Cerebrospinal fluid biomarker panel of synaptic dysfunction in Alzheimer's disease and other neurodegenerative disorders

Introduction: Synaptic degeneration is a key part of the pathophysiology of neurodegenerative diseases, and biomarkers reflecting the pathological alterations are greatly needed. Method: Seventeen synaptic proteins were quantified in a pathology-confirmed cerebrospinal fluid cohort of patients with Alzheimer's disease (AD; n = 63), frontotemporal lobar degeneration (FTLD; n = 53), and Lewy body spectrum of disorders (LBD; n = 21), as well as healthy controls (HC; n = 48). Results: Comparisons revealed four distinct patterns: markers decreased across all neurodegenerative conditions compared to HC (the neuronal pentraxins), markers increased across all neurodegenerative conditions (14-3-3 zeta/delta), markers selectively increased in AD compared to other neurodegenerative conditions (neurogranin and beta-synuclein), and markers selectively decreased in LBD and FTLD compared to HC and AD (AP2B1 and syntaxin-1B). Discussion: Several of the synaptic proteins may serve as biomarkers for synaptic dysfunction in AD, LBD, and FTLD. Additionally, differential patterns of synaptic protein alterations seem to be present across neurodegenerative diseases. Highlights: A panel of synaptic proteins were quantified in the cerebrospinal fluid using mass spectrometry. We compared Alzheimer's disease, frontotemporal degeneration, and Lewy body spectrum of disorders. Pathology was confirmed by autopsy or familial mutations. We discovered synaptic biomarkers for synaptic degeneration and cognitive decline. We found differential patterns of synaptic proteins across neurodegenerative diseases

Parkinson's disease biomarkers: perspective from the NINDS Parkinson's Disease Biomarkers Program

Biomarkers for Parkinson's disease (PD) diagnosis, prognostication and clinical trial cohort selection are an urgent need. While many promising markers have been discovered through the National Institute of Neurological Disorders and Stroke Parkinson's Disease Biomarker Program (PDBP) and other mechanisms, no single PD marker or set of markers are ready for clinical use. Here we discuss the current state of biomarker discovery for platforms relevant to PDBP. We discuss the role of the PDBP in PD biomarker identification and present guidelines to facilitate their development. These guidelines include: harmonizing procedures for biofluid acquisition and clinical assessments, replication of the most promising biomarkers, support and encouragement of publications that report negative findings, longitudinal follow-up of current cohorts including the PDBP, testing of wearable technologies to capture readouts between study visits and development of recently diagnosed (de novo) cohorts to foster identification of the earliest markers of disease onset

Biomarker-driven phenotyping in Parkinson's disease: A translational missing link in disease-modifying clinical trials

Past clinical trials of putative neuroprotective therapies have targeted PD as a single pathogenic disease entity. From an Oslerian clinicopathological perspective, the wide complexity of PD converges into Lewy bodies and justifies a reductionist approach to PD: A single-mechanism therapy can affect most of those sharing the classic pathological hallmark. From a systems-biology perspective, PD is a group of disorders that, while related by sharing the feature of nigral dopamine-neuron degeneration, exhibit unique genetic, biological, and molecular abnormalities, which probably respond differentially to a given therapeutic approach, particularly for strategies aimed at neuroprotection. Under this model, only biomarker-defined, homogenous subtypes of PD are likely to respond optimally to therapies proven to affect the biological processes within each subtype. Therefore, we suggest that precision medicine applied to PD requires a reevaluation of the biomarker-discovery effort. This effort is currently centered on correlating biological measures to clinical features of PD and on identifying factors that predict whether various prodromal states will convert into the classical movement disorder. We suggest, instead, that subtyping of PD requires the reverse view, where abnormal biological signals (i.e., biomarkers), rather than clinical definitions, are used to define disease phenotypes. Successful development of disease-modifying strategies will depend on how relevant the specific biological processes addressed by an intervention are to the pathogenetic mechanisms in the subgroup of targeted patients. This precision-medicine approach will likely yield smaller, but well-defined, subsets of PD amenable to successful neuroprotection.Fil: Espay, Alberto J.. University of Cincinnati; Estados UnidosFil: Schwarzschild, Michael A.. Massachusetts General Hospital; Estados UnidosFil: Tanner, Caroline M.. University of California; Estados UnidosFil: Fernandez, Hubert H.. Cleveland Clinic; Estados UnidosFil: Simon, David K.. Harvard Medical School; Estados UnidosFil: Leverenz, James B.. Cleveland Clinic; Estados UnidosFil: Merola, Aristide. University of Cincinnati; Estados UnidosFil: Chen Plotkin, Alice. University of Pennsylvania; Estados UnidosFil: Brundin, Patrik. Van Andel Research Institute. Center for Neurodegenerative Science; Estados UnidosFil: Kauffman, Marcelo Andres. Universidad Austral; Argentina. Universidad Austral. Facultad de Ciencias Biomédicas. Instituto de Investigaciones en Medicina Traslacional. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Medicina Traslacional; Argentina. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos "Ramos Mejía"; ArgentinaFil: Erro, Roberto. Universita di Verona; Italia. University College London; Reino UnidoFil: Kieburtz, Karl. University of Rochester Medical Center; Estados UnidosFil: Woo, Daniel. University of Cincinnati; Estados UnidosFil: Macklin, Eric A.. Massachusetts General Hospital; Estados UnidosFil: Standaert, David G.. University of Alabama at Birmingahm; Estados UnidosFil: Lang, Anthony E.. University of Toronto; Canad

