Suicide in individuals with eating disorders who had sought mental health treatment in England: a national retrospective cohort study.

BACKGROUND: Although studies have suggested a high risk of suicide in people with eating disorders, most studies have focused on suicidal ideation and attempts. There is little research on the characteristics of people with eating disorders who died by suicide, nor investigation of trends over time. We aimed to compare the characteristics of patients with eating disorders who died by suicide versus patients with other mental health diagnoses who died by suicide in England and to examine the trends in rates. METHODS: In this national retrospective cohort study, data on all people (aged ≥10 years) who died by suicide in England, UK, between Jan 1, 1997, and Dec 31, 2021, while under the care (within the previous 12 months) of mental health services were obtained from the National Confidential Inquiry into Suicide and Safety in Mental Health (NCISH), in which clinical information is collected via a questionnaire completed by the mental health professional responsible for the patient's care. Incidence of suicide in, and demographic, clinical, and treatment characteristics of, patients with a diagnosis of eating disorder (as recorded by the treating clinician) who died by suicide were compared with patients with other mental health diagnoses who died by suicide within the same timeframe using univariable logistic regression analysis. People with related lived experience were involved in the study design, implementation, interpretation, and writing of the manuscript. FINDINGS: Of 119 446 people for whom NCISH were notified of dying by suicide in England, 30 795 were under the recent care of mental health services, of whom 30 246 had known diagnoses and were included in analyses. Of these individuals, 10 373 (34%) were female and 19 873 (66%) were male; 2236 (8%) were of minority ethnicity; 382 (1%) had a diagnosis of eating disorder and 29 864 (99%) had another mental health diagnosis. Compared with patients with other mental health diagnoses who died by suicide, patients with eating disorders were younger (median age 33 years [range 15-90] vs 45 years [10-100]), more often female (343 [90%] female and 39 [10%] male in the eating disorders group; 10 030 [34%] female and 19 834 [66%] male in the other diagnoses group), and less likely to have evidence of conventional risk factors for suicide such as living alone (odds ratio [OR] 0·68, 95% CI 0·55-0·84). 22 (6%) of 382 were from a minority ethnic group. Patients with an eating disorder were characterised by a greater clinical complexity (eg, self-harm [OR 2·31, 95% CI 1·78-3·00], comorbidity [9·79, 6·81-14·1], and longer duration of illness [1·95, 1·56-2·43]), and were more likely to have died following overdoses (2·00, 1·62-2·45) than patients with other diagnoses. Childhood abuse (52 [37%] of 140) and domestic violence (18 [20%] of 91) were common in patients with eating disorders. Similar to patients with other diagnoses, most (244 [75%] of 326) of those with eating disorders who died by suicide were rated as low risk by clinicians at last contact. The number of suicide deaths in patients with eating disorders rose between 1997 and 2021 (incidence rate ratio [IRR] 1·03, 95% CI 1·02-1·05; p<0·0001), but rates fell when accounting for the greater number of patients entering mental health services (IRR 0·97, 0·95-1·00; p=0·033). INTERPRETATION: This study was focused on people who sought help from mental health services. It did not consider subtypes of eating disorders or include a control group, but it does highlight possible areas for intervention. The comprehensive provision of evidence-based treatment for eating disorders and underlying conditions to address the clinical complexity in these patients might help to reduce suicide. Recognising limitations in clinical risk assessment, addressing early life experiences and current adversities, and appropriate prescribing might also be of benefit. Suicide prevention must remain a priority for eating disorder services and mental health care more widely. FUNDING: The Healthcare Quality Improvement Partnership.

Substance use and self-poisoning in schizophrenia: 11-year findings from a national clinical survey of suicide in mental health patients in the UK.

