnetic resonance imaging (MRI; n = 38, 62.3%), occult residual (n = 14, 23.0%), (radio-)surgical planning (n = 6, 9.8%), and occult de novo tumor (n = 3, 4.9%). RESULTS: A total of 33/61 patients (54.1%) underwent PET-guided surgery. Twenty-four of 33 patients (72.7%) achieved complete biochemical remission following (re-)surgery. Insulin-like growth factor 1 levels were reduced to <2 × upper limit of normal (ULN) in 6 of the remaining 9 cases, 3 of whom achieved levels of <1.1 × ULN compared with mean preoperative levels of 2.4 × ULN (SD 0.8) for n = 9. Only 3 patients developed single new hormonal deficits (gonadotropic/thyrotropic insufficiency). There were no neurovascular complications after surgery. CONCLUSION: In patients with persistent/recurrent acromegaly or occult tumors, Met-PET can facilitate further targeted intervention (surgery/radiosurgery). This led to complete remission in most cases (24/33) or significant improvement with comparatively low risk of complications. L-[methyl-11C]-methionine-positron emission tomography should therefore be considered in all patients who are potential candidates for further surgical intervention but present no clear target on MRI.

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Recent advancements in plasma lipidomic profiling methodology have significantly increased specificity and accuracy of lipid measurements. This evolution, driven by improved chromatographic and mass spectrometric resolution of newer platforms, has made it challenging to align datasets created at different times, or on different platforms. Here we present a framework for harmonising such plasma lipidomic datasets with different levels of granularity in their lipid measurements. Our method utilises elastic-net prediction models, constructed from high-resolution lipidomics reference datasets, to predict unmeasured lipid species in lower-resolution studies. The approach involves (1) constructing composite lipid measures in the reference dataset that map to less resolved lipids in the target dataset, (2) addressing discrepancies between aligned lipid species, (3) generating prediction models, (4) assessing their transferability into the targe dataset, and (5) evaluating their prediction accuracy. To demonstrate our approach, we used the AusDiab population-based cohort (747 lipid species) as the reference to impute unmeasured lipid species into the LIPID study (342 lipid species). Furthermore, we compared measured and imputed lipids in terms of parameter estimation and predictive performance, and validated imputations in an independent study. Our method for harmonising plasma lipidomic datasets will facilitate model validation and data integration efforts.

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AIM: To harmonize two ascertainment and severity rating instruments commonly used for the clinical high risk syndrome for psychosis (CHR-P): the Structured Interview for Psychosis-risk Syndromes (SIPS) and the Comprehensive Assessment of At-Risk Mental States (CAARMS). METHODS: The initial workshop is described in the companion report from Addington et al. After the workshop, lead experts for each instrument continued harmonizing attenuated positive symptoms and criteria for psychosis and CHR-P through an intensive series of joint videoconferences. RESULTS: Full harmonization was achieved for attenuated positive symptom ratings and psychosis criteria, and modest harmonization for CHR-P criteria. The semi-structured interview, named Positive SYmptoms and Diagnostic Criteria for the CAARMS Harmonized with the SIPS (PSYCHS), generates CHR-P criteria and severity scores for both CAARMS and SIPS. CONCLUSIONS: Using the PSYCHS for CHR-P ascertainment, conversion determination, and attenuated positive symptom severity rating will help in comparing findings across studies and in meta-analyses.

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INTRODUCTION: The role of different femoral head materials for total hip arthroplasty (THA) has been widely studied in the context of wear properties and corrosion. Cobalt chrome (CoCr) femoral heads are commonly used as a standard of comparison to other materials such as ceramic and oxidized zirconium (OxZi). This study aims to evaluate the impact of femoral head material on clinical outcomes in elective primary THA patients. METHODS: Retrospective analysis of THA patients within the Medicare claims database between October 2017 and September 2020 using diagnosis-related group codes was conducted. Information collected included sex, age, Charlson Comorbidity Index, and femoral head type. Patients with CoCr femoral heads were compared against patients with either OxZi or ceramic femoral heads using 1:1 propensity score matching. Z-testing and Chi-square analysis were used to determine between-group significance. RESULTS: In total, 112,960 elective THA patients were included, with 56,480 in OxZi or ceramic and 56,480 in CoCr. Readmission rates were lower in patients that received OxZi or ceramic femoral heads at 30-day (p < 0.0001), 60-day (p < 0.0001), and 90-day postoperatively (p < 0.0001) compared to CoCr. Mortality rates were also lower in patients that received OxZi or ceramic femoral heads at 30-day (p = 0.004), 60-day (p = 0.018), and 90-day postoperatively (p = 0.009) compared to CoCr. CONCLUSION: CoCr femoral heads had higher rates of readmissions and mortality compared to OxZi or ceramic. Further analysis of bearing surface combinations and sub-group analyses to determine significance between-group differences is needed. LEVEL III EVIDENCE: Retrospective analysis.

