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Non-genetic mechanisms have recently emerged as important drivers of cancer therapy failure1, where some cancer cells can enter a reversible drug-tolerant persister state in response to treatment2. Although most cancer persisters remain arrested in the presence of the drug, a rare subset can re-enter the cell cycle under constitutive drug treatment. Little is known about the non-genetic mechanisms that enable cancer persisters to maintain proliferative capacity in the presence of drugs. To study this rare, transiently resistant, proliferative persister population, we developed Watermelon, a high-complexity expressed barcode lentiviral library for simultaneous tracing of each cell’s clonal origin and proliferative and transcriptional states. Here we show that cycling and non-cycling persisters arise from different cell lineages with distinct transcriptional and metabolic programs. Upregulation of antioxidant gene programs and a metabolic shift to fatty acid oxidation are associated with persister proliferative capacity across multiple cancer types. Impeding oxidative stress or metabolic reprogramming alters the fraction of cycling persisters. In human tumours, programs associated with cycling persisters are induced in minimal residual disease in response to multiple targeted therapies. The Watermelon system enabled the identification of rare persister lineages that are preferentially poised to proliferate under drug pressure, thus exposing new vulnerabilities that can be targeted to delay or even prevent disease recurrence. Lineage tracing by barcoding of individual cells using a lentivirus library shows that cycling and non-cycling drug-tolerant persister cells in cancer arise from different lineages with distinct transcriptional and metabolic programs.

Background: Observational studies in Parkinson’s disease (PD) have focused on relatively small numbers of research participants who are studied extensively. The Molecular Integration in Neurological Diagnosis Initiative at the University of Pennsylvania aims to characterize molecular and clinical features of PD in every patient in a large academic center. Objective: To determine the feasibility and interest in a global-capture biomarker research protocol. Additionally, to describe the clinical characteristics and GBA and LRRK2 variant carrier status among participants. Methods: All patients at UPenn with a clinical diagnosis of PD were eligible. Informed consent included options for access to the medical record, future recontact, and use of biosamples for additional studies. A blood sample and a completed questionnaire were obtained from participants. Targeted genotyping for four GBA and eight LRRK2 variants was performed, with plasma and DNA banked for future research. Results: Between September 2018 and December 2019, 704 PD patients were approached for enrollment; 652 (92.6%) enrolled, 28 (3.97%) declined, and 24 (3.41%) did not meet eligibility criteria. Median age was 69 (IQR 63_75) years, disease duration was 5.41 (IQR 2.49_9.95) years, and 11.10%of the cohort was non-white. Disease risk-associated variants in GBA were identified in 39 participants (5.98%) and in LRRK2 in 16 participants (2.45%). Conclusions: We report the clinical and genetic characteristics of PD patients in an all-comers, global capture protocol from an academic center. Patient interest in participation and yield for identification of GBA and LRRK2 mutation carriers is high, demonstrating feasibility of PD clinic-wide molecular characterization.

Brain metastases are refractory to therapies that control systemic disease in patients with human epidermal growth factor receptor 2 (HER2+) breast cancer, and the brain microenvironment contributes to this therapy resistance. Nutrient availability can vary across tissues, therefore metabolic adaptations required for brain metastatic breast cancer growth may introduce liabilities that can be exploited for therapy. Here, we assessed how metabolism differs between breast tumors in brain versus extracranial sites and found that fatty acid synthesis is elevated in breast tumors growing in brain. We determine that this phenotype is an adaptation to decreased lipid availability in brain relative to other tissues, resulting in a site-specific dependency on fatty acid synthesis for breast tumors growing at this site. Genetic or pharmacological inhibition of fatty acid synthase (FASN) reduces HER2+ breast tumor growth in the brain, demonstrating that differences in nutrient availability across metastatic sites can result in targetable metabolic dependencies.

ObjectiveTo determine whether patients with Lewy body dementia (LBD) with likely Alzheimer disease (AD)–type copathology are more impaired on confrontation naming than those without likely AD-type copathology.MethodsWe selected 57 patients with LBD (dementia with Lewy bodies [DLB], n = 38; Parkinson disease dementia [PDD], n = 19) with available AD CSF biomarkers and neuropsychological data. CSF β-amyloid1-42 (Aβ42), phosphorylated-tau (p-tau), and total-tau (t-tau) concentrations were measured. We used an autopsy-validated CSF cut point (t-tau:Aβ42 ratio > 0.3, n = 43), or autopsy data when available (n = 14), to categorize patients as having LBD with (LBD + AD, n = 26) and without (LBD − AD, n = 31) likely AD-type copathology. Analysis of covariance tested between-group comparisons across biologically defined groups (LBD + AD, LBD − AD) and clinical phenotypes (DLB, PDD) on confrontation naming (30-item Boston Naming Test [BNT]), executive abilities (letter fluency [LF], reverse digit span [RDS]), and global cognition (Mini-Mental State Examination [MMSE]), with adjustment for age at dementia onset, time from dementia onset to test date, and time from CSF to test date. Spearman correlation related cognitive performance to CSF analytes.ResultsPatients with LBD + AD performed worse on BNT than patients with LBD − AD (F = 4.80, p = 0.03); both groups performed similarly on LF, RDS, and MMSE (all p > 0.1). Clinically defined PDD and DLB groups did not differ in performance on any of these measures (all p > 0.05). A correlation across all patients showed that BNT score was negatively associated with CSF t-tau (ρ = −0.28, p < 0.05) and p-tau (ρ = −0.26, p = 0.05) but not Aβ42 (p > 0.1).ConclusionMarkers of AD-type copathology are implicated in impaired language performance in LBD. Biologically based classification of LBD may be advantageous over clinically defined syndromes to elucidate clinical heterogeneity.

ObjectivesTo investigate the impact of Alzheimer's disease (AD) co-pathology on an in vivo structural measure of neurodegeneration in Lewy body disorders (LBD).MethodsWe studied 72 LBD patients (Parkinson disease (PD)=2, PD-MCI=25, PD with dementia=10, dementia with Lewy bodies=35) with either CSF analysis or neuropathological examination and structural MRI during life. The cohort was divided into those harboring significant AD co-pathology, either at autopsy (intermediate/high AD neuropathologic change) or with CSF signature indicating AD co-pathology (t-tau/Aβ1-42 >0.3) (LBD+AD, N=19), and those without AD co-pathology (LBD-AD, N=53). We also included a reference group of 25 patients with CSF biomarker-confirmed amnestic AD. We investigated differences in MRI cortical thickness estimates between groups, and in the 21 autopsied LBD patients (LBD-AD=14, LBD+AD=7), directly tested the association between antemortem MRI and post-mortem burdens of tau, Aβ, and alpha-synuclein using digital histopathology in five representative neocortical regions.ResultsThe LBD+AD group was characterized by cortical thinning in anterior/medial and lateral temporal regions (P&nbsp