Suicide is the leading cause of unnatural death among people with schizophrenia. Substance use is a highly prevalent comorbid feature of schizophrenia and a modifiable risk factor for suicide. However, no studies have examined changes in the frequency of substance use or self-poisoning in those who died by suicide over time. Knowing this could support more tailored approaches to reducing specific risk factors and access to means in those with schizophrenia who are at risk of suicide. We conducted an 11-year observational study on a clinical survey of people with schizophrenia in the UK who died by suicide within 12 months of contact with mental health services between 2010 and 2020 (n = 2718). Overall, alcohol, cannabis and stimulants were the most frequently reported substances. The odds of lifetime use significantly increased over time for cannabis, stimulants, heroin, and benzodiazepines. There were differences in socio-demographic, behavioural and clinical factors between those with recent and historical alcohol and drug use before death. Deaths by hanging, jumping and self-poisoning were the most common suicide methods. Though deaths by hanging significantly increased over time, deaths by self-poisoning significantly decreased, especially by means of psychotropic medication and opioids. To improve risk management, clinical efforts should focus on identifying and treating people with schizophrenia using specific substances. Nationwide initiatives for improving safety in prescribing could be contributing to reduced risks of suicide via self-poisoning in this group.

Psychiatric in-patient care in England: as safe as it can be? An examination of in-patient suicide between 2009 and 2020.

BACKGROUND: Psychiatric in-patients have a greatly elevated risk of suicide. We aimed to examine trends in in-patient suicide rates and determine if characteristics of in-patients who died by suicide have changed over time. METHODS: We identified all in-patients in England who died by suicide between 2009 and 2020 from the National Confidential Inquiry into Suicide and Safety in Mental Health. Suicide rates were calculated using data from Hospital Episodes Statistics. RESULTS: The rate of in-patient suicide per 100 000 bed days fell by 41.9% between 2009-2011 and 2018-2020. However, since 2016 the rate has remained static with no significant fall. Rates fell in men, those aged 30-59, and those with schizophrenia and other delusional disorders or personality disorder. Rates also fell for suicide by hanging (including hanging on the ward) and jumping. No falls were seen in suicide rates among women, younger and older age groups, and those with affective disorder. There was no indication of a transfer of risk to the post-discharge period or to home treatment/crisis care. More in-patients in the latter part of the study were aged under 25, were on authorised leave, and had psychiatric comorbidity. CONCLUSIONS: In-patient suicide has significantly fallen since 2009, suggesting patient safety may have improved. The recent slowdown in the fall in rates, however, highlights that renewed preventative efforts are needed. These should include a greater focus on women, younger and older patients, and those with affective disorder. Careful reviews prior to granting leave are important to ensure a safe transition into the community.

Homicide as the first conviction: A retrospective cohort study.

The association between previous convictions and perpetrating homicide has been previously described but little is known about the characteristics of homicide offenders without previous convictions. By utilizing the unique database on homicide offenders held by the National Confidential Inquiry into Suicide and Safety in Mental Health, this study aimed to describe the sample of homicide perpetrators in England and Wales who have committed homicide as their first offense based on their sociodemographic and clinical characteristics. Compared with those with previous convictions, homicide offenders without previous convictions were more likely to be female and a member of an ethnic minority group. More of those without previous convictions belonged to the youngest (<25) and oldest (>55) age groups and were more likely to kill somebody family member or a spouse. Schizophrenia and other delusional disorders as well as affective disorders were more prevalent in those without previous convictions as were mental illness/insanity as a circumstance in homicide, but those without previous convictions were less likely to have been in previous contact with mental health services. There are clear sociodemographic and clinical differences between homicide perpetrators with and without previous convictions. Implications of these findings are discussed.

Tachykinins and the potential causal factors for post-COVID-19 condition.

The most prevalent symptoms of post-COVID-19 condition are pulmonary dysfunction, fatigue and muscle weakness, anxiety, anosmia, dysgeusia, headaches, difficulty in concentrating, sexual dysfunction, and digestive disturbances. Hence, neurological dysfunction and autonomic impairments predominate in post-COVID-19 condition. Tachykinins including the most studied substance P are neuropeptides expressed throughout the nervous and immune systems, and contribute to many physiopathological processes in the nervous, immune, gastrointestinal, respiratory, urogenital, and dermal systems and participate in inflammation, nociception, and cell proliferation. Substance P is a key molecule in neuroimmune crosstalk; immune cells near the peripheral nerve endings can send signals to the brain with cytokines, which highlights the important role of tachykinins in neuroimmune communication. We reviewed the evidence that relates the symptoms of post-COVID-19 condition to the functions of tachykinins and propose a putative pathogenic mechanism. The antagonism of tachykinins receptors can be a potential treatment target.

