The Parkinson's progression markers initiative (PPMI) - establishing a PD biomarker cohort.

ObjectiveThe Parkinson's Progression Markers Initiative (PPMI) is an observational, international study designed to establish biomarker-defined cohorts and identify clinical, imaging, genetic, and biospecimen Parkinson's disease (PD) progression markers to accelerate disease-modifying therapeutic trials.MethodsA total of 423 untreated PD, 196 Healthy Control (HC) and 64 SWEDD (scans without evidence of dopaminergic deficit) subjects were enrolled at 24 sites. To enroll PD subjects as early as possible following diagnosis, subjects were eligible with only asymmetric bradykinesia or tremor plus a dopamine transporter (DAT) binding deficit on SPECT imaging. Acquisition of data was standardized as detailed at www.ppmi-info.org.ResultsApproximately 9% of enrolled subjects had a single PD sign at baseline. DAT imaging excluded 16% of potential PD subjects with SWEDD. The total MDS-UPDRS for PD was 32.4 compared to 4.6 for HC and 28.2 for SWEDD. On average, PD subjects demonstrated 45% and 68% reduction in mean striatal and contralateral putamen Specific Binding Ratios (SBR), respectively. Cerebrospinal fluid (CSF) was acquired from >97% of all subjects. CSF (PD/HC/SWEDD pg/mL) α-synuclein (1845/2204/2141) was reduced in PD vs HC or SWEDD (P < 0.03). Similarly, t-tau (45/53) and p-tau (16/18) were reduced in PD versus HC (P < 0.01).InterpretationPPMI has detailed the biomarker signature for an early PD cohort defined by clinical features and imaging biomarkers. This strategy provides the framework to establish biomarker cohorts and to define longitudinal progression biomarkers to support future PD treatment trials

Precompetitive data sharing as a catalyst to address unmet needs in Parkinson's disease

Parkinson's disease is a complex heterogeneous disorder with urgent need for disease-modifying therapies. Progress in successful therapeutic approaches for PD will require an unprecedented level of collaboration. At a workshop hosted by Parkinson's UK and co-organized by Critical Path Institute's (C-Path) Coalition Against Major Diseases (CAMD) Consortiums, investigators from industry, academia, government and regulatory agencies agreed on the need for sharing of data to enable future success. Government agencies included EMA, FDA, NINDS/NIH and IMI (Innovative Medicines Initiative). Emerging discoveries in new biomarkers and genetic endophenotypes are contributing to our understanding of the underlying pathophysiology of PD. In parallel there is growing recognition that early intervention will be key for successful treatments aimed at disease modification. At present, there is a lack of a comprehensive understanding of disease progression and the many factors that contribute to disease progression heterogeneity. Novel therapeutic targets and trial designs that incorporate existing and new biomarkers to evaluate drug effects independently and in combination are required. The integration of robust clinical data sets is viewed as a powerful approach to hasten medical discovery and therapies, as is being realized across diverse disease conditions employing big data analytics for healthcare. The application of lessons learned from parallel efforts is critical to identify barriers and enable a viable path forward. A roadmap is presented for a regulatory, academic, industry and advocacy driven integrated initiative that aims to facilitate and streamline new drug trials and registrations in Parkinson's disease

An anatomic gene expression atlas of the adult mouse brain

Studying gene expression provides a powerful means of understanding structure-function relationships in the nervous system. The availability of genome-scale in situ hybridization datasets enables new possibilities for understanding brain organization based on gene expression patterns. The Anatomic Gene Expression Atlas (AGEA) is a new relational atlas revealing the genetic architecture of the adult C57Bl/6J mouse brain based on spatial correlations across expression data for thousands of genes in the Allen Brain Atlas (ABA). The AGEA includes three discovery tools for examining neuroanatomical relationships and boundaries: (1) three-dimensional expression-based correlation maps, (2) a hierarchical transcriptome-based parcellation of the brain and (3) a facility to retrieve from the ABA specific genes showing enriched expression in local correlated domains. The utility of this atlas is illustrated by analysis of genetic organization in the thalamus, striatum and cerebral cortex. The AGEA is a publicly accessible online computational tool integrated with the ABA (http://mouse.brain-map.org/agea)

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Plasma Neurofilament Light for Prediction of Disease Progression in Familial Frontotemporal Lobar Degeneration

