737 research outputs found

    Association of cerebrospinal fluid Aβ42 with A2M gene in cognitively normal subjects

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    Low cerebrospinal fluid (CSF) Aβ42 levels correlate with increased brain Aβ deposition in Alzheimer’s disease (AD), which suggests a disruption in the degradation and clearance of Aβ from the brain. In addition, APOE ε4 carriers have lower CSF Aβ42 levels than non-carriers. The hypothesis of this investigation was that CSF Aβ42 levels correlate with regulatory region variation in genes that are biologically associated with degradation or clearance of Aβ from the brain. CSF Aβ42 levels were tested for associations with Aβ degradation and clearance genes and APOE ε4. Twenty-four SNPs located within the 5′ and 3′ regions of 12 genes were analyzed. The study sample consisted of 99 AD patients and 168 cognitively normal control subjects. CSF Aβ42 levels were associated with APOE ε4 status in controls but not in AD patientsA2M regulatory region SNPs were also associated with CSF Aβ42 levels in controls, but not in AD patients, even after adjusting for APOE ε4. These results suggest that genetic variation within the A2M gene influences CSF Aβ42 levels

    Multimorbidity in bipolar disorder and under-treatment of cardiovascular disease: a cross sectional study

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    Background: Individuals with serious mental disorders experience poor physical health, especially increased rates of cardiometabolic morbidity and premature morbidity. Recent evidence suggests that individuals with schizophrenia have numerous comorbid physical conditions which may be under-recorded and under-treated but to date very few studies have explored this issue for bipolar disorder. Methods:We conducted a cross-sectional analysis of a dataset of 1,751,841 registered patients within 314 primary-care practices in Scotland, U.K. Bipolar disorder was identified using Read Codes recorded within electronic medical records. Data on 32 common chronic physical conditions were also assessed. Potential prescribing inequalities were evaluated by analyzing prescribing data for coronary heart disease (CHD) and hypertension. Results: Compared to controls, individuals with bipolar disorder were significantly less likely to have no recorded physical conditions (OR 0.59, 95% CI 0.54-0.63) and significantly more likely to have one physical condition (OR 1.27, 95% CI 1.16-1.39), two physical conditions (OR 1.45, 95% CI 1.30-1.62) and three or more physical conditions (OR 1.44, 95% CI 1.30-1.64). People with bipolar disorder also had higher rates of thyroid disorders, chronic kidney disease, chronic pain, chronic obstructive airways disease and diabetes but, surprisingly, lower recorded rates of hypertension and atrial fibrillation. People with bipolar disorder and comorbid CHD or hypertension were significantly more likely to be prescribed no antihypertensive or cholesterol-lowering medications compared to controls, and bipolar individuals with CHD or hypertension were significantly less likely to be on 2 or more antihypertensive agents. Conclusions: Individuals with bipolar disorder are similar to individuals with schizophrenia in having a wide range of comorbid and multiple physical health conditions. They are also less likely than controls to have a primary-care record of cardiovascular conditions such as hypertension and atrial fibrillation. Those with a recorded diagnosis of CHD or hypertension were less likely to be treated with cardiovascular medications and were treated less intensively. This study highlights the high physical healthcare needs of people with bipolar disorder, and provides evidence for a systematic under-recognition and under-treatment of cardiovascular disease in this group

    Hypomethylation of MB-COMT promoter is a major risk factor for schizophrenia and bipolar disorder