Oral hygiene, mouthwash usage and cardiovascular mortality during 18.8 years of follow-up.

Aim(s) We tested the following hypotheses: would better oral hygiene self-care (OHS) influence cardiovascular (CVD) mortality? Will using mouthwash in addition to OHS affect CVD mortality? How does mouthwash usage impact the oral microbes?Design and methods Among 354 dentate subjects from the Kuopio Oral Health and Heart study, the association of OHS with CVD mortality was assessed using Cox regression analyses, adjusting for age, sex, smoking, dyslipidemia, diabetes, hypertension and education. Additionally, whether using mouthwash would affect this relationship was evaluated.Results In the multivariable-adjusted models, OHS was associated with a 51% reduction in the risk of CVD mortality (hazard ratio [HR] 0.49 [0.28-0.85]; p = 0.01). Even those who had coronary artery disease at baseline showed a marginally significant benefit (0.50 [0.24-1.06]; p = 0.07). However, mouthwash usage did not change OHS effects (HR = 0.49 [0.27-0.87]; p = 0.01), indicating no additional benefits nor detriments. All tested microbes trended to decrease with mouthwash usage in the short term, but none were statistically significant.Conclusion Good OHS significantly lowered the risk of CVD mortality relative to poor OHS. Mouthwash usage did not show any long-term harm or benefit on CVD mortality beyond the benefits rendered by brushing and flossing.

Sex-Specific Metabolic Pathways Were Associated with Alzheimer's Disease (AD) Endophenotypes in the European Medical Information Framework for AD Multimodal Biomarker Discovery Cohort.

BACKGROUND: physiological differences between males and females could contribute to the development of Alzheimer's Disease (AD). Here, we examined metabolic pathways that may lead to precision medicine initiatives. METHODS: We explored whether sex modifies the association of 540 plasma metabolites with AD endophenotypes including diagnosis, cerebrospinal fluid (CSF) biomarkers, brain imaging, and cognition using regression analyses for 695 participants (377 females), followed by sex-specific pathway overrepresentation analyses, APOE ε4 stratification and assessment of metabolites' discriminatory performance in AD. RESULTS: In females with AD, vanillylmandelate (tyrosine pathway) was increased and tryptophan betaine (tryptophan pathway) was decreased. The inclusion of these two metabolites (area under curve (AUC) = 0.83, standard error (SE) = 0.029) to a baseline model (covariates + CSF biomarkers, AUC = 0.92, SE = 0.019) resulted in a significantly higher AUC of 0.96 (SE = 0.012). Kynurenate was decreased in males with AD (AUC = 0.679, SE = 0.046). CONCLUSIONS: metabolic sex-specific differences were reported, covering neurotransmission and inflammation pathways with AD endophenotypes. Two metabolites, in pathways related to dopamine and serotonin, were associated to females, paving the way to personalised treatment.

Leakage pressures for gasketless superhydrophobic fluid interconnects for modular lab-on-a-chip systems.

Chip-to-chip and world-to-chip fluidic interconnections are paramount to enable the passage of liquids between component chips and to/from microfluidic systems. Unfortunately, most interconnect designs add additional physical constraints to chips with each additional interconnect leading to over-constrained microfluidic systems. The competing constraints provided by multiple interconnects induce strain in the chips, creating indeterminate dead volumes and misalignment between chips that comprise the microfluidic system. A novel, gasketless superhydrophobic fluidic interconnect (GSFI) that uses capillary forces to form a liquid bridge suspended between concentric through-holes and acting as a fluid passage was investigated. The GSFI decouples the alignment between component chips from the interconnect function and the attachment of the meniscus of the liquid bridge to the edges of the holes produces negligible dead volume. This passive seal was created by patterning parallel superhydrophobic surfaces (water contact angle ≥ 150°) around concentric microfluidic ports separated by a gap. The relative position of the two polymer chips was determined by passive kinematic constraints, three spherical ball bearings seated in v-grooves. A leakage pressure model derived from the Young-Laplace equation was used to estimate the leakage pressure at failure for the liquid bridge. Injection-molded, Cyclic Olefin Copolymer (COC) chip assemblies with assembly gaps from 3 to 240 µm were used to experimentally validate the model. The maximum leakage pressure measured for the GSFI was 21.4 kPa (3.1 psig), which corresponded to a measured mean assembly gap of 3 µm, and decreased to 0.5 kPa (0.073 psig) at a mean assembly gap of 240 µm. The effect of radial misalignment on the efficacy of the gasketless seals was tested and no significant effect was observed. This may be a function of how the liquid bridges are formed during the priming of the chip, but additional research is required to test that hypothesis.

