Comparative analysis of germline and somatic micro-lesion mutational spectra in 17 human tumour suppressor genes

The known somatic (N>4000) and germline (N>4000) cancer-associated mutational spectra (viz. missense and nonsense mutations micro-deletions, micro-insertions and micro- indels <20bp) of 17 human tumour suppressor genes (viz. APC, ATM, BRCA1, BRCA2, CDH1, CDKN2A, NF1, NF2, PTCH, PTEN, RBI, STK11, TP53, TSC1, TSC2, VHL and WT1) were compared in order to identify similarities and differences. Analysed parameters included the recurrence status of mutations, CpG mutability Grantham difference evolutionary conservation of affected codons role of nonsense-mediated mRNA decay and co-location with repetitive sequence elements. Only a small proportion of the mutations (-5%) were found to be shared between the germline and soma, although the proportions varied between different types of mutation (from 11% for missense mutations to 1% for micro-indels). Shared mutations are unlikely to be coincidental and are probably indicative of underlying shared (and endogenous) mutational mechanisms. Shared missense mutations were found to be more likely to be drivers of tumorigenesis than either exclusively somatic or exclusively germline missense mutations. Shared micro-lesions combined for all genes occurred disproportionately within repetitive elements by comparison with both somatic or germline micro-lesions, consistent with an endogenous mutational mechanism. For some genes (e.g. TP53), shared CpG-dinucleotide mutations evidenced the action of an endogenous mutational mechanism (viz. methylation-mediated deamination of 5-methylcytosine) in both the soma and the germline. Differences between mutational spectra were also noted. Germline missense mutations were found to be more likely to bear relatively more drastic functional consequences by comparison with somatic missense mutations, but also more likely to be truncating mutations. Germline micro-lesions (combined for all genes) were also found to be more likely to be co-located with repetitive elements than somatic micro-lesions. This could be due to the germline being relatively more protected from the action of exogenous mutagens by comparison to the soma. This study of 17 human tumour suppressor genes has therefore provided a first glimpse of the similarities and differences between germline and somatic mutational spectra

Comparative analysis of germline and somatic micro-lesion mutational spectra in 17 human tumour suppressor genes

The known somatic (N>4000) and germline (N>4000) cancer-associated mutational spectra (viz. missense and nonsense mutations micro-deletions, micro-insertions and micro- indels <20bp) of 17 human tumour suppressor genes (viz. APC, ATM, BRCA1, BRCA2, CDH1, CDKN2A, NF1, NF2, PTCH, PTEN, RBI, STK11, TP53, TSC1, TSC2, VHL and WT1) were compared in order to identify similarities and differences. Analysed parameters included the recurrence status of mutations, CpG mutability Grantham difference evolutionary conservation of affected codons role of nonsense-mediated mRNA decay and co-location with repetitive sequence elements. Only a small proportion of the mutations (-5%) were found to be shared between the germline and soma, although the proportions varied between different types of mutation (from 11% for missense mutations to 1% for micro-indels). Shared mutations are unlikely to be coincidental and are probably indicative of underlying shared (and endogenous) mutational mechanisms. Shared missense mutations were found to be more likely to be drivers of tumorigenesis than either exclusively somatic or exclusively germline missense mutations. Shared micro-lesions combined for all genes occurred disproportionately within repetitive elements by comparison with both somatic or germline micro-lesions, consistent with an endogenous mutational mechanism. For some genes (e.g. TP53), shared CpG-dinucleotide mutations evidenced the action of an endogenous mutational mechanism (viz. methylation-mediated deamination of 5-methylcytosine) in both the soma and the germline. Differences between mutational spectra were also noted. Germline missense mutations were found to be more likely to bear relatively more drastic functional consequences by comparison with somatic missense mutations, but also more likely to be truncating mutations. Germline micro-lesions (combined for all genes) were also found to be more likely to be co-located with repetitive elements than somatic micro-lesions. This could be due to the germline being relatively more protected from the action of exogenous mutagens by comparison to the soma. This study of 17 human tumour suppressor genes has therefore provided a first glimpse of the similarities and differences between germline and somatic mutational spectra.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

A novel computational approach for predicting complex phenotypes in Drosophila (starvation-sensitive and sterile) by deriving their gene expression signatures from public data

