Serum neurofilament light in familial Alzheimer disease: A marker of early neurodegeneration.

OBJECTIVES: To investigate whether serum neurofilament light (NfL) concentration is increased in familial Alzheimer disease (FAD), both pre and post symptom onset, and whether it is associated with markers of disease stage and severity. METHODS: We recruited 48 individuals from families with PSEN1 or APP mutations to a cross-sectional study: 18 had symptomatic Alzheimer disease (AD) and 30 were asymptomatic but at 50% risk of carrying a mutation. Serum NfL was measured using an ultrasensitive immunoassay on the single molecule array (Simoa) platform. Cognitive testing and MRI were performed; 33 participants had serial MRI, allowing calculation of atrophy rates. Genetic testing established mutation status. A generalized least squares regression model was used to compare serum NfL among symptomatic mutation carriers, presymptomatic carriers, and noncarriers, adjusting for age and sex. Spearman coefficients assessed associations between serum NfL and (1) estimated years to/from symptom onset (EYO), (2) cognitive measures, and (3) MRI measures of atrophy. RESULTS: Nineteen of the asymptomatic participants were mutation carriers (mean EYO -9.6); 11 were noncarriers. Compared with noncarriers, serum NfL concentration was higher in both symptomatic (p < 0.0001) and presymptomatic mutation carriers (p = 0.007). Across all mutation carriers, serum NfL correlated with EYO (ρ = 0.81, p < 0.0001) and multiple cognitive and imaging measures, including Mini-Mental State Examination (ρ = -0.62, p = 0.0001), Clinical Dementia Rating Scale sum of boxes (ρ = 0.79, p < 0.0001), baseline brain volume (ρ = -0.62, p = 0.0002), and whole-brain atrophy rate (ρ = 0.53, p = 0.01). CONCLUSIONS: Serum NfL concentration is increased in FAD prior to symptom onset and correlates with measures of disease stage and severity. Serum NfL may thus be a feasible biomarker of early AD-related neurodegeneration

Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression

Multiple, complex molecular events characterize cancer development and progression(1,2). Deciphering the molecular networks that distinguish organ- confined disease from metastatic disease may lead to the identification of critical biomarkers for cancer invasion and disease aggressiveness. Although gene and protein expression have been extensively profiled in human tumours, little is known about the global metabolomic alterations that characterize neoplastic progression. Using a combination of high- throughput liquid- and- gas- chromatography- based mass spectrometry, we profiled more than 1,126 metabolites across 262 clinical samples related to prostate cancer ( 42 tissues and 110 each of urine and plasma). These unbiased metabolomic profiles were able to distinguish benign prostate, clinically localized prostate cancer and metastatic disease. Sarcosine, an N- methyl derivative of the amino acid glycine, was identified as a differential metabolite that was highly increased during prostate cancer progression to metastasis and can be detected non- invasively in urine. Sarcosine levels were also increased in invasive prostate cancer cell lines relative to benign prostate epithelial cells. Knockdown of glycine- N- methyl transferase, the enzyme that generates sarcosine from glycine, attenuated prostate cancer invasion. Addition of exogenous sarcosine or knockdown of the enzyme that leads to sarcosine degradation, sarcosine dehydrogenase, induced an invasive phenotype in benign prostate epithelial cells. Androgen receptor and the ERG gene fusion product coordinately regulate components of the sarcosine pathway. Here, by profiling the metabolomic alterations of prostate cancer progression, we reveal sarcosine as a potentially important metabolic intermediary of cancer cell invasion and aggressivity.Early Detection Research Network ; National Institutes of Health ; MTTC ; Clinical Translational Science Award ; Fund for Discovery of the University of Michigan Comprehensive Cancer Center ; University of Michigan Cancer Biostatistics Training Grant ; Doris Duke Charitable FoundationWe thank J. Granger for help in manuscript preparation, J. Siddiqui and R. Varambally for help with the clinical database, and A. Vellaichamy and S. Pullela for technical assistance. We thank K. Pienta for access to metastatic prostate cancer samples from the University of Michigan Prostate SPORE rapid autopsy programme. This work is supported in part by the Early Detection Research Network (A.M.C., J.T.W.), National Institutes of Health (A.S., S.P., J.B., T.M.R., D.G., G.S.O. and A.M.C.) and an MTTC grant (G.S.O. and A.S.). A.M.C. is supported by a Clinical Translational Science Award from the Burroughs Welcome Foundation. A. S. is supported by a grant from the Fund for Discovery of the University of Michigan Comprehensive Cancer Center. L. M. P. is supported by the University of Michigan Cancer Biostatistics Training Grant. A. M. C and S. P. are supported by the Doris Duke Charitable Foundation.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62661/1/nature07762.pd

Presymptomatic atrophy in autosomal dominant Alzheimer's disease: A serial magnetic resonance imaging study.