BackgroundCurrently available treatments for Parkinson’s disease (PD) do not slow clinical progression nor target alpha-synuclein, the main pathology associated with the disease.ObjectiveThe study objective was to evaluate the efficacy and safety of prasinezumab, a humanized monoclonal antibody that binds aggregated alpha-synuclein, in individuals with early PD. The study rationale, design, and baseline characteristics of enrolled subjects are presented here.MethodsThe PASADENA study is a multicenter, randomized, double-blind, placebo-controlled treatment study. Individuals with early PD, recruited across the US and Europe, received monthly intravenous doses of prasinezumab (1500 mg or 4500 mg) or placebo for a 52-week period (Part 1), followed by a 52-week extension (Part 2) in which all participants received active treatment. Key inclusion criteria were: aged 40–80 years; Hoehn & Yahr (H&Y) Stage I or II; time from diagnosis ≤2 years; having bradykinesia plus one other cardinal sign of PD (e.g. resting tremor, rigidity); DAT-SPECT imaging consistent with PD; and either treatment naïve or on a stable monoamine oxidase B (MAO-B) inhibitor dose. Study design assumptions for sample size and study duration were built using a patient cohort from the Parkinson’s Progression Marker Initiative (PPMI). In this report, baseline characteristics are compared between the treatment-naïve and MAO-B inhibitor-treated PASADENA cohorts and between the PASADENA and PPMI populations.ResultsOf the 443 patients screened, 316 were enrolled into the PASADENA study between June 2017 and November 2018, with an average age of 59.9 years and 67.4% being male. The mean time from diagnosis at baseline was 10.11 months, with 75.3% in H&Y Stage II. Baseline motor and non-motor symptoms (assessed using Movement Disorder Society – Unified Parkinson’s Disease Rating Scale [MDS-UPDRS]) were similar in severity between the MAO-B inhibitor-treated and treatment-naïve PASADENA cohorts (MDS-UPDRS Total score [standard deviation (SD)]; 30.21 [11.96], 32.10 [13.20], respectively). The overall PASADENA population (63.6% treatment naïve and 36.4% on MAO-B inhibitor) also showed a similar severity in MDS-UPDRS scores (e.g. MDS-UPDRS Total score [SD]; 31.41 [12.78], 32.63 [13.04], respectively) to the PPMI cohort (all treatment naïve).ConclusionsThe PASADENA study population is suitable to investigate the potential of prasinezumab to slow disease progression in individuals with early PD.Trial RegistrationNCT03100149

IMPORTANCE: Urate elevation, despite associations with crystallopathic, cardiovascular, and metabolic disorders, has been pursued as a potential disease-modifying strategy for Parkinson disease (PD) based on convergent biological, epidemiological, and clinical data. OBJECTIVE: To determine whether sustained urate-elevating treatment with the urate precursor inosine slows early PD progression. DESIGN, PARTICIPANTS, AND SETTING: Randomized, double-blind, placebo-controlled, phase 3 trial of oral inosine treatment in early PD. A total of 587 individuals consented, and 298 with PD not yet requiring dopaminergic medication, striatal dopamine transporter deficiency, and serum urate below the population median concentration (

SUMMARYGenetic variation at the SLC16A11 locus contributes to the disproportionate impact of type 2 diabetes (T2D) on Latino populations. We recently demonstrated that T2D risk variants reduce SLC16A11 liver expression and function of MCT11, the monocarboxylate transporter encoded by the SLC16A11 gene. Here, we show that SLC16A11 expression within the liver is primarily localized to the low oxygen pericentral region, and that T2D risk variants disrupt oxygen-regulated SLC16A11 expression in human hepatocytes. Under physiologic oxygen conditions, MCT11 deficiency alters hepatocyte glucose metabolism, resulting in elevated intracellular lactate and a metabolic shift toward triacylglycerol accumulation. We also demonstrate an impact of Mct11 deficiency on glucose and lipid metabolism in Slc16a11 knockout mice, which display physiological changes that are observed in individuals with T2D. Our findings provide mechanistic insight into how SLC16A11 disruption impacts hepatic energy metabolism and T2D risk, and highlight MCT11-mediated regulation of lactate levels as a potential therapeutic target.

There are several previous studies on the association of vitamin E with prevention of stroke but the findings remain controversial. We have conducted a systematic review, meta-analysis together with trial sequential analysis of randomised controlled trials to evaluate the effect of vitamin E supplementation versus placebo/no vitamin E on the risk reduction of total, fatal, non-fatal, haemorrhagic and ischaemic stroke. Relevant studies were identified by searching online databases through Medline, PubMed and Cochrane Central Register of Controlled Trials. A total of 18 studies with 148 016 participants were included in the analysis. There was no significant difference in the prevention of total stroke (RR (relative risk)=0.98, 95% CI 0.92–1.04, p=0.57), fatal stroke (RR=0.96, 95% CI 0.77–1.20, p=0.73) and non-fatal stroke (RR=0.96, 95% CI 0.88–1.05, p=0.35). Subgroup analyses were performed under each category (total stroke, fatal stroke and non-fatal stroke) and included the following subgroups (types of prevention, source and dosage of vitamin E and vitamin E alone vs control). The findings in all subgroup analyses were statistically insignificant. In stroke subtypes analysis, vitamin E showed significant risk reduction in ischaemic stroke (RR=0.92, 95% CI 0.85–0.99, p=0.04) but not in haemorrhagic stroke (RR=1.17, 95% CI 0.98–1.39, p=0.08). However, the trial sequential analysis demonstrated that more studies were needed to control random errors. Limitations of this study include the following: trials design may not have provided sufficient power to detect a change in stroke outcomes, participants may have had different lifestyles or health issues, there were a limited number of studies available for subgroup analysis, studies were mostly done in developed countries, and the total sample size for all included studies was insufficient to obtain a meaningful result from metaanalysis. In conclusion, there is still a lack of statistically significant evidence of the effects of vitamin E on the risk reduction of stroke. Nevertheless, vitamin E may offer some benefits in the prevention of ischaemic stroke and additional well-designed randomised controlled trials are needed to arrive at a definitive finding. PROSPERO registration number: CRD42020167827.

Background and purpose\ud Several clinical and demographic factors relate to anatomic spread of adult-onset isolated dystonia, but a predictive model is still lacking. The aims of this study were: (i) to develop and validate a predictive model of anatomic spread of adult-onset isolated dystonia; and (ii) to evaluate whether presence of tremor associated with dystonia influences model predictions of spread.\ud \ud Methods\ud Adult-onset isolated dystonia participants with focal onset from the Dystonia Coalition Natural History Project database were included. We developed two prediction models, one with dystonia as sole disease manifestation (“dystonia-only”) and one accepting dystonia OR tremor in any body part as disease manifestations (“dystonia OR tremor”). Demographic and clinical predictors were selected based on previous evidence, clinical plausibility of association with spread, or both. We used logistic regressions and evaluated model discrimination and calibration. Internal validation was carried out based on bootstrapping.\ud \ud Results\ud Both predictive models showed an area under the curve of 0.65 (95% confidence intervals 0.62–0.70 and 0.62–0.69, respectively) and good calibration after internal validation. In both models, onset of dystonia in body regions other than the neck, older age, depression and history of neck trauma were predictors of spread.\ud \ud Conclusions\ud This predictive modeling of spread in adult-onset isolated dystonia based on accessible predictors (demographic and clinical) can be easily implemented to inform individuals’ risk of spread. Because tremor did not influence prediction of spread, our results support the argument that tremor is a part of the dystonia syndrome, and not an independent or coincidental disorder.