Many research teams perform numerous genetic, transcriptomic, proteomic and other types of omic experiments to understand molecular, cellular and physiological mechanisms of disease and health. Often (but not always), the results of these experiments are deposited in publicly available repository databases. These data records often include phenotypic characteristics following genetic and environmental perturbations, with the aim of discovering underlying molecular mechanisms leading to the phenotypic responses. A constrained set of phenotypic characteristics is usually recorded and these are mostly hypothesis driven of possible to record within financial or practical constraints. We present a novel proof-of-principal computational approach for combining publicly available gene-expression data from control/mutant animal experiments that exhibit a particular phenotype, and we use this approach to predict unobserved phenotypic characteristics in new experiments (data derived from EBI’s ArrayExpress and ExpressionAtlas respectively). We utilised available microarray gene-expression data for two phenotypes (starvation-sensitive and sterile) in Drosophila. The data were combined using a linear-mixed effects model with the inclusion of consecutive principal components to account for variability between experiments in conjunction with Gene Ontology enrichment analysis. We present how available data can be ranked in accordance to a phenotypic likelihood of exhibiting these two phenotypes using random forest. The results from our study show that it is possible to integrate seemingly different gene-expression microarray data and predict a potential phenotypic manifestation with a relatively high degree of confidence (>80% AUC). This provides thus far unexplored opportunities for inferring unknown and unbiased phenotypic characteristics from already performed experiments, in order to identify studies for future analyses. Molecular mechanisms associated with gene and environment perturbations are intrinsically linked and give rise to a variety of phenotypic manifestations. Therefore, unravelling the phenotypic spectrum can help to gain insights into disease mechanisms associated with gene and environmental perturbations. Our approach uses public data that are set to increase in volume, thus providing value for money

Machine learning for the life-time risk prediction of Alzheimer’s disease: a systematic review

Alzheimer’s disease is a neurodegenerative disorder and the most common form of dementia. Early diagnosis may assist interventions to delay onset and reduce the progression rate of the disease. We systematically reviewed the use of machine learning algorithms for predicting Alzheimer’s disease using single nucleotide polymorphisms and instances where these were combined with other types of data. We evaluated the ability of machine learning models to distinguish between controls and cases, while also assessing their implementation and potential biases. Articles published between December 2009 and June 2020 were collected using Scopus, PubMed and Google Scholar. These were systematically screened for inclusion leading to a final set of 12 publications. Eighty-five per cent of the included studies used the Alzheimer's Disease Neuroimaging Initiative dataset. In studies which reported area under the curve, discrimination varied (0.49–0.97). However, more than half of the included manuscripts used other forms of measurement, such as accuracy, sensitivity and specificity. Model calibration statistics were also found to be reported inconsistently across all studies. The most frequent limitation in the assessed studies was sample size, with the total number of participants often numbering less than a thousand, whilst the number of predictors usually ran into the many thousands. In addition, key steps in model implementation and validation were often not performed or unreported, making it difficult to assess the capability of machine learning models

Restoring synapse integrity and memory in Alzheimer’s disease by downregulation of the Wnt antagonist Dickkopf-3

Increasing evidence supports a role of deficient Wnt signaling in Alzheimer’s disease (AD). Recent studies reveal that the secreted Wnt antagonist Dickkopf-3 (DKK3) is elevated in the human AD brain. Here, we investigate the contribution of DKK3 to synapse integrity in the healthy and AD brain. We uncover a novel genetic link between DKK3 gene variants and AD risk. Our findings show that DKK3 protein is increased in different human brain fractions consistent with disease progression. In the hAPP-J20 and hAPPNL-G-F/NL-G-F AD models, DKK3 accumulates at plaques in the brain. Oligomers of amyloid-β enhance the secretion of DKK3 from cultured neurons and DKK3 secretion is also increased in hippocampal slices of hAPP-J20 mice. In addition, gain-of-function experiments revealed that DKK3 decreases the density of excitatory synapses through inhibition of the canonical Wnt/GSK3β pathway but increases inhibitory synapse density through activation of the Wnt/JNK pathway. Our studies demonstrate that in vivo DKK3 downregulation restores synapse number in hAPP-J20 mice. Importantly, DKK3 knockdown improves memory in this AD model. Collectively, our findings identify DKK3 as a novel driver of synapse defects and memory impairment in AD

Cognitive decline in Alzheimer’s disease is not associated with APOE

Background:The rate of cognitive decline in Alzheimer’s disease (AD) has been found to vary widely between individuals, with numerous factors driving this heterogeneity. Objective:This study aimed to compute a measure of cognitive decline in patients with AD based on clinical information and to utilize this measure to explore the genetic architecture of cognitive decline in AD. Methods:An in-house cohort of 616 individuals, hereby termed the Cardiff Genetic Resource for AD, as well as a subset of 577 individuals from the publicly available ADNI dataset, that have been assessed at multiple timepoints, were used in this study. Measures of cognitive decline were computed using various mixed effect linear models of Mini-Mental State Examination (MMSE). After an optimal model was selected, a metric of cognitive decline for each individual was estimated as the random slope derived from this model. This metric was subsequently used for testing the association of cognitive decline with apolipoprotein E (APOE) genotype. Results:No association was found between the number of APOE ɛ2 or ɛ4 alleles and the rate of cognitive decline in either of the datasets examined. Conclusion:Further exploration is required to uncover possible genetic variants that affect the rate of decline in patients with AD