Neurofilament Light Chain Related to Longitudinal Decline in Frontotemporal Lobar Degeneration

OBJECTIVE: Accurate diagnosis and prognosis of frontotemporal lobar degeneration (FTLD) during life is an urgent concern in the context of emerging disease-modifying treatment trials. Few CSF markers have been validated longitudinally in patients with known pathology, and we hypothesized that CSF neurofilament light chain (NfL) would be associated with longitudinal cognitive decline in patients with known FTLD-TAR DNA binding protein ~43kD (TDP) pathology. METHODS: This case-control study evaluated CSF NfL, total tau, phosphorylated tau, and β-amyloid1-42 in patients with known FTLD-tau or FTLD-TDP pathology (n = 50) and healthy controls (n = 65) and an extended cohort of clinically diagnosed patients with likely FTLD-tau or FTLD-TDP (n = 148). Regression analyses related CSF analytes to longitudinal cognitive decline (follow-up ∼1 year), controlling for demographic variables and core AD CSF analytes. RESULTS: In FTLD-TDP with known pathology, CSF NfL is significantly elevated compared with controls and significantly associated with longitudinal decline on specific executive and language measures, after controlling for age, disease duration, and core AD CSF analytes. Similar findings are found in the extended cohort, also including clinically identified likely FTLD-TDP. Although CSF NfL is elevated in FTLD-tau compared with controls, the association between NfL and longitudinal cognitive decline is limited to executive measures. CONCLUSION: CSF NfL is associated with longitudinal clinical decline in relevant cognitive domains in patients with FTLD-TDP after controlling for demographic factors and core AD CSF analytes and may also be related to longitudinal decline in executive functioning in FTLD-tau

Evolution favors protein mutational robustness in sufficiently large populations

BACKGROUND: An important question is whether evolution favors properties such as mutational robustness or evolvability that do not directly benefit any individual, but can influence the course of future evolution. Functionally similar proteins can differ substantially in their robustness to mutations and capacity to evolve new functions, but it has remained unclear whether any of these differences might be due to evolutionary selection for these properties. RESULTS: Here we use laboratory experiments to demonstrate that evolution favors protein mutational robustness if the evolving population is sufficiently large. We neutrally evolve cytochrome P450 proteins under identical selection pressures and mutation rates in populations of different sizes, and show that proteins from the larger and thus more polymorphic population tend towards higher mutational robustness. Proteins from the larger population also evolve greater stability, a biophysical property that is known to enhance both mutational robustness and evolvability. The excess mutational robustness and stability is well described by existing mathematical theories, and can be quantitatively related to the way that the proteins occupy their neutral network. CONCLUSIONS: Our work is the first experimental demonstration of the general tendency of evolution to favor mutational robustness and protein stability in highly polymorphic populations. We suggest that this phenomenon may contribute to the mutational robustness and evolvability of viruses and bacteria that exist in large populations

Long-term dementia prevalence in Parkinson Disease: Glass half-full?

Introduction: Dementia occurs in up to 80% of Parkinson’s disease (PD) patients long-term, but studies reporting such high rates were published years ago and had relatively small sample sizes and other limitations. Objective: To determine long-term, cumulative dementia prevalence rates in PD using data from two large, ongoing, prospective observational studies. Design: Analyses of data from the Parkinson’s Progression Markers Initiative (PPMI) and a longstanding PD research clinical core at the University of Pennsylvania (Penn). Setting: PPMI is a multi-site international study, and Penn is a single site study at a tertiary movement disorders center. Participants: PPMI enrolls de novo, untreated PD participants at baseline, and Penn enrolls a convenience cohort from a large clinical center. Methods: For PPMI a cognitive battery and MDS-UPDRS Part I are administered annually, and the site investigator assigns a cognitive diagnosis annually. At Penn a comprehensive cognitive battery is administered either annually or biennially, and a cognitive diagnosis is made by expert consensus. Main Outcomes: Kaplan-Meier (KM) survival curves were fit for time from PD diagnosis to stable dementia diagnosis for each cohort, using assigned cognitive diagnosis of dementia as the primary endpoint (for both PPMI and Penn), and MoCA score <21 and MDS-UPDRS Part I cognition score ≥3 as secondary endpoints (for PPMI). In addition, cumulative dementia prevalence by PD disease duration was tabulated for each study and endpoint. Results: For the PPMI cohort, 417 PD participants were seen at baseline; estimated cumulative probability of dementia at year 10 disease duration were: 7% (site investigator diagnosis), 9% (MoCA) or 7.4% (MDS-UPDRS Part I cognition). For the Penn cohort, 389 PD participants were followed over time, with 184 participants (47% of cohort) eventually diagnosed with dementia. The KM curve for the Penn cohort had median time to dementia diagnosis =15 years (95% CI: 13-15) disease duration; the estimated cumulative probability of dementia was 27% at year 10, 50% at year 15, and 74% at year 20. Conclusions and Relevance: Results from two large, prospective studies suggest that dementia in Parkinson disease occurs less frequently, or later in the disease course, than often-cited previous research studies have reported