Replication study of plasma proteins relating to Alzheimer's pathology.

INTRODUCTION: This study sought to discover and replicate plasma proteomic biomarkers relating to Alzheimer's disease (AD) including both the "ATN" (amyloid/tau/neurodegeneration) diagnostic framework and clinical diagnosis. METHODS: Plasma proteins from 972 subjects (372 controls, 409 mild cognitive impairment [MCI], and 191 AD) were measured using both SOMAscan and targeted assays, including 4001 and 25 proteins, respectively. RESULTS: Protein co-expression network analysis of SOMAscan data revealed the relation between proteins and "N" varied across different neurodegeneration markers, indicating that the ATN variants are not interchangeable. Using hub proteins, age, and apolipoprotein E ε4 genotype discriminated AD from controls with an area under the curve (AUC) of 0.81 and MCI convertors from non-convertors with an AUC of 0.74. Targeted assays replicated the relation of four proteins with the ATN framework and clinical diagnosis. DISCUSSION: Our study suggests that blood proteins can predict the presence of AD pathology as measured in the ATN framework as well as clinical diagnosis.

Tenecteplase for Acute Ischemic Stroke Treatment.

The introduction of thrombolytic therapy in the 1990s has transformed acute ischemic stroke treatment. Thus far, intravenous recombinant tissue plasminogen activator (rt-PA) also known as alteplase is the only thrombolytic proven to be efficacious and approved by the United States Food and Drug Administration. But the thrombolytic agent tenecteplase (TNK) is emerging as a potential replacement for rt-PA. TNK has greater fibrin specificity, slower clearance, and higher resistance to plasminogen activator inhibitor-1 than rt-PA. Hence, TNK has the potential to provide superior lysis with fewer hemorrhagic complications. Also, easier bolus-only administration makes TNK a very practical rt-PA alternative. In several clinical trials, TNK has shown similar efficacy and safety to rt-PA, and the potential to be at least noninferior to rt-PA in some settings. TNK may be superior to rt-PA for reperfusing large vessel occlusions in patients with salvageable penumbra, although this has not yet translated to improved clinical outcomes. Further phase 3 studies are in progress comparing rt-PA with TNK for acute ischemic stroke during the first 4.5 hours. Studies are also in progress to evaluate the use of TNK for extended applications, such as wake-up stroke.

Homicide by men diagnosed with schizophrenia: national case-control study.

BACKGROUND: Some people diagnosed with schizophrenia are more prone to committing acts of serious violence, especially in the presence of drug or alcohol misuse. The rarity of homicide has meant that no large controlled study has previously examined clinical risk factors. AIMS: To determine the risk factors for homicide by males diagnosed with schizophrenia. METHOD: A national nested case-control study of all previously admitted males diagnosed with schizophrenia, convicted of homicide between 1 January 1997 and 31 December 2012. Univariate and multivariable conditional logistic regression models were fitted to identify predictors of homicide in this population. RESULTS: During the observation period 160 male patients with schizophrenia and a history of psychiatric admission were convicted of homicide, and they were matched with 542 male control patients who had not been convicted of homicide. Patients who committed homicide were more likely to have a history of violence and comorbid personality disorder or drug misuse. They were more likely to have missed their last contact with services prior to the offence and to have been non-adherent with their treatment plan. Almost all (94%) of homicides were committed by patients who had a history of alcohol or drug misuse and/or who were not in receipt of planned treatment. CONCLUSIONS: In England and Wales, homicides by patients with schizophrenia without substance misuse and in receipt of planned care are exceptionally rare. To prevent serious violence, mental health services should focus on drug and alcohol misuse, treatment adherence and maintaining contact with services.