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    The variability in phenotypic presentations and the lack of consistency of genetic associations in mental illnesses remain a major challenge in molecular psychiatry. Recently, it has become increasingly clear that altered promoter DNA methylation could play a critical role in mediating differential regulation of genes and in facilitating short-term adaptation in response to the environment. Here, we report the investigation of the differential activity of membrane-bound catechol-O-methyltransferase (MB - COMT) due to altered promoter methylation and the nature of the contribution of COMT Val158Met polymorphism as risk factors for schizophrenia and bipolar disorder by analyzing 115 post-mortem brain samples from the frontal lobe. These studies are the first to reveal that the MB - COMT promoter DNA is frequently hypomethylated in schizophrenia and bipolar disorder patients, compared with the controls (methylation rate: 26 and 29 versus 60; P = 0.004 and 0.008, respectively), particularly in the left frontal lobes (methylation rate: 29 and 30 versus 81; P = 0.003 and 0.002, respectively). Quantitative gene-expression analyses showed a corresponding increase in transcript levels of MB - COMT in schizophrenia and bipolar disorder patients compared with the controls (P = 0.02) with an accompanying inverse correlation between MB - COMT and DRD1 expression. Furthermore, there was a tendency for the enrichment of the Val allele of the COMT Val158Met polymorphism with MB - COMT hypomethylation in the patients. These findings suggest that MB - COMT over-expression due to promoter hypomethylation and/or hyperactive allele of COMT may increase dopamine degradation in the frontal lobe providing a molecular basis for the shared symptoms of schizophrenia and bipolar disorder. © Copyright 2006 Oxford University Press

    Using an Uncertainty-Coding Matrix in Bayesian Regression Models for Haplotype-Specific Risk Detection in Family Association Studies

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    Haplotype association studies based on family genotype data can provide more biological information than single marker association studies. Difficulties arise, however, in the inference of haplotype phase determination and in haplotype transmission/non-transmission status. Incorporation of the uncertainty associated with haplotype inference into regression models requires special care. This task can get even more complicated when the genetic region contains a large number of haplotypes. To avoid the curse of dimensionality, we employ a clustering algorithm based on the evolutionary relationship among haplotypes and retain for regression analysis only the ancestral core haplotypes identified by it. To integrate the three sources of variation, phase ambiguity, transmission status and ancestral uncertainty, we propose an uncertainty-coding matrix which combines these three types of variability simultaneously. Next we evaluate haplotype risk with the use of such a matrix in a Bayesian conditional logistic regression model. Simulation studies and one application, a schizophrenia multiplex family study, are presented and the results are compared with those from other family based analysis tools such as FBAT. Our proposed method (Bayesian regression using uncertainty-coding matrix, BRUCM) is shown to perform better and the implementation in R is freely available

    Visualization of Genomic Changes by Segmented Smoothing Using an L0 Penalty

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    Copy number variations (CNV) and allelic imbalance in tumor tissue can show strong segmentation. Their graphical presentation can be enhanced by appropriate smoothing. Existing signal and scatterplot smoothers do not respect segmentation well. We present novel algorithms that use a penalty on the norm of differences of neighboring values. Visualization is our main goal, but we compare classification performance to that of VEGA

    The Effect of Algorithms on Copy Number Variant Detection

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    BACKGROUND: The detection of copy number variants (CNVs) and the results of CNV-disease association studies rely on how CNVs are defined, and because array-based technologies can only infer CNVs, CNV-calling algorithms can produce vastly different findings. Several authors have noted the large-scale variability between CNV-detection methods, as well as the substantial false positive and false negative rates associated with those methods. In this study, we use variations of four common algorithms for CNV detection (PennCNV, QuantiSNP, HMMSeg, and cnvPartition) and two definitions of overlap (any overlap and an overlap of at least 40% of the smaller CNV) to illustrate the effects of varying algorithms and definitions of overlap on CNV discovery. METHODOLOGY AND PRINCIPAL FINDINGS: We used a 56 K Illumina genotyping array enriched for CNV regions to generate hybridization intensities and allele frequencies for 48 Caucasian schizophrenia cases and 48 age-, ethnicity-, and gender-matched control subjects. No algorithm found a difference in CNV burden between the two groups. However, the total number of CNVs called ranged from 102 to 3,765 across algorithms. The mean CNV size ranged from 46 kb to 787 kb, and the average number of CNVs per subject ranged from 1 to 39. The number of novel CNVs not previously reported in normal subjects ranged from 0 to 212. CONCLUSIONS AND SIGNIFICANCE: Motivated by the availability of multiple publicly available genome-wide SNP arrays, investigators are conducting numerous analyses to identify putative additional CNVs in complex genetic disorders. However, the number of CNVs identified in array-based studies, and whether these CNVs are novel or valid, will depend on the algorithm(s) used. Thus, given the variety of methods used, there will be many false positives and false negatives. Both guidelines for the identification of CNVs inferred from high-density arrays and the establishment of a gold standard for validation of CNVs are needed