On Protection by Layout Randomization

Layout randomization is a powerful, popular technique for software protection. We present it and study it in programming-language terms. More specifically, we consider layout randomization as part of an implementation for a high-level programming language; the implementation translates this language to a lower-level language in which memory addresses are numbers. We analyze this implementation, by relating low-level attacks against the implementation to contexts in th

CSF proteomics in autosomal dominant Alzheimer's disease highlights parallels with sporadic disease

Autosomal dominant Alzheimer's disease (ADAD) offers a unique opportunity to study pathophysiological changes in a relatively young population with few comorbidities. A comprehensive investigation of proteome changes occurring in ADAD could provide valuable insights into AD-related biological mechanisms and uncover novel biomarkers and therapeutic targets. Furthermore, ADAD might serve as a model for sporadic AD, but in-depth proteome comparisons are lacking. We aimed to identify dysregulated CSF proteins in ADAD and determine the degree of overlap with sporadic AD. We measured 1472 proteins in CSF of PSEN1 or APP mutation carriers (n = 22) and age- and sex-matched controls (n = 20) from the Amsterdam Dementia Cohort using proximity extension-based immunoassays (PEA). We compared protein abundance between groups with two-sided t-tests and identified enriched biological pathways. Using the same protein panels in paired plasma samples, we investigated correlations between CSF proteins and their plasma counterparts. Finally, we compared our results with recently published PEA data from an international cohort of sporadic AD (n = 230) and non-AD dementias (n = 301). All statistical analyses were false discovery rate-corrected. We detected 66 differentially abundant CSF proteins (65 increased, 1 decreased) in ADAD compared to controls (q &lt; 0.05). The most strongly upregulated proteins (fold change &gt;1.8) were related to immunity (CHIT1, ITGB2, SMOC2), cytoskeletal structure (MAPT, NEFL) and tissue remodelling (TMSB10, MMP-10). Significant CSF-plasma correlations were found for the upregulated proteins SMOC2 and LILR1B. Of the 66 differentially expressed proteins, 36 had been measured previously in the sporadic dementias cohort, 34 of which (94%) were also significantly upregulated in sporadic AD, with a strong correlation between the fold changes of these proteins in both cohorts (rs = 0.730, P &lt; 0.001). Twenty-nine of the 36 proteins (81%) were also upregulated among non-AD patients with suspected AD co-pathology. This CSF proteomics study demonstrates substantial biochemical similarities between ADAD and sporadic AD, suggesting involvement of the same biological processes. Besides known AD-related proteins, we identified several relatively novel proteins, such as TMSB10, MMP-10 and SMOC2, which have potential as novel biomarkers. With shared pathophysiological CSF changes, ADAD study findings might be translatable to sporadic AD, which could greatly expedite therapy development.</p

The Eighth Data Release of the Sloan Digital Sky Survey: First Data from SDSS-III

The Sloan Digital Sky Survey (SDSS) started a new phase in August 2008, with new instrumentation and new surveys focused on Galactic structure and chemical evolution, measurements of the baryon oscillation feature in the clustering of galaxies and the quasar Ly alpha forest, and a radial velocity search for planets around ~8000 stars. This paper describes the first data release of SDSS-III (and the eighth counting from the beginning of the SDSS). The release includes five-band imaging of roughly 5200 deg^2 in the Southern Galactic Cap, bringing the total footprint of the SDSS imaging to 14,555 deg^2, or over a third of the Celestial Sphere. All the imaging data have been reprocessed with an improved sky-subtraction algorithm and a final, self-consistent photometric recalibration and flat-field determination. This release also includes all data from the second phase of the Sloan Extension for Galactic Understanding and Evolution (SEGUE-2), consisting of spectroscopy of approximately 118,000 stars at both high and low Galactic latitudes. All the more than half a million stellar spectra obtained with the SDSS spectrograph have been reprocessed through an improved stellar parameters pipeline, which has better determination of metallicity for high metallicity stars.Comment: Astrophysical Journal Supplements, in press (minor updates from submitted version