Affinity enrichment of extracellular vesicles from plasma reveals mRNA changes associated with acute ischemic stroke.

Currently there is no in vitro diagnostic test for acute ischemic stroke (AIS), yet rapid diagnosis is crucial for effective thrombolytic treatment. We previously demonstrated the utility of CD8(+) T-cells' mRNA expression for AIS detection; however extracellular vesicles (EVs) were not evaluated as a source of mRNA for AIS testing. We now report a microfluidic device for the rapid and efficient affinity-enrichment of CD8(+) EVs and subsequent EV's mRNA analysis using droplet digital PCR (ddPCR). The microfluidic device contains a dense array of micropillars modified with anti-CD8α monoclonal antibodies that enriched 158 ± 10 nm sized EVs at 4.3 ± 2.1 × 109 particles/100 µL of plasma. Analysis of mRNA from CD8(+) EVs and their parental T-cells revealed correlation in the expression for AIS-specific genes in both cell lines and healthy donors. In a blinded study, 80% test positivity for AIS patients and controls was revealed with a total analysis time of 3.7 h.

Dickkopf-1 Overexpression in vitro Nominates Candidate Blood Biomarkers Relating to Alzheimer's Disease Pathology.

BACKGROUND: Previous studies suggest that Dickkopf-1 (DKK1), an inhibitor of Wnt signaling, plays a role in amyloid-induced toxicity and hence Alzheimer's disease (AD). However, the effect of DKK1 expression on protein expression, and whether such proteins are altered in disease, is unknown. OBJECTIVE: We aim to test whether DKK1 induced protein signature obtained in vitro were associated with markers of AD pathology as used in the amyloid/tau/neurodegeneration (ATN) framework as well as with clinical outcomes. METHODS: We first overexpressed DKK1 in HEK293A cells and quantified 1,128 proteins in cell lysates using aptamer capture arrays (SomaScan) to obtain a protein signature induced by DKK1. We then used the same assay to measure the DKK1-signature proteins in human plasma in two large cohorts, EMIF (n = 785) and ANM (n = 677). RESULTS: We identified a 100-protein signature induced by DKK1 in vitro. Subsets of proteins, along with age and apolipoprotein E ɛ4 genotype distinguished amyloid pathology (A + T-N-, A+T+N-, A+T-N+, and A+T+N+) from no AD pathology (A-T-N-) with an area under the curve of 0.72, 0.81, 0.88, and 0.85, respectively. Furthermore, we found that some signature proteins (e.g., Complement C3 and albumin) were associated with cognitive score and AD diagnosis in both cohorts. CONCLUSIONS: Our results add further evidence for a role of DKK regulation of Wnt signaling in AD and suggest that DKK1 induced signature proteins obtained in vitro could reflect theATNframework as well as predict disease severity and progression in vivo.

Liquid biopsy markers for stroke diagnosis.

INTRODUCTION: There is a short time window (4.5 h) for the effective treatment of acute ischemic stroke (AIS), which uses recombinant tissue plasminogen activator (rt-PA). Unfortunately, this short therapeutic timeframe is a contributing factor to the relatively small number of patients (~7%) that receive rt-PA. While neuroimaging is the major diagnostic for AIS, more timely decisions could be made using a molecular diagnostic. AREAS COVERED: In this review, we survey neuroimaging techniques used to diagnose stroke and their limitations. We also highlight the potential of various molecular/cellular biomarkers, especially peripheral blood-based (i.e. liquid biopsy) biomarkers, for diagnosing stroke to allow for precision decisions on managing stroke in a timely manner. Both protein and nucleic acid molecular biomarkers are reviewed. In particular, mRNA markers are discussed for AIS and hemorrhagic stroke diagnosis sourced from both cells and extracellular vesicles. EXPERT OPINION: While there are a plethora of molecular markers for stroke diagnosis that have been reported, they have yet to be FDA-cleared. Possible reasons include the inability for these markers to appear in sufficient quantities for highly sensitive clinical decisions within the rt-PA therapeutic time.