OBJECTIVES: Prediabetes is a highly prevalent intermediate stage between normal glucose tolerance and type 2 diabetes (T2D). Lifestyle interventions (LSI) are the main focus for T2D prevention, but little is known about the aspects of LSI that can lead to the regression to a normal glucose regulation (RNGT). Metabolomics can be a helpful tool to identify the footprints of RNGR. Our aim was to identify the metabolites and lifestyle aspects that contribute to RNGR in prediabetes. METHODS: We conducted a one arm intervention study with 24 weeks of follow-up. Eligible study participants were identified by having at least one prediabetes criteria according to the American Diabetes Association, and BMI between 25 and 45 kg/m(2). The LSI was a hypocaloric diet and >150 min of physical activity at a medium intensity per week. The primary outcome, RNGR was defined as HbA1c

Despite considerable efforts to identify cancer metabolic alterations that might unveil druggable vulnerabilities, systematic characterizations of metabolism as it relates to functional genomic features and associated dependencies remain uncommon. To further understand the metabolic diversity of cancer, we profiled 225 metabolites in 928 cell lines from more than 20 cancer types in the Cancer Cell Line Encyclopedia (CCLE) using liquid chromatography–mass spectrometry (LC-MS). This resource enables unbiased association analysis linking the cancer metabolome to genetic alterations, epigenetic features and gene dependencies. Additionally, by screening barcoded cell lines, we demonstrated that aberrant ASNS hypermethylation sensitizes subsets of gastric and hepatic cancers to asparaginase therapy. Finally, our analysis revealed distinct synthesis and secretion patterns of kynurenine, an immune-suppressive metabolite, in model cancer cell lines. Together, these findings and related methodology provide comprehensive resources that will help clarify the landscape of cancer metabolism. Systematic metabolite profiling across cancer cell lines uncovers patterns associated with genetic and epigenetic features and reveals dysregulated metabolic states that can be exploited for anticancer therapy

Clear-cell carcinomas (CCCs) are a histological group of highly aggressive malignancies commonly originating in the kidney and ovary. CCCs are distinguished by aberrant lipid and glycogen accumulation and are refractory to a broad range of anti-cancer therapies. Here we identify an intrinsic vulnerability to ferroptosis associated with the unique metabolic state in CCCs. This vulnerability transcends lineage and genetic landscape, and can be exploited by inhibiting glutathione peroxidase 4 (GPX4) with small-molecules. Using CRISPR screening and lipidomic profiling, we identify the hypoxia-inducible factor (HIF) pathway as a driver of this vulnerability. In renal CCCs, HIF-2α selectively enriches polyunsaturated lipids, the rate-limiting substrates for lipid peroxidation, by activating the expression of hypoxia-inducible, lipid droplet-associated protein (HILPDA). Our study suggests targeting GPX4 as a therapeutic opportunity in CCCs, and highlights that therapeutic approaches can be identified on the basis of cell states manifested by morphological and metabolic features in hard-to-treat cancers., Clear-cell carcinomas are aggressive tumours characterised by high accumulation of lipids and glycogen. Here, the authors report that these cancers have a common vulnerability to GPX4 inhibition-induced ferroptosis and using CRISPR screen and lipodomic profiling, they identify HIF-2α- HILPDA axis promotes ferroptosis via enrichment of PUFA lipids.

Introduction In Parkinson's disease, dyskinesias result from disease progression and chronic levodopa therapy. Using Unified Dyskinesia Rating Scale (UDysRS) data pooled from two pivotal trials of ADS-5102 (amantadine) extended-release capsules in dyskinetic patients, we assessed the impact of dyskinesia on activities of daily living (ADLs), and the effects of ADS-5102 versus placebo. Methods Patients had troublesome dyskinesia (≥1 h/day) and at least mild functional impact of dyskinesia per Movement Disorder Society Unified Parkinson's Disease Rating Scale, Part IV, item 4.2. UDysRS Parts 1B, 3, and 4 scores at baseline were summarized descriptively. Twelve-week changes in score distributions and total scores were tested for significant differences between treatments. Results Among 196 patients, the majority (63%–73%) characterized their dyskinesia at baseline as having at least a mild impact on walking and balance; public and social settings; exciting or emotional settings; doing hobbies and other activities; handwriting; and dressing (six of ten ADLs in UDysRS Part 1B). By clinician ratings (in Parts 3 and 4), greatest impairment was most often observed in the trunk (62% of patients) and occurred most often for the ADL of dressing (64% had at least moderate impairment). ADS-5102 significantly reduced the patient-rated impact of dyskinesia on six of ten ADLs in Part 1B, the clinician-rated intensity of dyskinesia in all seven body regions assessed in Part 3, and the clinician-rated disability during three of four ADL tasks assessed in Part 4. Improvements in Parts 1B, 3, and 4 total scores were also statistically significant. Conclusion Dyskinesia can impair multiple tasks of daily living. Further studies may help characterize its underreported impact. By several measures, ADS-5102 treatment was associated with significant improvement of dyskinesias.

Background. Frailty potentially influences clinicians’ decision making on treatment provided they can select the appropriate assessment tools. This study aims to investigate the difference between the FRAIL scale and the Clinical Frailty Scale (CFS) in assessing frailty among community-dwelling older adults attending the General Medical Clinic (GMC) in Seberang Jaya Hospital, Penang, Malaysia. Methods. The medical records of 95 older patients (age ≥ 65) who attended the GMC from 16 December 2019 to 10 January 2020 were reviewed. Frailty was identified using the FRAIL scale and the CFS. Patient characteristics were investigated for their association with frailty and their difference in the prevalence of frailty by the FRAIL scale and CFS. Results. The CFS identified nonsignificant higher prevalence of frailty compared to the FRAIL scale (21/95; 22.1% vs. 17/95; 17.9%, ratio of prevalence = 1.235, p = 0.481 ). Minimal agreement was found between the FRAIL scale and the CFS (Kappa = 0.272, p < 0.001 ). Three out of 5 components of the FRAIL scale (resistance, ambulation, and loss of weight) were associated with frailty by the CFS. Higher prevalence of frailty was identified by the CFS in those above 70 years of age. The FRAIL scale identified more patients with frailty in ischaemic heart disease patients. Conclusion. Patient characteristics influenced the choice of the frailty assessment tool. The FRAIL scale and the CFS may complement each other in providing optimized care to older patients who attended the GMC.

Obesity is an epidemic internationally. While weight loss interventions are efficacious, they are compounded by heterogeneity with regards to clinically relevant metabolic responses. Thus, we sought to identify metabolic biomarkers that are associated with beneficial metabolic changes to weight loss and which distinguish individuals with obesity who would most benefit from a given type of intervention. Liquid chromatography mass spectrometry-based profiling was used to measure 765 metabolites in baseline plasma from three different weight loss studies: WLM (behavioral intervention, N = 443), STRRIDE-PD (exercise intervention, N = 163), and CBD (surgical cohort, N = 125). The primary outcome was percent change in insulin resistance (as measured by the Homeostatic Model Assessment of Insulin Resistance [%ΔHOMA-IR]) over the intervention. Overall, 92 individual metabolites were associated with %ΔHOMA-IR after adjustment for multiple comparisons. Concordantly, the most significant metabolites were triacylglycerols (TAGs; p = 2.3e-5) and diacylglycerols (DAGs; p = 1.6e-4), with higher baseline TAG and DAG levels associated with a greater improvement in insulin resistance with weight loss. In tests of heterogeneity, 50 metabolites changed differently between weight loss interventions; we found amino acids, peptides, and their analogues to be most significant (4.7e-3) in this category. Our results highlight novel metabolic pathways associated with heterogeneity in response to weight loss interventions, and related biomarkers which could be used in future studies of personalized approaches to weight loss interventions.

