There is currently a lack of an efficient, objective and systemic approach towards the classification of Alzheimer’s disease (AD), due to its complex etiology and pathogenesis. As AD is inherently dynamic, it is also not clear how the relationships among AD indicators vary over time. To address these issues, we propose a hybrid computational approach for AD classification and evaluate it on the heterogeneous longitudinal AIBL dataset. Specifically, using clinical dementia rating as an index of AD severity, the most important indicators (mini-mental state examination, logical memory recall, grey matter and cerebrospinal volumes from MRI and active voxels from PiB-PET brain scans, ApoE, and age) can be automatically identified from parallel data mining algorithms. In this work, Bayesian network modelling across different time points is used to identify and visualize time-varying relationships among the significant features, and importantly, in an efficient way using only coarse-grained data. Crucially, our approach suggests key data features and their appropriate combinations that are relevant for AD severity classification with high accuracy. Overall, our study provides insights into AD developments and demonstrates the potential of our approach in supporting efficient AD diagnosis.

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BackgroundSuicidal behaviour is known to aggregate in families. Patients with psychiatric disorders are at higher risk for suicide attempts (SA), however protective and risk genetic variants for suicide appear to be independent of underlying psychiatric disorders. Here we investigate genetic variants in genes important for neurobiological pathways linked to suicidal behaviour and/or associated endophenotypes, for association with SA among patients with co-existing psychiatric illness. Selected gene-gene and gene-environment interactions were also tested.MethodsDNA was obtained from bloods of 159 patients (76 suicide attempters and 83 non-attempters), who were profiled for DSM-IV Axis I psychiatric diagnosis. Twenty-eight single nucleotide polymorphisms (SNPs) from 18 candidate genes (COMT, 5-HT2A, 5-HT1A, 5-HTR1B, TPH1, MAO-A, TPH2, DBH, CNR1, BDNF, ABCG1, GABRA5, GABRG2, GABRB2, SLC1A2, SLC1A3, NTRK2, CRHR1) were genotyped. Genotyping was performed by KBioscience. Tests of association between genetic variants and SA were conducted using Chi squared and Armitage Trend tests. Binary logistical regression analyses were performed to evaluate the contribution of individual genetic variants to the prediction of SA, and to examine SNPs for potential gene-gene and gene-environment interactions.ResultsOur analysis identified 4 SNPs (rs4755404, rs2269272, rs6296 and rs1659400), which showed evidence of association with SA compared to a non-attempter control group. We provide evidence of a 3-locus gene-gene interaction, and a putative gene-environment interaction, whereby genetic variation at the NTRK2 locus may moderate the risk associated with history of childhood abuse.ConclusionPreliminary findings suggest that allelic variability in SLC1A2/3, 5-HTR1B and NTRK2 may be relevant to the underlying diathesis for suicidal acts.

Recently, a significant epigenetic component in the pathology of suicide has been realized. Here we investigate candidate functional SNPs in epigenetic-regulatory genes, DNMT1 and DNMT3B, for association with suicide attempt (SA) among patients with co-existing psychiatric illness. In addition, global DNA methylation levels [5-methyl cytosine (5-mC%)] between SA and psychiatric controls were quantified using the Methylflash Methylated DNA Quantification Kit. DNA was obtained from blood of 79 suicide attempters and 80 non-attempters, assessed for DSM-IV Axis I disorders. Functional SNPs were selected for each gene (DNMT1; n = 7, DNMT3B; n = 10), and genotyped. A SNP (rs2424932) residing in the 3 UTR of the DNMT3B gene was associated with SA compared with a non-attempter control group (P = 0.001; Chi-squared test, Bonferroni adjusted P value = 0.02). Moreover, haplotype analysis identified a DNMT3B haplotype which differed between cases and controls, however this association did not hold after Bonferroni correction (P = 0.01, Bonferroni adjusted P value = 0.56). Global methylation analysis showed that psychiatric patients with a history of SA had significantly higher levels of global DNA methylation compared with controls (P = 0.018, Student's t-test). In conclusion, this is the first report investigating polymorphisms in DNMT genes and global DNA methylation quantification in SA risk. Preliminary findings suggest that allelic variability in DNMT3B may be relevant to the underlying diathesis for suicidal acts and our findings support the hypothesis that aberrant DNA methylation profiles may contribute to the biology of suicidal acts. Thus, analysis of global DNA hypermethylation in blood may represent a biomarker for increased SA risk in psychiatric patients.Keywords: DNA methylation, DNA methyltransferases, epigenetics, polymorphisms, psychiatry, suicide Suicide is a worldwide public health problem and a leading cause of death among young people in developed countries. Every year, almost one million people die from suicide globally with suicide attempts (SAs) up to 20 times more frequent than completed suicide (World Health Organization 2012). The risk for suicidal acts is multi-factorial, and consists of a range of biological, psychiatric, psychosocial, interpersonal and cultural risk factors.In addition to classical genetic abnormalities, an epigenetic component in the pathology of suicide has been realized. Epigenetics can be defined as the mechanisms that initiate and maintain heritable patterns of gene expression without altering the sequence of the genome (Holliday 1987). There are several layers of epigenetic complexity including histone modifications, chromatin remodelling and DNA methylation, the latter being the most thoroughly studied to date (Esteller 2006). DNA methylation refers to the addition of a methyl group to the carbon at position 5 of the cytosine ring, resulting in 5-methylcytosine (5-mC) (Razin & Riggs 1980) and is a key regulatory mechanism of the genome, playing a central role in diverse...

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