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1.  Niemann-Pick C Disease Gene Mutations and Age-Related Neurodegenerative Disorders 
PLoS ONE  2013;8(12):e82879.
Niemann-Pick type C (NPC) disease is a rare autosomal-recessively inherited lysosomal storage disorder caused by mutations in NPC1 (95%) or NPC2. Given the highly variable phenotype, diagnosis is challenging and particularly late-onset forms with predominantly neuropsychiatric presentations are likely underdiagnosed. Pathophysiologically, genetic alterations compromising the endosomal/lysosomal system are linked with age-related neurodegenerative disorders. We sought to examine a possible association of rare sequence variants in NPC1 and NPC2 with Parkinson's disease (PD), frontotemporal lobar degeneration (FTLD) and progressive supranuclear palsy (PSP), and to genetically determine the proportion of potentially misdiagnosed NPC patients in these neurodegenerative conditions. By means of high-resolution melting, we screened the coding regions of NPC1 and NPC2 for rare genetic variation in a homogenous German sample of patients clinically diagnosed with PD (n = 563), FTLD (n = 133) and PSP (n = 94), and 846 population-based controls. The frequencies of rare sequence variants in NPC1/2 did not differ significantly between patients and controls. Disease-associated NPC1/2 mutations were found in six PD patients (1.1%) and seven control subjects (0.8%), but not in FTLD or PSP. All rare variation was detected in the heterozygous state and no compound heterozygotes were observed. Our data do not support the hypothesis that rare NPC1/2 variants confer susceptibility for PD, FTLD, or PSP in the German population. Misdiagnosed NPC patients were not present in our samples. However, further assessment of NPC disease genes in age-related neurodegeneration is warranted.
PMCID: PMC3875432  PMID: 24386122
2.  Rare variants in LRRK1 and Parkinson's disease 
Neurogenetics  2013;15:49-57.
Approximately 20 % of individuals with Parkinson's disease (PD) report a positive family history. Yet, a large portion of causal and disease-modifying variants is still unknown. We used exome sequencing in two affected individuals from a family with late-onset PD to identify 15 potentially causal variants. Segregation analysis and frequency assessment in 862 PD cases and 1,014 ethnically matched controls highlighted variants in EEF1D and LRRK1 as the best candidates. Mutation screening of the coding regions of these genes in 862 cases and 1,014 controls revealed several novel non-synonymous variants in both genes in cases and controls. An in silico multi-model bioinformatics analysis was used to prioritize identified variants in LRRK1 for functional follow-up. However, protein expression, subcellular localization, and cell viability were not affected by the identified variants. Although it has yet to be proven conclusively that variants in LRRK1 are indeed causative of PD, our data strengthen a possible role for LRRK1 in addition to LRRK2 in the genetic underpinnings of PD but, at the same time, highlight the difficulties encountered in the study of rare variants identified by next-generation sequencing in diseases with autosomal dominant or complex patterns of inheritance.
Electronic supplementary material
The online version of this article (doi:10.1007/s10048-013-0383-8) contains supplementary material, which is available to authorized users.
PMCID: PMC3968516  PMID: 24241507
Parkinson's disease; LRRK1; EEF1D; Exome sequencing
3.  Rare Variants in PLXNA4 and Parkinson’s Disease 
PLoS ONE  2013;8(11):e79145.
Approximately 20% of individuals with Parkinson’s disease (PD) report a positive family history. Yet, a large portion of causal and disease-modifying variants is still unknown. We used exome sequencing in two affected individuals from a family with late-onset familial PD followed by frequency assessment in 975 PD cases and 1014 ethnically-matched controls and linkage analysis to identify potentially causal variants. Based on the predicted penetrance and the frequencies, a variant in PLXNA4 proved to be the best candidate and PLXNA4 was screened for additional variants in 862 PD cases and 940 controls, revealing an excess of rare non-synonymous coding variants in PLXNA4 in individuals with PD. Although we cannot conclude that the variant in PLXNA4 is indeed the causative variant, these findings are interesting in the light of a surfacing role of axonal guidance mechanisms in neurodegenerative disorders but, at the same time, highlight the difficulties encountered in the study of rare variants identified by next-generation sequencing in diseases with autosomal dominant or complex patterns of inheritance.
PMCID: PMC3823607  PMID: 24244438
4.  MicroRNAs in cerebrospinal fluid identify glioblastoma and metastatic brain cancers and reflect disease activity 
Neuro-Oncology  2012;14(6):689-700.