The escalated burden of diabetes on the population&rsquo, s health has catalyzed rigorous scientific research to produce appropriate evidence for treatment and control. Malaysia suffers from the leading diabetes epidemic within the Western Pacific region. It is crucial to map the scientific landscape of diabetes research for the country to identify trends in productivity and determine whether research efforts are directed toward the needs-gaps priority for evidence synthesis that could be used for the drafting of policies and guidelines. This systematic scientometrics study was conducted to map the scientific research output (trends and distribution, citation frequency, keywords link visualization, and thematic cluster conceptualization) related to diabetes between 2000&ndash, 2018 in Malaysia. Using three international databases (PubMed, EMBASE, Scopus) and one local database (MyCite), scientific publication records related to diabetes in Malaysia between 2000 and 2018 were retrieved and analyzed using quantitative and qualitative methodologies. Microsoft Excel 2016, EndNote X9.2, BibExcel 2016, GraphPad Prism 8.0.1, VOS viewer software 1.6.13, and R software version 1.3.959 were used to analyze the trend and contents of diabetes publications. A total of 2094 publication records that accounted for 35,497 citations were analyzed. Kuala Lumpur was the most scientifically productive state in Malaysia, contributing 754 papers. Medical Journal of Malaysia had the highest number of publications. The inflection point of the Malaysian diabetes research output was in 2013, with most publications being non-collaborative research works. Most publications originated from academia, especially from local public universities. The overall publication productivity of diabetes research in Malaysia was conceptualized into eleven thematic clusters, with clinical and animal studies being the most prevalent themes. The diabetes literature in Malaysia has grown steadily over the past 19 years. However, the cumulative evidence remains inadequate and is insufficiently powered to guide policymaking and the control of diabetes. It does not yet seem feasible to direct the diabetes epidemic curve to a plateau for the Malaysian population based on Malaysian diabetes publications.

ObjectivesAntiretroviral therapy (ART) use is associated with disrupted lipid and glucose metabolism in people with HIV-infection. We aimed to identify plasma lipid species associated with risk of diabetes in the context of HIV infection.Research Design and MethodsWe profiled 211 plasma lipid species in 491 HIV-infected and 203 HIV-uninfected participants aged 35-55 years from the Women’s Interagency HIV study and the Multicenter AIDS Cohort Study. Cox proportional hazards model was used to examine associations between baseline lipid species and incident diabetes (166 diabetes cases were identified during a median follow-up of 12.6 years).ResultsWe identified 11 lipid species, representing independent signals for 8 lipid classes/subclasses, associated with risk of diabetes (PConclusionsThis study identified multiple plasma lipid species associated with incident diabetes. Regardless of the directions of their associations with diabetes, most diabetes-associated lipid species were elevated in ART-treated people with HIV-infection. This suggests a complex role of lipids in the link between ART and diabetes in HIV infection.

Obesity is an epidemic internationally. While weight loss interventions are efficacious, they are compounded by heterogeneity with regards to clinically relevant metabolic responses. Thus, we sought to identify metabolic pathways and biomarkers that distinguish individuals with obesity who would most benefit from a given type of intervention. Liquid chromatography mass spectrometry-based profiling was used to measure 765 metabolites in baseline plasma from three different weight loss studies: WLM (behavioral intervention, N=443), STRRIDE-PD (exercise trial, N=163), and CBD (surgical cohort, N=125). The primary outcome was percent change in insulin resistance (as measured by the Homeostatic Model Assessment of Insulin Resistance [%ΔHOMA-IR]) over the intervention. Overall, 92 individual metabolites were associated with %ΔHOMA-IR after adjustment for multiple comparisons. Concordantly, the most significant metabolites were triacylglycerols (TAGs; p=2.3e-5) and diacylglycerols (DAGs; p=1.6e-4), with higher TAG and DAG levels associated with a greater improvement in HOMA-IR. In tests of heterogeneity, 50 metabolites changed differently between weight loss interventions; we found amino acids, peptides, and their analogues to be most significant (4.7e-3) in this category. Our results highlight novel metabolic pathways associated with heterogeneity in response to weight loss interventions, and related biomarkers which could be used in future studies of personalized approaches to weight loss interventions.

Background: Whereas regular exercise is associated with lower risk of cardiovascular disease and mortality, mechanisms of exercise-mediated health benefits remain less clear. We used metabolite profiling before and after acute exercise to delineate the metabolic architecture of exercise response patterns in humans. Methods: Cardiopulmonary exercise testing and metabolite profiling was performed on Framingham Heart Study participants (age 53±8 years, 63% women) with blood drawn at rest (n=471) and at peak exercise (n=411). Results: We observed changes in circulating levels for 502 of 588 measured metabolites from rest to peak exercise (exercise duration 11.9±2.1 minutes) at a 5% false discovery rate. Changes included reductions in metabolites implicated in insulin resistance (glutamate, −29%; P =1.5×10 −55 ; dimethylguanidino valeric acid [DMGV], −18%; P =5.8×10 −18 ) and increases in metabolites associated with lipolysis (1-methylnicotinamide, +33%; P =6.1×10 −67 ), nitric oxide bioavailability (arginine/ornithine + citrulline, +29%; P =2.8×10 −169 ), and adipose browning (12,13-dihydroxy-9Z-octadecenoic acid +26%; P =7.4×10 −38 ), among other pathways relevant to cardiometabolic risk. We assayed 177 metabolites in a separate Framingham Heart Study replication sample (n=783, age 54±8 years, 51% women) and observed concordant changes in 164 metabolites (92.6%) at 5% false discovery rate. Exercise-induced metabolite changes were variably related to the amount of exercise performed (peak workload), sex, and body mass index. There was attenuation of favorable excursions in some metabolites in individuals with higher body mass index and greater excursions in select cardioprotective metabolites in women despite less exercise performed. Distinct preexercise metabolite levels were associated with different physiologic dimensions of fitness (eg, ventilatory efficiency, exercise blood pressure, peak V o 2 ). We identified 4 metabolite signatures of exercise response patterns that were then analyzed in a separate cohort (Framingham Offspring Study; n=2045, age 55±10 years, 51% women), 2 of which were associated with overall mortality over median follow-up of 23.1 years ( P ≤0.003 for both). Conclusions: In a large sample of community-dwelling individuals, acute exercise elicits widespread changes in the circulating metabolome. Metabolic changes identify pathways central to cardiometabolic health, cardiovascular disease, and long-term outcome. These findings provide a detailed map of the metabolic response to acute exercise in humans and identify potential mechanisms responsible for the beneficial cardiometabolic effects of exercise for future study.