Early Post-Discharge Suicide in Mental Health Patients: Findings From a National Clinical Survey.

Studies on suicide by recently discharged mental health patients have reported a high number of deaths in the early post-discharge period, which has led to recommendations of follow-up within 7 days (d). More recently, the National Confidential Inquiry into Suicide and Safety in Mental Health (NCISH) proposed a more "stringent" follow-up period of 2-3 days (d) after discharge. Patients who died within this early time-frame post-discharge were more likely to die before the follow-up appointment occurred. They more often had a primary diagnosis of a personality disorder, self-discharged, and had a higher frequency of death by jumping from a height or in front of the vehicle compared to later deaths. This study provides practical implications for post-discharge management and safety planning. Clinicians should be aware of (1) the increased risk of immediate suicide in the post-discharge period by people with a diagnosis of personality disorder, (2) immediate suicide risk in patients who initiate their own discharge, and (3) the increased risk of death by jumping from a height or in front of the vehicle in the immediate post-discharge period. Our findings support the recent recommendation from NCISH that follow-up should occur within 3 d of discharge from in-patient care.

Validation of Plasma Proteomic Biomarkers Relating to Brain Amyloid Burden in the EMIF-Alzheimer's Disease Multimodal Biomarker Discovery Cohort.

We have previously investigated, discovered, and replicated plasma protein biomarkers for use to triage potential trials participants for PET or cerebrospinal fluid measures of Alzheimer's disease (AD) pathology. This study sought to undertake validation of these candidate plasma biomarkers in a large, multi-center sample collection. Targeted plasma analyses of 34 proteins with prior evidence for prediction of in vivo pathology were conducted in up to 1,000 samples from cognitively healthy elderly individuals, people with mild cognitive impairment, and in patients with AD-type dementia, selected from the EMIF-AD catalogue. Proteins were measured using Luminex xMAP, ELISA, and Meso Scale Discovery assays. Seven proteins replicated in their ability to predict in vivo amyloid pathology. These proteins form a biomarker panel that, along with age, could significantly discriminate between individuals with high and low amyloid pathology with an area under the curve of 0.74. The performance of this biomarker panel remained consistent when tested in apolipoprotein E ɛ4 non-carrier individuals only. This blood-based panel is biologically relevant, measurable using practical immunocapture arrays, and could significantly reduce the cost incurred to clinical trials through screen failure.

Discovery and validation of plasma proteomic biomarkers relating to brain amyloid burden by SOMAscan assay.

INTRODUCTION: Plasma proteins have been widely studied as candidate biomarkers to predict brain amyloid deposition to increase recruitment efficiency in secondary prevention clinical trials for Alzheimer's disease. Most such biomarker studies are targeted to specific proteins or are biased toward high abundant proteins. METHODS: 4001 plasma proteins were measured in two groups of participants (discovery group = 516, replication group = 365) selected from the European Medical Information Framework for Alzheimer's disease Multimodal Biomarker Discovery study, all of whom had measures of amyloid. RESULTS: A panel of proteins (n = 44), along with age and apolipoprotein E (APOE) ε4, predicted brain amyloid deposition with good performance in both the discovery group (area under the curve = 0.78) and the replication group (area under the curve = 0.68). Furthermore, a causal relationship between amyloid and tau was confirmed by Mendelian randomization. DISCUSSION: The results suggest that high-dimensional plasma protein testing could be a useful and reproducible approach for measuring brain amyloid deposition.

Primary fatty amides in plasma associated with brain amyloid burden, hippocampal volume, and memory in the European Medical Information Framework for Alzheimer's Disease biomarker discovery cohort.

INTRODUCTION: A critical and as-yet unmet need in Alzheimer's disease (AD) is the discovery of peripheral small molecule biomarkers. Given that brain pathology precedes clinical symptom onset, we set out to test whether metabolites in blood associated with pathology as indexed by cerebrospinal fluid (CSF) AD biomarkers. METHODS: This study analyzed 593 plasma samples selected from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery study, of individuals who were cognitively healthy (n = 242), had mild cognitive impairment (n = 236), or had AD-type dementia (n = 115). Logistic regressions were carried out between plasma metabolites (n = 883) and CSF markers, magnetic resonance imaging, cognition, and clinical diagnosis. RESULTS: Eight metabolites were associated with amyloid ß and one with t-tau in CSF, these were primary fatty acid amides (PFAMs), lipokines, and amino acids. From these, PFAMs, glutamate, and aspartate also associated with hippocampal volume and memory. DISCUSSION: PFAMs have been found increased and associated with amyloid ß burden in CSF and clinical measures.

