1Parkinsonism Relat. Disord. 2008 Aug 14: 465-70
TitleAutosomal dominant dopa-responsive parkinsonism in a multigenerational Swiss family.
AbstractTo describe a large family with autosomal dominant parkinsonism.
Seven genes are directly implicated in autosomally inherited parkinsonism. However, there are several multigenerational large families known with no identifiable mutation.
Family members were evaluated clinically, by history and chart review. Genetic investigation included SCA2, SCA3, UCHL1, SNCA, LRRK2, PINK1, PRKN, PGRN, FMR1 premutation, and MAPT. The proband underwent brain fluorodopa PET (FD-PET) scan, and one autopsy was available.
Eleven patients had a diagnosis of Parkinson's disease (PD), nine women. Mean age of onset was 52 with tremor-predominant dopa-responsive parkinsonism. Disease progression was slow but severe motor fluctuations occurred. One patient required subthalamic nucleus deep-brain stimulation with a good motor outcome. One patient had mental retardation, schizophrenia and became demented, and another patient was demented. Three patients and also two unaffected subjects had mild learning difficulties. All genetic tests yielded negative results. FD-PET showed marked asymmetric striatal tracer uptake deficiency, consistent with PD. Pathological examination demonstrated no Lewy bodies and immunostaining was negative for alpha-synuclein.
Apart from a younger age of onset and a female predominance, the phenotype was indistinguishable from sporadic tremor-predominant PD, including FD-PET scan results. As known genetic causes of autosomal dominant PD were excluded, this family harbors a novel genetic defect.
SCZ Keywordsschizophrenia
2Rinsho Shinkeigaku 2011 Nov 51: 928-9
Title["Atypical" method for understanding dementia. How can studying epigenetics contribute?].
AbstractThe pathological hallmark of neurodegeneration is presence of intra- and extra neuronal inclusion bodies such as Lewy bodies in Parkinson's disease, senile plaques and neurofibrillary tangles in Alzheimer's disease. These are consisted of aggregated conformationally abnormal proteins. The precise mechanism of aggregation remains unknown, but increased expression of aggregation-prone proteins can lead to their aggregation. For example, in Down syndrome, duplication of the 21(st) chromosome, which contains the amyloid beta precursor protein (APP) gene, leads to accumulation of amyloid beta and Alzheimer's disease pathology and multiplication of APP gene is shown to be the cause of familial Alzheimer's disease. Moreover, in rare cases of PD, duplication or triplication of SNCA gene leads to alpha-synuclein accumulation, with triplication producing a more severe phenotype than duplication, suggesting that SNCA expression level determines the severity of the pathology. Lastly, animal models of neurodegenerative disorders are generated by over-expression of causal genes, further supporting the conclusion that increased gene expression is related to pathogenesis. Additional evidence indicates that SNCA promoter polymorphisms increases alpha-synuclein expression and increases susceptibility to sporadic PD. In addition to promoter polymorphisms, epigenetic modification can alter downstream gene expression. Epigenetic regulation includes histone modification and DNA methylation, of which CpG island methylation can be gene-specific; in several different cancers, CpG methylation inhibits binding of the transcription machinery, causing silencing of a specific oncogene, which leads to carcinogenesis. In central nervous system disorders, CpG methylation has been associated with psychiatric disorders, such as autism and schizophrenia. We found several cases of Parkinson's disease with epigenetic abnormality in SNCA gene. Thus, we believe that studying epigenetics can provide previously unknown causes for dementia and other neurodegenerative disorders.
SCZ Keywordsschizophrenia
3Transl Psychiatry 2014 -1 4: e391
TitleGenetic risk prediction and neurobiological understanding of alcoholism.