Population genetic studies highlight a missense variant (G398S) of A1CF that is strongly associated with higher levels of blood triglycerides (TGs) and total cholesterol (TC). Functional analyses suggest that the mutation accelerates the secretion of very low-density lipoprotein (VLDL) from the liver by an unknown mechanism. Here, we used multiomics approaches to interrogate the functional difference between the WT and mutant A1CF. Using metabolomics analyses, we captured the cellular lipid metabolite changes induced by transient expression of the proteins, confirming that the mutant A1CF is able to relieve the TG accumulation induced by WT A1CF. Using a proteomics approach, we obtained the interactomic data of WT and mutant A1CF. Networking analyses show that WT A1CF interacts with three functional protein groups, RNA/mRNA processing, cytosolic translation, and, surprisingly, mitochondrial translation. The mutation diminishes these interactions, especially with the group of mitochondrial translation. Differential analyses show that the WT A1CF-interacting proteins most significantly different from the mutant are those for mitochondrial translation, whereas the most significant interacting proteins with the mutant are those for cytoskeleton and vesicle-mediated transport. RNA-seq analyses validate that the mutant, but not the WT, A1CF increases the expression of the genes responsible for cellular transport processes. On the contrary, WT A1CF affected the expression of mitochondrial matrix proteins and increased cell oxygen consumption. Thus, our studies confirm the previous hypothesis that A1CF plays broader roles in regulating gene expression. The interactions of the mutant A1CF with the vesicle-mediated transport machinery provide mechanistic insight in understanding the increased VLDL secretion in the A1CF mutation carriers.

Neurodegeneration of the locus coeruleus (LC) in age-related neurodegenerative diseases such as Alzheimer's disease (AD) is well documented. However, detailed studies of LC neurodegeneration in the full spectrum of frontotemporal lobar degeneration (FTLD) proteinopathies comparing tauopathies (FTLD-tau) to TDP-43 proteinopathies (FTLD-TDP) are lacking. Here, we tested the hypothesis that there is greater LC neuropathology and neurodegeneration in FTLD-tau compared to FTLD-TDP. We examined 280 patients including FTLD-tau (n = 94), FTLD-TDP (n = 135), and two reference groups: clinical/pathological AD (n = 32) and healthy controls (HC, n = 19). Adjacent sections of pons tissue containing the LC were immunostained for phosphorylated TDP-43 (1D3-p409/410), hyperphosphorylated tau (PHF-1), and tyrosine hydroxylase (TH) to examine neuromelanin-containing noradrenergic neurons. Blinded to clinical and pathologic diagnoses, we semi-quantitatively scored inclusions of tau and TDP-43 both inside LC neuronal somas and in surrounding neuropil. We also digitally measured the percent area occupied of neuromelanin inside of TH-positive LC neurons and in surrounding neuropil to calculate a ratio of extracellular-to-intracellular neuromelanin as an objective composite measure of neurodegeneration. We found that LC tau burden in FTLD-tau was greater than LC TDP-43 burden in FTLD-TDP (z = - 11.38, p 0.0001). Digital measures of LC neurodegeneration in FTLD-tau were comparable to AD (z = - 1.84, p 0.05) but greater than FTLD-TDP (z = - 3.85, p 0.0001) and HC (z = - 4.12, p 0.0001). Both tau burden and neurodegeneration were consistently elevated in the LC across pathologic and clinical subgroups of FTLD-tau compared to FTLD-TDP subgroups. Moreover, LC tau burden positively correlated with neurodegeneration in the total FTLD group (rho = 0.24, p = 0.001), while TDP-43 burden did not correlate with LC neurodegeneration in FTLD-TDP (rho = - 0.01, p = 0.90). These findings suggest that patterns of disease propagation across all tauopathies include prominent LC tau and neurodegeneration that are relatively distinct from the minimal degenerative changes to the LC in FTLD-TDP and HC. Antemortem detection of LC neurodegeneration and/or function could potentially improve antemortem differentiation of underlying FTLD tauopathies from clinically similar FTLD-TDP proteinopathies.

Despite high-quality evidence highlighting metabolic surgery as an effective treatment option for type 2 diabetes mellitus (T2DM), the number of patients receiving bariatric surgery (BS) remains low. Since the introduction of the Diabetes Surgery Summit II (DSS-II) eligibility criteria, data on eligibility rates for BS in T2DM cohorts remain scarce. The aims of the present study were to examine in a real-world clinical setting: (i) what is the percentage of T2DM patients visiting diabetes outpatient clinics who meet the DSS-II eligibility criteria, (ii) how many of these have been informed about the option of BS, and (iii) what are the characteristics associated with eligibility and awareness of BS. Demographic, anthropometric, clinical and socioeconomic data were obtained for all patients with T2DM who were consecutively examined in the outpatient clinics of three large-volume university hospitals (n = 1167). A medical registry form was completed to screen for BS eligibility. Patients were considered eligible if the recommendation by DSS-II criteria was either to “consider” or “recommend” BS. Eligible patients were further inquired whether they had ever been informed about the option of BS by their physicians. The advanced DiaRem score (ADRS) was applied to eligible patients to assess their probability of achieving postoperative T2DM remission. A significant percentage of T2DM patients who are routinely assessed in outpatient clinics meet the DSS-II eligibility criteria (15.3%). Eligible patients are younger and more obese, have a shorter T2DM duration, worse glycaemic control and better renal function, compared to non-eligible ones. Among eligible patients, only 39.3% have been medically informed about the option of BS. Informed patients are younger and more severely obese than non-informed ones. A significant percentage of non-informed patients (35%) have an ADRS ≤10, indicating a considerable probability for T2DM remission after BS, and are thus deprived of this opportunity due to lack of appropriate medical counseling. Screening and awareness of BS remain an unmet need in current T2DM management. Future research should focus on intensifying screening for BS eligibility at every medical visit and promoting evidence-based clinical recommendations for patients expected to benefit the most.

SCOPE: The plasma metabolomics profiles of protein intake has been rarely investigated. We aimed to identify the distinct plasma metabolomics profiles associated with overall intakes of protein as well as with intakes from animal and plant protein sources. METHODS AND RESULTS: Cross-sectional analysis using data from 1,833 participants at high risk of cardiovascular disease. Plasma metabolomics analysis was performed using LC-MS. Associations between 385 identified metabolites and the intake of total, animal protein (AP) and plant protein (PP), and plant-to-animal ratio (PR) were assessed using elastic net continuous regression analyses. A double 10-cross-validation (CV) procedure was used and Pearson correlations coefficients between multi-metabolite weighted models and reported protein intake in each pair of training-validation datasets were calculated. A wide set of metabolites was consistently associated with each protein source evaluated. These metabolites mainly consisted of amino acids and their derivatives, acylcarnitines, different organic acids and lipid species. Few metabolites overlapped among protein sources (i.e. C14:0 SM, C20:4 carnitine, GABA and allantoin) but none of them towards the same direction. Regarding AP and PP approaches, C20:4 carnitine and dimethylglycine were positively associated with PP but negatively associated with AP. However, allantoin, C14:0 SM, C38:7 PE plasmalogen, GABA, metronidazole and trigonelline (N-methylnicotinate) behaved contrary. Ten-CV Pearson correlations coefficients between self-reported protein intake and plasma metabolomics profiles ranged from 0.21 for PR to 0.32 for total protein. CONCLUSIONS: Different sets of metabolites were associated with total, animal and plant protein intake. Further studies are needed to assess the contribution of these metabolites in protein biomarkers’ discovery and prediction of cardiometabolic alterations.