Objective: We tested the hypothesis that plasma neurofilament light chain (NfL) identifies asymptomatic carriers of familial frontotemporal lobar degeneration (FTLD)-causing mutations at risk of disease progression. Methods: Baseline plasma NfL concentrations were measured with single-molecule array in original (n = 277) and validation (n = 297) cohorts. C9orf72, GRN, and MAPT mutation carriers and noncarriers from the same families were classified by disease severity (asymptomatic, prodromal, and full phenotype) using the CDR Dementia Staging Instrument plus behavior and language domains from the National Alzheimer's Disease Coordinating Center FTLD module (CDR+NACC-FTLD). Linear mixed-effect models related NfL to clinical variables. Results: In both cohorts, baseline NfL was higher in asymptomatic mutation carriers who showed phenoconversion or disease progression compared to nonprogressors (original: 11.4 ± 7 pg/mL vs 6.7 ± 5 pg/mL, p = 0.002; validation: 14.1 ± 12 pg/mL vs 8.7 ± 6 pg/mL, p = 0.035). Plasma NfL discriminated symptomatic from asymptomatic mutation carriers or those with prodromal disease (original cutoff: 13.6 pg/mL, 87.5% sensitivity, 82.7% specificity; validation cutoff: 19.8 pg/mL, 87.4% sensitivity, 84.3% specificity). Higher baseline NfL correlated with worse longitudinal CDR+NACC-FTLD sum of boxes scores, neuropsychological function, and atrophy, regardless of genotype or disease severity, including asymptomatic mutation carriers. Conclusions: Plasma NfL identifies asymptomatic carriers of FTLD-causing mutations at short-term risk of disease progression and is a potential tool to select participants for prevention clinical trials. Trial registration information: ClinicalTrials.gov Identifier: NCT02372773 and NCT02365922. Classification of evidence: This study provides Class I evidence that in carriers of FTLD-causing mutations, elevation of plasma NfL predicts short-term risk of clinical progression

Circulating MicroRNAs as Clinical Biomarkers in the Predictions of Pregnancy Complications

Predicting pregnancy complications is a major topic for clinicians and biologists for maternal and fetal monitoring. Noninvasive biomarkers in maternal blood such as circulating microRNAs (miRNAs) are promising molecules to predict pregnancy disorders. miRNAs are noncoding short RNAs that regulate mRNA expression by repressing the translation or cleaving the transcript. miRNAs are released to the extracellular systemic circulation via exosomes. The discovery of plasma- or serum-derived miRNAs and of free-circulating exosomes that contain miRNAs provides useful information about the physiological or pathophysiological roles of the miRNAs. Specific placental miRNAs are present in maternal plasma in different ways depending on whether the pregnancy is normal or pathological or if there is no pregnancy. This paper focuses on placental miRNAs and extracellular miRNAs to the placenta whose misregulation could lead to pregnancy complications

Circulating MicroRNAs as Clinical Biomarkers in the Predictions of Pregnancy Complications

Predicting pregnancy complications is a major topic for clinicians and biologists for maternal and fetal monitoring. Noninvasive biomarkers in maternal blood such as circulating microRNAs (miRNAs) are promising molecules to predict pregnancy disorders. miRNAs are noncoding short RNAs that regulate mRNA expression by repressing the translation or cleaving the transcript. miRNAs are released to the extracellular systemic circulation via exosomes. The discovery of plasma-or serum-derived miRNAs and of free-circulating exosomes that contain miRNAs provides useful information about the physiological or pathophysiological roles of the miRNAs. Specific placental miRNAs are present in maternal plasma in different ways depending on whether the pregnancy is normal or pathological or if there is no pregnancy. This paper focuses on placental miRNAs and extracellular miRNAs to the placenta whose misregulation could lead to pregnancy complications

Non-invasive prenatal diagnosis of monogenic disorders: an optimized protocol using MEMO qPCR with miniSTR as internal control

International audienceBACKGROUND:Analysis of circulating cell-free fetal DNA (cffDNA) in maternal plasma is very promising for early diagnosis of monogenic diseases. However, this approach is not yet available for routine use and remains technically challenging because of the low concentration of cffDNA, which is swamped by the overwhelming maternal DNA.METHODS:To make clinical applications more readily accessible, we propose a new approach based on mutant enrichment with 3'-modified oligonucleotides (MEMO) PCR along with real-time PCR to selectively amplify from the maternal blood the paternally inherited fetal allele that is not present in the maternal genome.RESULTS:The first proof of concept of this strategy was displayed for cystic fibrosis by the accuracy of our detection of the p.Gly542* mutation used as the initial developmental model. Subsequently, a retrospective study of plasmas originating from two pregnant women carrying a fetus with private mutation confirmed the effectiveness of our method. We confirmed the presence of cffDNA in the studied samples by the identification of a tri-allelic DNA profile using a miniSTR kit.CONCLUSIONS:This new non-invasive prenatal diagnosis test offers numerous advantages over current methods: it is simple, cost effective, time efficient and does not require complex equipment or bioinformatics settings. Moreover, our assays for different private mutations demonstrate the viability of this approach in clinical settings for monogenic disorders