An accurate, nonsurgical diagnostic test for brain tumors is currently unavailable, and the methods of monitoring disease progression are not fully reliable. MicroRNA profiling of biological fluids has recently emerged as a diagnostic tool for several pathologic conditions. Here we tested whether microRNA profiling of cerebrospinal fluid (CSF) enables detection of glioblastoma, discrimination between glioblastoma and metastatic brain tumors, and reflects disease activity. We determined CSF levels of several cancer-associated microRNAs for 118 patients diagnosed with different types of brain cancers and nonneoplastic neuropathologies by quantitative reverse transcription PCR analysis. The levels of miR-10b and miR-21 are found significantly increased in the CSF of patients with glioblastoma and brain metastasis of breast and lung cancer, compared with tumors in remission and a variety of nonneoplastic conditions. Members of the miR-200 family are highly elevated in the CSF of patients with brain metastases but not with any other pathologic conditions, allowing discrimination between glioblastoma and metastatic brain tumors. Quantification of as few as 7 microRNAs in CSF enables differential recognition of glioblastoma and metastatic brain cancer using computational machine learning tools (Support Vector Machine) with high accuracy (91%–99%) on a test set of samples. Furthermore, we show that disease activity and treatment response can be monitored by longitudinal microRNA profiles in the CSF of glioblastoma and non–small cell lung carcinoma patients. This study demonstrates that microRNA-based detection of brain malignancies can be reliably performed and that microRNAs in CSF can serve as biomarkers of treatment response in brain cancers.
PMCID: PMC3367845  PMID: 22492962
biomarkers; brain metastasis; cerebrospinal fluid; glioblastoma; leptomeningeal metastasis; microRNA
5.  Biochemical Pre-motor Biomarkers for Parkinson Disease 
A biomarker is a biological characteristic that is objectively measured and evaluated as an indicator of normal biological or pathologic processes or of pharmacologic responses to a therapeutic intervention. We review the current status on target protein biomarkers (e.g. total/oligomeric α-synuclein and DJ-1) in cerebrospinal fluid, as well as on unbiased processes that can be used to discover novel biomarkers. We also give details about strategies towards potential populations/models and technologies, including the need for standardized sampling techniques, to pursue the identification of new biochemical markers in the pre-motor stage of Parkinson disease in the future.
PMCID: PMC3428741  PMID: 22508282
Biomarkers; genomics; metabolomics; Parkinson disease; pre-motor; proteomics
6.  α-Synuclein in human cerebrospinal fluid is principally derived from neurons of the central nervous system 
Journal of Neural Transmission  2012;119(7):739-746.
The source of Parkinson disease-linked α-synuclein (aSyn) in human cerebrospinal fluid (CSF) remains unknown. We decided to measure the concentration of aSyn and its gradient in human CSF specimens and compared it with serum to explore its origin. We correlated aSyn concentrations in CSF versus serum (QaSyn) to the albumin quotient (Qalbumin) to evaluate its relation to blood–CSF barrier function. We also compared aSyn with several other CSF constituents of either central or peripheral sources (or both) including albumin, neuron-specific enolase, β-trace protein and total protein content. Finally, we examined whether aSyn is present within the structures of the choroid plexus (CP). We observed that QaSyn did not rise or fall with Qalbumin values, a relative measure of blood–CSF barrier integrity. In our CSF gradient analyses, aSyn levels decreased slightly from rostral to caudal fractions, in parallel to the recorded changes for neuron-specific enolase; the opposite trend was recorded for total protein, albumin and β-trace protein. The latter showed higher concentrations in caudal CSF fractions due to the diffusion-mediated transfer of proteins from blood and leptomeninges into CSF in the lower regions of the spine. In postmortem sections of human brain, we detected highly variable aSyn reactivity within the epithelial cell layer of CP in patients diagnosed with a range of neurological diseases; however, in sections of mice that express only human SNCA alleles (and in those without any Snca gene expression), we detected no aSyn signal in the epithelial cells of the CP. We conclude from these complementary results that despite its higher levels in peripheral blood products, neurons of the brain and spinal cord represent the principal source of aSyn in human CSF.
PMCID: PMC3378837  PMID: 22426833
α-Synuclein; Cerebrospinal fluid; Blood–CSF barrier; Biomarker; Choroid plexus
7.  Combined Analysis of CSF Tau, Aβ42, Aβ1–42% and Aβ1–40ox% in Alzheimer's Disease, Dementia with Lewy Bodies and Parkinson's Disease Dementia 
We studied the diagnostic value of CSF Aβ42/tau versus low Aβ1–42% and high Aβ1–40ox% levels for differential diagnosis of Alzheimer's disease (AD) and dementia with Lewy bodies (DLB), respectively. CSF of 45 patients with AD, 15 with DLB, 21 with Parkinson's disease dementia (PDD), and 40 nondemented disease controls (NDC) was analyzed by Aβ-SDS-PAGE/immunoblot and ELISAs (Aβ42 and tau). Aβ42/tau lacked specificity in discriminating AD from DLB and PDD. Best discriminating biomarkers were Aβ1–42% and Aβ1–40ox% for AD and DLB, respectively. AD and DLB could be differentiated by both Aβ1–42% and Aβ1–40ox% with an accuracy of 80% at minimum. Thus, we consider Aβ1–42% and Aβ1–40ox% to be useful biomarkers for AD and DLB, respectively. We propose further studies on the integration of Aβ1–42% and Aβ1–40ox% into conventional assay formats. Moreover, future studies should investigate the combination of Aβ1–40ox% and CSF alpha-synuclein for the diagnosis of DLB.
PMCID: PMC2938459  PMID: 20862375

Results 1-7 (7)