Ferroptosis is widely involved in degenerative diseases in various tissues including kidney, liver and brain, and is a targetable vulnerability in clear-cell carcinomas and therapy-resistant cancers. Accumulation of phospholipid hydroperoxides in cellular membranes is recognized as the hallmark and rate-limiting step of ferroptosis; however, the enzymes contributing to lipid peroxidation remain poorly characterized. Using genome-wide, CRISPR/Cas9-mediated suppressor screens, we identify cytochrome P450 oxidoreductase (POR) as a contributor to ferroptotic cell death in cancer cells exhibiting inherent and induced susceptibility to ferroptosis. By genetic depletion of POR in cancer cells, we reveal that POR contributes to ferroptosis across a wide range of lineages and cell-states, and in response to distinct mechanisms of ferroptosis induction. Using systematic lipidomic profiling, we further map POR’s activity to the lipid peroxidation step in ferroptosis. Hence, our work suggests POR as a key mediator of ferroptosis and a potential druggable target for developing anti-ferroptosis therapeutics.

Background People living with HIV have an increased risk of left ventricular diastolic dysfunction ( LVDD ) and heart failure. HIV ‐associated LVDD may reflect both cardiomyocyte and systemic metabolic derangements, but the underlying pathways remain unclear. Methods and Results To explore such pathways, we conducted a pilot study in the Bronx and Brooklyn sites of the WIHS (Women's Interagency HIV Study) who participated in concurrent, but separate, metabolomics and echocardiographic ancillary studies. Liquid chromatography tandem mass spectrometry–based metabolomic profiling was performed on plasma samples from 125 HIV‐infected (43 with LVDD) and 35 HIV‐uninfected women (9 with LVDD). Partial least squares discriminant analysis identified polar metabolites and lipids in the glycerophospholipid‐metabolism and fatty‐acid‐oxidation pathways associated with LVDD . After multivariable adjustment, LVDD was significantly associated with higher concentrations of diacylglycerol 30:0 (odds ratio [ OR ], 1.60, 95% CI [1.01–2.55]); triacylglycerols 46:0 ( OR 1.60 [1.04–2.48]), 48:0 ( OR 1.63 [1.04–2.54]), 48:1 ( OR 1.62 [1.01–2.60]), and 50:0 ( OR 1.61 [1.02–2.53]); acylcarnitine C7 ( OR 1.88 [1.21–2.92]), C9 ( OR 1.99 [1.27–3.13]), and C16 ( OR 1.80 [1.13–2.87]); as well as lower concentrations of phosphocholine ( OR 0.59 [0.38–0.91]). There was no evidence of effect modification of these relationships by HIV status. Conclusions In this pilot study, women with or at risk of HIV with LVDD showed alterations in plasma metabolites in the glycerophospholipid‐metabolism and fatty‐acid‐oxidation pathways. Although these findings require replication, they suggest that improved understanding of metabolic perturbations and their potential modification could offer new approaches to prevent cardiac dysfunction in this high‐risk group.

After Roux-en-Y gastric bypass (RYGB) surgery, the intestine undergoes structural and metabolic reprogramming and appears to enhance use of energetic fuels including glucose and amino acids (AAs), changes that may be related to the surgery’s remarkable metabolic effects. Consistently, RYGB alters serum levels of AAs and other metabolites, perhaps reflecting mechanisms for metabolic improvement. To home in on the intestinal contribution, we performed metabolomic profiling in portal venous (PV) blood from lean, Long Evans rats after RYGB vs sham surgery. We found that one-carbon metabolism (OCM), nitrogen metabolism, and arginine and proline metabolism were significantly enriched in PV blood. Nitrogen, OCM, and sphingolipid metabolism as well as ubiquinone biosynthesis were also overrepresented among metabolites uniquely affected in PV vs peripheral blood in RYGB-operated but not sham-operated animals. Peripheral blood demonstrated changes in AA metabolism, OCM, sphingolipid metabolism, and glycerophospholipid metabolism. Despite enrichment for many of the same pathways, the overall metabolite fingerprint of the 2 compartments did not correlate, highlighting a unique role for PV metabolomic profiling as a window into gut metabolism. AA metabolism and OCM were enriched in peripheral blood both from humans and lean rats after RYGB, demonstrating that these conserved pathways might represent mechanisms for clinical improvement elicited by the surgery in patients. Together, our data provide novel insight into RYGB’s effects on the gut-liver axis and highlight a role for OCM as a key metabolic pathway affected by RYGB.

OBJECTIVE Specific lipid molecular changes leading to type 2 diabetes (T2D) are largely unknown. We assessed lipidome factors associated with future occurrence of T2D in a population at high cardiovascular risk. RESEARCH DESIGN AND METHODS We conducted a case-cohort study nested within the PREDIMED trial, with 250 incident T2D cases diagnosed during 3.8 years of median follow-up, and a random sample of 692 participants (639 noncases and 53 overlapping cases) without T2D at baseline. We repeatedly measured 207 plasma known lipid metabolites at baseline and after 1 year of follow-up. We built combined factors of lipid species using principal component analysis and assessed the association between these lipid factors (or their 1-year changes) and T2D incidence. RESULTS Baseline lysophosphatidylcholines and lysophosphatidylethanolamines (lysophospholipids [LPs]), phosphatidylcholine-plasmalogens (PC-PLs), sphingomyelins (SMs), and cholesterol esters (CEs) were inversely associated with risk of T2D (multivariable-adjusted P for linear trend ≤0.001 for all). Baseline triacylglycerols (TAGs), diacylglycerols (DAGs), and phosphatidylethanolamines (PEs) were positively associated with T2D risk (multivariable-adjusted P for linear trend CONCLUSIONS Two plasma lipid profiles made up of different lipid classes were found to be associated with T2D in participants at high cardiovascular risk. A profile including LPs, PC-PLs, SMs, and CEs was associated with lower T2D risk. Another profile composed of TAGs, DAGs, and PEs was associated with higher T2D risk.

Brain metastases are refractory to therapies that otherwise control systemic disease in patients with human epidermal growth factor receptor 2 (HER2+) breast cancer, and the unique brain microenvironment contributes to this therapy resistance. Nutrient availability can vary across tissues, therefore metabolic adaptations required for breast cancer growth in the brain microenvironment may also introduce liabilities that can be exploited for therapy. Here, we assessed how metabolism differs between breast tumors growing in the brain versus extracranial sites and found that fatty acid synthesis is elevated in breast tumors growing in the brain. We determine that this phenotype is an adaptation to decreased lipid availability in the brain relative to other tissues, which results in a site-specific dependency on fatty acid synthesis for breast tumors growing at this site. Genetic or pharmacological inhibition of fatty acid synthase (FASN) reduces HER2+ breast tumor growth in the brain, demonstrating that differences in nutrient availability across metastatic sites can result in targetable metabolic dependencies.