    Genome-wide association study identifies loci associated with liability to alcohol and drug dependence that is associated with variability in reward-related ventral striatum activity in African- and European-Americans.

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    Genetic influences on alcohol and drug dependence partially overlap, however, specific loci underlying this overlap remain unclear. We conducted a genome-wide association study (GWAS) of a phenotype representing alcohol or illicit drug dependence (ANYDEP) among 7291 European-Americans (EA; 2927 cases) and 3132 African-Americans (AA: 1315 cases) participating in the family-based Collaborative Study on the Genetics of Alcoholism. ANYDEP was heritable (h 2 in EA = 0.60, AA = 0.37). The AA GWAS identified three regions with genome-wide significant (GWS; P < 5E-08) single nucleotide polymorphisms (SNPs) on chromosomes 3 (rs34066662, rs58801820) and 13 (rs75168521, rs78886294), and an insertion-deletion on chromosome 5 (chr5:141988181). No polymorphisms reached GWS in the EA. One GWS region (chromosome 1: rs1890881) emerged from a trans-ancestral meta-analysis (EA + AA) of ANYDEP, and was attributable to alcohol dependence in both samples. Four genes (AA: CRKL, DZIP3, SBK3; EA: P2RX6) and four sets of genes were significantly enriched within biological pathways for hemostasis and signal transduction. GWS signals did not replicate in two independent samples but there was weak evidence for association between rs1890881 and alcohol intake in the UK Biobank. Among 118 AA and 481 EA individuals from the Duke Neurogenetics Study, rs75168521 and rs1890881 genotypes were associated with variability in reward-related ventral striatum activation. This study identified novel loci for substance dependence and provides preliminary evidence that these variants are also associated with individual differences in neural reward reactivity. Gene discovery efforts in non-European samples with distinct patterns of substance use may lead to the identification of novel ancestry-specific genetic markers of risk

    A Genome-Wide Linkage Scan for Distinct Subsets of Schizophrenia Characterized by Age at Onset and Neurocognitive Deficits

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    As schizophrenia is genetically and phenotypically heterogeneous, targeting genetically informative phenotypes may help identify greater linkage signals. The aim of the study is to evaluate the genetic linkage evidence for schizophrenia in subsets of families with earlier age at onset or greater neurocognitive deficits.Patients with schizophrenia (n  =  1,207) and their first-degree relatives (n  =  1,035) from 557 families with schizophrenia were recruited from six data collection field research centers throughout Taiwan. Subjects completed a face-to-face semi-structured interview, the Continuous Performance Test (CPT), the Wisconsin Card Sorting Test, and were genotyped with 386 microsatellite markers across the genome.A maximum nonparametric logarithm of odds (LOD) score of 4.17 at 2q22.1 was found in 295 families ranked by increasing age at onset, which had significant increases in the maximum LOD score compared with those obtained in initial linkage analyses using all available families. Based on this subset, a further subsetting by false alarm rate on the undegraded and degraded CPT obtained further increase in the nested subset-based LOD on 2q22.1, with a score of 7.36 in 228 families and 7.71 in 243 families, respectively.We found possible evidence of linkage on chromosome 2q22.1 in families of schizophrenia patients with more CPT false alarm rates nested within the families with younger age at onset. These results highlight the importance of incorporating genetically informative phenotypes in unraveling the complex genetics of schizophrenia
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