AbstractWe have used a translational Convergent Functional Genomics (CFG) approach to discover genes involved in alcoholism, by gene-level integration of genome-wide association study (GWAS) data from a German alcohol dependence cohort with other genetic and gene expression data, from human and animal model studies, similar to our previous work in bipolar disorder and schizophrenia. A panel of all the nominally significant P-value SNPs in the top candidate genes discovered by CFG  (n=135 genes, 713 SNPs) was used to generate a genetic  risk prediction score (GRPS), which showed a trend towards significance (P=0.053) in separating  alcohol dependent individuals from controls in an independent German test cohort. We then validated and prioritized our top findings from this discovery work, and subsequently tested them in three independent cohorts, from two continents. A panel of all the nominally significant P-value single-nucleotide length polymorphisms (SNPs) in the top candidate genes discovered by CFG (n=135 genes, 713 SNPs) were used to generate a Genetic Risk Prediction Score (GRPS), which showed a trend towards significance (P=0.053) in separating alcohol-dependent individuals from controls in an independent German test cohort. In order to validate and prioritize the key genes that drive behavior without some of the pleiotropic environmental confounds present in humans, we used a stress-reactive animal model of alcoholism developed by our group, the D-box binding protein (DBP) knockout mouse, consistent with the surfeit of stress theory of addiction proposed by Koob and colleagues. A much smaller panel (n=11 genes, 66 SNPs) of the top CFG-discovered genes for alcoholism, cross-validated and prioritized by this stress-reactive animal model showed better predictive ability in the independent German test cohort (P=0.041). The top CFG scoring gene for alcoholism from the initial discovery step, synuclein alpha (SNCA) remained the top gene after the stress-reactive animal model cross-validation. We also tested this small panel of genes in two other independent test cohorts from the United States, one with alcohol dependence (P=0.00012) and one with alcohol abuse (a less severe form of alcoholism; P=0.0094). SNCA by itself was able to separate alcoholics from controls in the alcohol-dependent cohort (P=0.000013) and the alcohol abuse cohort (P=0.023). So did eight other genes from the panel of 11 genes taken individually, albeit to a lesser extent and/or less broadly across cohorts. SNCA, GRM3 and MBP survived strict Bonferroni correction for multiple comparisons. Taken together, these results suggest that our stress-reactive DBP animal model helped to validate and prioritize from the CFG-discovered genes some of the key behaviorally relevant genes for alcoholism. These genes fall into a series of biological pathways involved in signal transduction, transmission of nerve impulse (including myelination) and cocaine addiction. Overall, our work provides leads towards a better understanding of illness, diagnostics and therapeutics, including treatment with omega-3 fatty acids. We also examined the overlap between the top candidate genes for alcoholism from this work and the top candidate genes for bipolar disorder, schizophrenia, anxiety from previous CFG analyses conducted by us, as well as cross-tested genetic risk predictions. This revealed the significant genetic overlap with other major psychiatric disorder domains, providing a basis for comorbidity and dual diagnosis, and placing alcohol use in the broader context of modulating the mental landscape.
SCZ Keywordsschizophrenia
4Parkinsonism Relat. Disord. 2016 Apr 25: 108-9
TitleSchizophrenia as a prodromal symptom in a patient harboring SNCA duplication.
AbstractWe present the case of a patient who developed delusions and auditory hallucinations and was clinically diagnosed as having schizophrenia. Ten years after the onset of schizophrenia, the disease progressed to mild parkinsonism. SNCA duplication was confirmed. This case expands the spectrum of clinical features in carriers of SNCA duplication.
SCZ Keywordsschizophrenia
5BMC Psychiatry 2016 -1 16: 154
TitleValidating reference genes using minimally transformed qpcr data: findings in human cortex and outcomes in schizophrenia.
AbstractIt is common practice, when using quantitative real time polymerase chain reaction (qPCR), to normalise levels of mRNA to reference gene mRNA which, by definition, should not vary between tissue, with any disease aetiology or after drug treatments. The complexity of human CNS means it unlikely that any gene could fulfil these criteria.
To address this issue we measured levels of mRNA for six potential reference genes (GAPDH, PPIA, SNCA, NOL9, TFB1M and SKP1) in three cortical regions (Brodmann's areas (BA) 8, 9 and 44) from 30 subjects with schizophrenia and 30 age and sex matched controls. We used a structured statistical approach to examine the characteristics of these data to determine their suitability as reference genes. We also analysed our data using reference genes selected by rank as defined using the average of the standard deviation of pair-gene ?Ct and the BestKeeper, NormFinder and geNorm algorithms to determine if they suggested the same reference genes.
Our minimally derived data showed that levels of mRNA for all of the six genes varied between cortical regions and therefore no gene fulfilled the absolute requirements for use as reference genes. As levels of some mRNA for some genes did not vary with diagnoses within a cortical region from subjects with schizophrenia compared to controls, we normalised levels of mRNA for all the other genes to mRNA for one, two or three reference genes in each cortical region. This showed that using the geometric mean of at least two reference genes gave more reproducible results. Finally, using the reference gene ranking protocols the average of the standard deviation of pair-gene ?Ct, BestKeeper, NormFinder and geNorm we showed that these approaches ranked potential reference genes differently. We then showed that outcomes of comparing data from subjects with schizophrenia and controls varied depending on the reference genes chosen.
Our data shows that the selection of reference genes is a significant component of qPCR study design and therefore the process by which reference genes are selected must be clearly listed as a potential confound in studying gene expression in human CNS. This should include showing that, using minimally derived qPCR data, levels of mRNA for proposed reference genes does not vary with variables such as diagnoses and CNS region.
SCZ Keywordsschizophrenia