Brain metastases are refractory to therapies that control systemic disease in patients with human epidermal growth factor receptor 2-positive breast cancer and the brain microenvironment contributes to this therapy resistance. Nutrient availability can vary across tissues, therefore metabolic adaptations required for brain metastatic breast cancer growth may introduce liabilities that can be exploited for therapy. Here we assessed how metabolism differs between breast tumors in brain versus extracranial sites and found that fatty acid synthesis is elevated in breast tumors growing in the brain. We determine that this phenotype is an adaptation to decreased lipid availability in the brain relative to other tissues, resulting in site-specific dependency on fatty acid synthesis for breast tumors growing at this site. Genetic or pharmacological inhibition of fatty acid synthase reduces human epidermal growth factor receptor 2-positive breast tumor growth in the brain, demonstrating that differences in nutrient availability across metastatic sites can result in targetable metabolic dependencies.

Most deaths from cancer are explained by metastasis, and yet large-scale metastasis research has been impractical due to the inherent scale limitation of the in vivo models. Here we introduce an in vivo barcoding strategy capable of determining the metastatic potential of human cancer cell lines in murine xenografts at scale. We validated the robustness, scalability and reproducibility of the method, and applied it to 500 cell lines spanning 21 solid cancer types. We created a first-generation Metastasis Map (MetMap) that reveals organ-specific patterns of metastasis and allows relating those patterns to clinical and genomic features. We demonstrated the utility of MetMap by exploring the molecular basis of breast cancers capable of metastasizing to the brain - a principal cause of death in these patients. Breast cancers that were brain metastatic had unexpected genetic, expression, and metabolic evidence of altered lipid metabolism. Perturbing lipid metabolism curbed brain metastasis development and limited the outgrowth of cancer cells in the brain, suggesting a therapeutic strategy to combat the disease. These results illustrated the utility of MetMap as a step towards next-generation approach for high-throughput metastasis research. Citation Format: Xin Jin, Zelalem Demere, Karthik Nair, Ahmed Ali, Gino B. Ferraro, Ted Natoli, Amy Deik, Lia Petronio, Andrew A. Tang, Cong Zhu, Li Wang, Danny Rosenberg, Vamsi Mangena, Jennifer Roth, Kwanghun Chung, Rakesh K. Jain, Clary B. Clish, Matthew G. Vander Heiden, Todd R. Golub. A metastasis map of human cancer cell lines [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr NG10.

Brain metastases are refractory to therapies that otherwise control systemic disease in patients with human epidermal growth factor receptor 2 (HER2+) breast cancer, and the unique brain microenvironment contributes to this therapy resistance. Nutrient availability can vary across tissues, therefore metabolic adaptations required for breast cancer growth in the brain microenvironment may also introduce liabilities that can be exploited for therapy. Here, we assessed how metabolism differs between breast tumors growing in the brain versus extracranial sites and found that fatty acid synthesis is elevated in breast tumors growing in the brain. We determine that this phenotype is an adaptation to decreased lipid availability in the brain relative to other tissues, which results in a site-specific dependency on fatty acid synthesis for breast tumors growing at this site. Genetic or pharmacological inhibition of fatty acid synthase (FASN) reduces HER2+ breast tumor growth in the brain, demonstrating that differences in nutrient availability across metastatic sites can result in targetable metabolic dependencies. Citation Format: Gino B. Ferraro, Ahmed Ali, Alba Luengo, David P. Kodack, Amy Deik, Keene L. Abbott, Divya Bezwada, Landry Blanc, Brendan Prideaux, Xin Jin, Jessica M. Possada, Jiang Chen, Christopher R. Chin, Zohreh Amoozgar, Raphael Ferreira, Ivy Chen, Kamila Naxerova, Christopher Ng, Anna M. Westermark, Mark Duquette, Sylvie Roberge, Costas A. Lyssiotis, Dan G. Duda, Todd R. Golub, Shawn M. Davidson, Dai Fukumura, Véronique A. Dartois, Clary B. Clish, Matthew G. Vander Heiden, Rakesh K. Jain. Fatty acid synthesis is required for breast cancer brain metastasis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 90.

Background: Clinical nutrition research often lacks robust markers of compliance, complicating the interpretation of clinical trials and observational studies of free-living subjects.Objective: We aimed to examine metabolomics profiles in response to 3 diets that differed widely in macronutrient composition during a controlled feeding protocol.Design: Twenty-one adults with a high body mass index (in kg/m2; mean ± SD: 34.4 ± 4.9) were given hypocaloric diets to promote weight loss corresponding to 10-15% of initial body weight. They were then studied during weight stability while consuming 3 test diets, each for a 4-wk period according to a crossover design: low fat (60% carbohydrate, 20% fat, 20% protein), low glycemic index (40% carbohydrate, 40% fat, 20% protein), or very-low carbohydrate (10% carbohydrate, 60% fat, 30% protein). Plasma samples were obtained at baseline and at the end of each 4-wk period in the fasting state for metabolomics analysis by using liquid chromatography-tandem mass spectrometry. Statistical analyses included adjustment for multiple comparisons.Results: Of 333 metabolites, we identified 152 whose concentrations differed for ≥1 diet compared with the others, including diacylglycerols and triacylglycerols, branched-chain amino acids, and markers reflecting metabolic status. Analysis of groups of related metabolites, with the use of either principal components or pathways, revealed coordinated metabolic changes affected by dietary composition, including pathways related to amino acid metabolism. We constructed a classifier using the metabolites that differed between diets and were able to correctly identify the test diet from metabolite profiles in 60 of 63 cases (>95% accuracy). Analyses also suggest differential effects by diet on numerous cardiometabolic disease risk factors.Conclusions: Metabolomic profiling may be used to assess compliance during clinical nutrition trials and the validity of dietary assessment in observational studies. In addition, this methodology may help elucidate mechanistic pathways linking diet to chronic disease risk. This trial was registered at clinicaltrials.gov as NCT00315354.

Background The differential diagnosis of progressive supranuclear palsy (PSP) and Lewy body disorders, which include Parkinson disease and dementia with Lewy bodies, is often challenging due to the overlapping symptoms. Purpose To develop a diagnostic tool based on diffusion tensor imaging (DTI) to distinguish between PSP and Lewy body disorders at the individual-subject level. Materials and Methods In this retrospective study, skeletonized DTI metrics were extracted from two independent data sets: the discovery cohort from the Swedish BioFINDER study and the validation cohort from the Penn Frontotemporal Degeneration Center (data collected between 2010 and 2018). Based on previous neuroimaging studies and neuropathologic evidence, a combination of regions hypothesized to be sensitive to pathologic features of PSP were identified (ie, the superior cerebellar peduncle and frontal white matter) and fractional anisotropy (FA) was used to compute an FA score for each individual. Classification performances were assessed by using logistic regression and receiver operating characteristic analysis. Results In the discovery cohort, 16 patients with PSP (mean age ± standard deviation, 73 years ± 5; eight women, eight men), 34 patients with Lewy body disorders (mean age, 71 years ± 6; 14 women, 20 men), and 44 healthy control participants (mean age, 66 years ± 8; 26 women, 18 men) were evaluated. The FA score distinguished between clinical PSP and Lewy body disorders with an area under the curve of 0.97 ± 0.04, a specificity of 91% (31 of 34), and a sensitivity of 94% (15 of 16). In the validation cohort, 34 patients with PSP (69 years ± 7; 22 women, 12 men), 25 patients with Lewy body disorders (70 years ± 7; nine women, 16 men), and 32 healthy control participants (64 years ± 7; 22 women, 10 men) were evaluated. The accuracy of the FA score was confirmed (area under the curve, 0.96 ± 0.04; specificity, 96% [24 of 25]; and sensitivity, 85% [29 of 34]). Conclusion These cross-validated findings lay the foundation for a clinical test to distinguish progressive supranuclear palsy from Lewy body disorders. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Shah in this issue.