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BACKGROUND: Using comprehensive plasma lipidomic profiling from men with metastatic castration-resistant prostate cancer (mCRPC), we have previously identified a poor-prognostic lipid profile associated with shorter overall survival (OS). In order to translate this biomarker into the clinic, these men must be identifiable via a clinically accessible, regulatory-compliant assay. METHODS: A single regulatory-compliant liquid chromatography-mass spectrometry assay of candidate lipids was developed and tested on a mCRPC Discovery cohort of 105 men. Various risk-score Cox regression prognostic models of OS were built using the Discovery cohort. The model with the highest concordance index (PCPro) was chosen for validation and tested on an independent Validation cohort of 183 men. RESULTS: PCPro, the lipid biomarker, contains Cer(d18:1/18:0), Cer(d18:1/24:0), Cer(d18:1/24:1), triglycerides and total cholesterol. Within the Discovery and Validation cohorts, men who were PCPro positive had significantly shorter OS compared to those who were PCPro negative (Discovery: median OS 12.0 months vs 24.2 months, hazard ratio (HR) 3.75 [95% confidence interval (CI) 2.29-6.15], p < 0.001, Validation: median OS 13.0 months vs 25.7 months, HR = 2.13 [95% CI 1.46-3.12], p < 0.001). CONCLUSIONS: We have developed PCPro, a lipid biomarker assay capable of prospectively identifying men with mCRPC with a poor prognosis. Prospective clinical trials are required to determine if men who are PCPro positive will benefit from therapeutic agents targeting lipid metabolism.

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Alzheimer's disease (AD) is influenced by a variety of modifiable risk factors, including a person's dietary habits. While the ketogenic diet (KD) holds promise in reducing metabolic risks and potentially affecting AD progression, only a few studies have explored KD's metabolic impact, especially on blood and cerebrospinal fluid (CSF). Our study involved participants at risk for AD, either cognitively normal or with mild cognitive impairment. The participants consumed both a modified Mediterranean-ketogenic diet (MMKD) and the American Heart Association diet (AHAD) for 6 weeks each, separated by a 6-week washout period. We employed nuclear magnetic resonance (NMR)-based metabolomics to profile serum and CSF and metagenomics profiling on fecal samples. While the AHAD induced no notable metabolic changes, MMKD led to significant alterations in both serum and CSF. These changes included improved modifiable risk factors, like increased HDL-C and reduced BMI, reversed serum metabolic disturbances linked to AD such as a microbiome-mediated increase in valine levels, and a reduction in systemic inflammation. Additionally, the MMKD was linked to increased amino acid levels in the CSF, a breakdown of branched-chain amino acids (BCAAs), and decreased valine levels. Importantly, we observed a strong correlation between metabolic changes in the CSF and serum, suggesting a systemic regulation of metabolism. Our findings highlight that MMKD can improve AD-related risk factors, reverse some metabolic disturbances associated with AD, and align metabolic changes across the blood-CSF barrier.

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The dNTPase activity of tetrameric SAM and HD domain containing deoxynucleoside triphosphate triphosphohydrolase 1 (SAMHD1) plays a critical role in cellular dNTP regulation. SAMHD1 also associates with stalled DNA replication forks, DNA repair foci, ssRNA and telomeres. The above functions require nucleic acid binding by SAMHD1, which may be modulated by its oligomeric state. Here we establish in cryo-EM and biochemical studies that the guanine-specific A1 activator site of each SAMHD1 monomer is used to target the enzyme to guanine nucleotides within single-stranded (ss) DNA and RNA. Remarkably, nucleic acid strands containing a single guanine base induce dimeric SAMHD1, while two or more guanines with ∼20 nucleotide spacing induce a tetrameric form. A cryo-EM structure of ssRNA-bound tetrameric SAMHD1 shows how ssRNA strands bridge two SAMHD1 dimers and stabilize the structure. This ssRNA-bound tetramer is inactive with respect to dNTPase and RNase activity.

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Obesity is a risk factor for type 2 diabetes and cardiovascular disease. However, a substantial proportion of patients with these conditions have a seemingly normal body mass index (BMI). Conversely, not all obese individuals present with metabolic disorders giving rise to the concept of "metabolically healthy obese". We use lipidomic-based models for BMI to calculate a metabolic BMI score (mBMI) as a measure of metabolic dysregulation associated with obesity. Using the difference between mBMI and BMI (mBMIΔ), we identify individuals with a similar BMI but differing in their metabolic health and disease risk profiles. Exercise and diet associate with mBMIΔ suggesting the ability to modify mBMI with lifestyle intervention. Our findings show that, the mBMI score captures information on metabolic dysregulation that is independent of the measured BMI and so provides an opportunity to assess metabolic health to identify "at risk" individuals for targeted intervention and monitoring.

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BACKGROUND: Deep learning has shown potential in various scientific domains but faces challenges when applied to complex, high-dimensional multi-omics data. Alzheimer's Disease (AD) is a neurodegenerative disorder that lacks targeted therapeutic options. This study introduces the Circular-Sliding Window Association Test (c-SWAT) to improve the classification accuracy in predicting AD using serum-based metabolomics data, specifically lipidomics. METHODS: The c-SWAT methodology builds upon the existing Sliding Window Association Test (SWAT) and utilizes a three-step approach: feature correlation analysis, feature selection, and classification. Data from 997 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) served as the basis for model training and validation. Feature correlations were analyzed using Weighted Gene Co-expression Network Analysis (WGCNA), and Convolutional Neural Networks (CNN) were employed for feature selection. Random Forest was used for the final classification. FINDINGS: The application of c-SWAT resulted in a classification accuracy of up to 80.8% and an AUC of 0.808 for distinguishing AD from cognitively normal older adults. This marks a 9.4% improvement in accuracy and a 0.169 increase in AUC compared to methods without c-SWAT. These results were statistically significant, with a p-value of 1.04 × 10ˆ-4. The approach also identified key lipids associated with AD, such as Cer(d16:1/22:0) and PI(37:6). INTERPRETATION: Our results indicate that c-SWAT is effective in improving classification accuracy and in identifying potential lipid biomarkers for AD. These identified lipids offer new avenues for understanding AD and warrant further investigation. FUNDING: The specific funding of this article is provided in the acknowledgements section.

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