INTRODUCTION: Identifying at what point atrophy rates first change in Alzheimer's disease is important for informing design of presymptomatic trials. METHODS: Serial T1-weighted magnetic resonance imaging scans of 94 participants (28 noncarriers, 66 carriers) from the Dominantly Inherited Alzheimer Network were used to measure brain, ventricular, and hippocampal atrophy rates. For each structure, nonlinear mixed-effects models estimated the change-points when atrophy rates deviate from normal and the rates of change before and after this point. RESULTS: Atrophy increased after the change-point, which occurred 1-1.5 years (assuming a single step change in atrophy rate) or 3-8 years (assuming gradual acceleration of atrophy) before expected symptom onset. At expected symptom onset, estimated atrophy rates were at least 3.6 times than those before the change-point. DISCUSSION: Atrophy rates are pathologically increased up to seven years before "expected onset". During this period, atrophy rates may be useful for inclusion and tracking of disease progression

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

Volumes, spatial extents and a probabilistic atlas of the human basal ganglia and thalamus

The basal ganglia and thalamus are involved in processing all physiological behaviors and affected by many diseases. Accurate localization is a crucial issue in neuroimaging, particularly when working with groups of normalized images in a standard stereotaxic space. Here, manual delineation of the central structures (thalamus; nucleus caudatus and accumbens; putamen, pallidum, substantia nigra) was performed on 30 high resolution MRIs of healthy young adults (15 female, median age 31 years) in native space. Protocol inter-rater reliabilities were quantified as structure overlap (similarity indices, SIs). Structural volumes were calculated in native space, and after spatial normalization to stereotaxic space (MNI/ICBM152) and in relation to hemispheric volumes. Spatial extents relative to the anterior commissure (AC) were extracted. The 30 resulting atlases were then used to create probabilistic maps in stereotaxic space. Inter-rater SIs were high at 0.85-0.92 except for the nucleus accumbens. In native space, caudate, nucleus accumbens and putamen were significantly larger on the left, and the globus pallidus larger in males. After normalizing for brain volume, the nucleus accumbens, putamen and thalamus were larger on the left, with the gender difference in the globus pallidus still detectable. Some of these volume differences translated into significantly different distances from the AC. The probabilistic maps showed that overall the central structures' boundaries are relatively unchanged after spatial normalization. We present a comprehensive assessment of thalamic and basal ganglia volumetric and geometric data in both native and stereotaxic spaces. Probabilistic maps in MNI/ICBMI52 space will allow accurate localization in group analyses. (C) 2007 Elsevier Inc. All rights reserved

Impact of the COVID-19 pandemic on patients with paediatric cancer in low-income, middle-income and high-income countries: a multicentre, international, observational cohort study

OBJECTIVES: Paediatric cancer is a leading cause of death for children. Children in low-income and middle-income countries (LMICs) were four times more likely to die than children in high-income countries (HICs). This study aimed to test the hypothesis that the COVID-19 pandemic had affected the delivery of healthcare services worldwide, and exacerbated the disparity in paediatric cancer outcomes between LMICs and HICs. DESIGN: A multicentre, international, collaborative cohort study. SETTING: 91 hospitals and cancer centres in 39 countries providing cancer treatment to paediatric patients between March and December 2020. PARTICIPANTS: Patients were included if they were under the age of 18 years, and newly diagnosed with or undergoing active cancer treatment for Acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, Wilms' tumour, sarcoma, retinoblastoma, gliomas, medulloblastomas or neuroblastomas, in keeping with the WHO Global Initiative for Childhood Cancer. MAIN OUTCOME MEASURE: All-cause mortality at 30 days and 90 days. RESULTS: 1660 patients were recruited. 219 children had changes to their treatment due to the pandemic. Patients in LMICs were primarily affected (n=182/219, 83.1%). Relative to patients with paediatric cancer in HICs, patients with paediatric cancer in LMICs had 12.1 (95% CI 2.93 to 50.3) and 7.9 (95% CI 3.2 to 19.7) times the odds of death at 30 days and 90 days, respectively, after presentation during the COVID-19 pandemic (p<0.001). After adjusting for confounders, patients with paediatric cancer in LMICs had 15.6 (95% CI 3.7 to 65.8) times the odds of death at 30 days (p<0.001). CONCLUSIONS: The COVID-19 pandemic has affected paediatric oncology service provision. It has disproportionately affected patients in LMICs, highlighting and compounding existing disparities in healthcare systems globally that need addressing urgently. However, many patients with paediatric cancer continued to receive their normal standard of care. This speaks to the adaptability and resilience of healthcare systems and healthcare workers globally

Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic

Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality

COVID-19 Host Genetics Initiative. A first update on mapping the human genetic architecture of COVID-19

The COVID-19 pandemic continues to pose a major public health threat, especially in countries with low vaccination rates. To better understand the biological underpinnings of SARS-CoV-2 infection and COVID-19 severity, we formed the COVID-19 Host Genetics Initiative1. Here we present a genome-wide association study meta-analysis of up to 125,584 cases and over 2.5 million control individuals across 60 studies from 25 countries, adding 11 genome-wide significant loci compared with those previously identified2. Genes at new loci, including SFTPD, MUC5B and ACE2, reveal compelling insights regarding disease susceptibility and severity.</p

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population