Ovarian cancer has few known risk factors, hampering identification of high-risk women. We assessed the association of prediagnostic plasma metabolites (N = 420) with risk of epithelial ovarian cancer, including both borderline and invasive tumors. A total of 252 cases and 252 matched controls from the Nurses' Health Studies were included. Multivariable logistic regression was used to estimate ORs and 95% confidence intervals (CI), comparing the 90th–10th percentile in metabolite levels, using the permutation-based Westfall and Young approach to account for testing multiple correlated hypotheses. Weighted gene coexpression network analysis (WGCNA; n = 10 metabolite modules) and metabolite set enrichment analysis (n = 23 metabolite classes) were also evaluated. An increase in pseudouridine levels from the 10th to the 90th percentile was associated with a 2.5-fold increased risk of overall ovarian cancer (OR = 2.56; 95% CI, 1.48–4.45; P = 0.001/adjusted P = 0.15); a similar risk estimate was observed for serous/poorly differentiated tumors (n = 176 cases; comparable OR = 2.38; 95% CI, 1.33–4.32; P = 0.004/adjusted P = 0.55). For nonserous tumors (n = 34 cases), pseudouridine and C36:2 phosphatidylcholine plasmalogen had the strongest statistical associations (OR = 9.84; 95% CI, 2.89–37.82; P < 0.001/adjusted P = 0.07; and OR = 0.11; 95% CI, 0.03–0.35; P < 0.001/adjusted P = 0.06, respectively). Five WGCNA modules and 9 classes were associated with risk overall at FDR ≤ 0.20. Triacylglycerols (TAG) showed heterogeneity by tumor aggressiveness (case-only heterogeneity P < 0.0001). The TAG association with risk overall and serous tumors differed by acyl carbon content and saturation. In summary, this study suggests that pseudouridine may be a novel risk factor for ovarian cancer and that TAGs may also be important, particularly for rapidly fatal tumors, with associations differing by structural features. Significance: Pseudouridine represents a potential novel risk factor for ovarian cancer and triglycerides may be important particularly in rapidly fatal ovarian tumors.

BackgroundOvarian cancer has few known risk factors, hampering identification of high-risk women. Thus, we assessed the association of pre-diagnostic plasma metabolites (N=420) with risk.nnMethodsWe included 252 cases (176 serous/poorly differentiated; 34 non-serous [endometrioid/clear cell]) diagnosed 3-23 years after blood collection and 252 matched controls from the Nurses Health Studies. Multivariable logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) comparing the 90th-10thpercentile in metabolite levels, using permutation tests to account for testing multiple correlated hypotheses. Weighted gene co-expression network analysis (WGCNA) modules (n=10) summarized by the first principal component and metabolite set enrichment analysis (MSEA; n=23) were also evaluated.nnResultsPseudouridine had the strongest statistical association with ovarian cancer risk overall (OR=2.56, 95%CI=1.48-4.45; p=0.001/adjusted-p=0.15). C36:2 phosphatidylcholine (PC) plasmalogen had the strongest statistical association with lower risk (OR=0.11, 95%CI=0.03-0.35; p

In the Supplementary Tables 2, 4 and 6 originally published with this Article, the authors mistakenly included sample identifiers in the form of UMCGs rather than UMCG IBDs in the validation cohort; this has now been amended.

Objective: To identify prediagnostic plasma metabolomic biomarkers associated with amyotrophic lateral sclerosis (ALS). Methods: We conducted a global metabolomic study using a nested case-control study design within 5 prospective cohorts and identified 275 individuals who developed ALS during follow-up. We profiled plasma metabolites using liquid chromatography–mass spectrometry and identified 404 known metabolites. We used conditional logistic regression to evaluate the associations between metabolites and ALS risk. Further, we used machine learning analyses to determine whether the prediagnostic metabolomic profile could discriminate ALS cases from controls. Results: A total of 31 out of 404 identified metabolites were associated with ALS risk (p < 0.05). We observed inverse associations (n = 27) with plasma levels of diacylglycerides and triacylglycerides, urate, purine nucleosides, and some organic acids and derivatives, while we found positive associations for a cholesteryl ester, 2 phosphatidylcholines, and a sphingomyelin. The number of significant associations increased to 67 (63 inverse) in analyses restricted to cases with blood samples collected within 5 years of onset. None of these associations remained significant after multiple comparison adjustment. Further, we were not able to reliably distinguish individuals who became cases from controls based on their metabolomic profile using partial least squares discriminant analysis, elastic net regression, random forest, support vector machine, or weighted correlation network analyses. Conclusions: Although the metabolomic profile in blood samples collected years before ALS diagnosis did not reliably separate presymptomatic ALS cases from controls, our results suggest that ALS is preceded by a broad, but poorly defined, metabolic dysregulation years before the disease onset.

Background Insulin resistance is a complex metabolic disorder and is often associated with type 2 diabetes (T2D). Objectives The aim of this study was to test whether baseline metabolites can additionally improve the prediction of insulin resistance beyond classical risk factors. Furthermore, we examined whether a multimetabolite model predicting insulin resistance in nondiabetics can also predict incident T2D. Methods We used a case-cohort study nested within the Prevencion con Dieta Mediterranea (PREDIMED) trial in subsets of 700, 500, and 256 participants without T2D at baseline and 1 and 3 y. Fasting plasma metabolites were semiquantitatively profiled with liquid chromatography-tandem mass spectrometry. We assessed associations between metabolite concentrations and the homeostasis model of insulin resistance (HOMA-IR) through the use of elastic net regression analysis. We subsequently examined associations between the baseline HOMA-IR-related multimetabolite model and T2D incidence through the use of weighted Cox proportional hazard models. Results We identified a set of baseline metabolites associated with HOMA-IR. One-year changes in metabolites were also significantly associated with HOMA-IR. The area under the curve was significantly greater for the model containing the classical risk factors and metabolites together compared with classical risk factors alone at baseline [0.81 (95% CI: 0.79, 0.84) compared with 0.69 (95% CI: 0.66, 0.73)] and during a 1-y period [0.69 (95% CI: 0.66, 0.72) compared with 0.57 (95% CI: 0.53, 0.62)]. The variance in HOMA-IR explained by the combination of metabolites and classical risk factors was also higher in all time periods. The estimated HRs for incident T2D in the multimetabolite score (model 3) predicting high HOMA-IR (median value or higher) or HOMA-IR (continuous) at baseline were 2.00 (95% CI: 1.58, 2.55) and 2.24 (95% CI: 1.72, 2.90), respectively, after adjustment for T2D risk factors. Conclusions The multimetabolite model identified in our study notably improved the predictive ability for HOMA-IR beyond classical risk factors and significantly predicted the risk of T2D.