A metabolite-based machine learning approach to diagnose Alzheimer-type dementia in blood: Results from the European Medical Information Framework for Alzheimer disease biomarker discovery cohort.

INTRODUCTION: Machine learning (ML) may harbor the potential to capture the metabolic complexity in Alzheimer Disease (AD). Here we set out to test the performance of metabolites in blood to categorize AD when compared to CSF biomarkers. METHODS: This study analyzed samples from 242 cognitively normal (CN) people and 115 with AD-type dementia utilizing plasma metabolites (n = 883). Deep Learning (DL), Extreme Gradient Boosting (XGBoost) and Random Forest (RF) were used to differentiate AD from CN. These models were internally validated using Nested Cross Validation (NCV). RESULTS: On the test data, DL produced the AUC of 0.85 (0.80-0.89), XGBoost produced 0.88 (0.86-0.89) and RF produced 0.85 (0.83-0.87). By comparison, CSF measures of amyloid, p-tau and t-tau (together with age and gender) produced with XGBoost the AUC values of 0.78, 0.83 and 0.87, respectively. DISCUSSION: This study showed that plasma metabolites have the potential to match the AUC of well-established AD CSF biomarkers in a relatively small cohort. Further studies in independent cohorts are needed to validate whether this specific panel of blood metabolites can separate AD from controls, and how specific it is for AD as compared with other neurodegenerative disorders.

MRI predictors of amyloid pathology: results from the EMIF-AD Multimodal Biomarker Discovery study.

BACKGROUND: With the shift of research focus towards the pre-dementia stage of Alzheimer's disease (AD), there is an urgent need for reliable, non-invasive biomarkers to predict amyloid pathology. The aim of this study was to assess whether easily obtainable measures from structural MRI, combined with demographic data, cognitive data and apolipoprotein E (APOE) ε4 genotype, can be used to predict amyloid pathology using machine-learning classification. METHODS: We examined 810 subjects with structural MRI data and amyloid markers from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery study, including subjects with normal cognition (CN, n = 337, age 66.5 ± 7.2, 50% female, 27% amyloid positive), mild cognitive impairment (MCI, n = 375, age 69.1 ± 7.5, 53% female, 63% amyloid positive) and AD dementia (n = 98, age 67.0 ± 7.7, 48% female, 97% amyloid positive). Structural MRI scans were visually assessed and Freesurfer was used to obtain subcortical volumes, cortical thickness and surface area measures. We first assessed univariate associations between MRI measures and amyloid pathology using mixed models. Next, we developed and tested an automated classifier using demographic, cognitive, MRI and APOE ε4 information to predict amyloid pathology. A support vector machine (SVM) with nested 10-fold cross-validation was applied to identify a set of markers best discriminating between amyloid positive and amyloid negative subjects. RESULTS: In univariate associations, amyloid pathology was associated with lower subcortical volumes and thinner cortex in AD-signature regions in CN and MCI. The multi-variable SVM classifier provided an area under the curve (AUC) of 0.81 ± 0.07 in MCI and an AUC of 0.74 ± 0.08 in CN. In CN, selected features for the classifier included APOE ε4, age, memory scores and several MRI measures such as hippocampus, amygdala and accumbens volumes and cortical thickness in temporal and parahippocampal regions. In MCI, the classifier including demographic and APOE ε4 information did not improve after additionally adding imaging measures. CONCLUSIONS: Amyloid pathology is associated with changes in structural MRI measures in CN and MCI. An automated classifier based on clinical, imaging and APOE ε4 data can identify the presence of amyloid pathology with a moderate level of accuracy. These results could be used in clinical trials to pre-screen subjects for anti-amyloid therapies.