Golgi apparatus, endoplasmic reticulum and mitochondrial function implicated in Alzheimer's disease through polygenic risk and RNA sequencing

Polygenic risk scores (PRS) have been widely adopted as a tool for measuring common variant liability and they have been shown to predict lifetime risk of Alzheimer’s disease (AD) development. However, the relationship between PRS and AD pathogenesis is largely unknown. To this end, we performed a differential gene-expression and associated disrupted biological pathway analyses of AD PRS vs. case/controls in human brain-derived cohort sample (cerebellum/temporal cortex; MayoRNAseq). The results highlighted already implicated mechanisms: immune and stress response, lipids, fatty acids and cholesterol metabolisms, endosome and cellular/neuronal death, being disrupted biological pathways in both case/controls and PRS, as well as previously less well characterised processes such as cellular structures, mitochondrial respiration and secretion. Despite heterogeneity in terms of differentially expressed genes in case/controls vs. PRS, there was a consensus of commonly disrupted biological mechanisms. Glia and microglia-related terms were also significantly disrupted, albeit not being the top disrupted Gene Ontology terms. GWAS implicated genes were significantly and in their majority, up-regulated in response to different PRS among the temporal cortex samples, suggesting potential common regulatory mechanisms. Tissue specificity in terms of disrupted biological pathways in temporal cortex vs. cerebellum was observed in relation to PRS, but limited tissue specificity when the datasets were analysed as case/controls. The largely common biological mechanisms between a case/control classification and in association with PRS suggests that PRS stratification can be used for studies where suitable case/control samples are not available or the selection of individuals with high and low PRS in clinical trials

Cell type-specific modulation of healthspan by Forkhead family transcription factors in the nervous system

Reduced activity of insulin/insulin-like growth factor signaling (IIS) increases healthy lifespan among diverse animal species. Downstream of IIS, multiple evolutionarily conserved transcription factors (TFs) are required; however, distinct TFs are likely responsible for these effects in different tissues. Here we have asked which TFs can extend healthy lifespan within distinct cell types of the adult nervous system in Drosophila. Starting from published single-cell transcriptomic data, we report that forkhead (FKH) is endogenously expressed in neurons, whereas forkhead-box-O (FOXO) is expressed in glial cells. Accordingly, we find that neuronal FKH and glial FOXO exert independent prolongevity effects. We have further explored the role of neuronal FKH in a model of Alzheimer’s disease-associated neuronal dysfunction, where we find that increased neuronal FKH preserves behavioral function and reduces ubiquitinated protein aggregation. Finally, using transcriptomic profiling, we identify Atg17, a member of the Atg1 autophagy initiation family, as one FKH-dependent target whose neuronal overexpression is sufficient to extend healthy lifespan. Taken together, our results underscore the importance of cell type-specific mapping of TF activity to preserve healthy function with age

Rare copy number variants: a point of rarity in genetic risk for bipolar disorder and schizophrenia

Context: Recent studies suggest that copy number variation in the human genome is extensive and may play an important role in susceptibility to disease, including neuropsychiatric disorders such as schizophrenia and autism. The possible involvement of copy number variants (CNVs) in bipolar disorder has received little attention to date. Objectives: To determine whether large (>100 000 base pairs) and rare (found in <1% of the population) CNVs are associated with susceptibility to bipolar disorder and to compare with findings in schizophrenia. Design: A genome-wide survey of large, rare CNVs in a case-control sample using a high-density microarray. Setting: The Wellcome Trust Case Control Consortium. Participants: There were 1697 cases of bipolar disorder and 2806 nonpsychiatric controls. All participants were white UK residents. Main Outcome Measures: Overall load of CNVs and presence of rare CNVs. Results: The burden of CNVs in bipolar disorder was not increased compared with controls and was significantly less than in schizophrenia cases. The CNVs previously implicated in the etiology of schizophrenia were not more common in cases with bipolar disorder. Conclusions: Schizophrenia and bipolar disorder differ with respect to CNV burden in general and association with specific CNVs in particular. Our data are consistent with the possibility that possession of large, rare deletions may modify the phenotype in those at risk of psychosis: those possessing such events are more likely to be diagnosed as having schizophrenia, and those without them are more likely to be diagnosed as having bipolar disorder

No evidence for association between polymorphisms in GRM3 and schizophrenia

BACKGROUND: Three studies have previously reported data that were interpreted by the authors as supportive of association between schizophrenia and polymorphisms in the gene encoding the metabotropic glutamate receptor GRM3. METHODS: In a bid to examine this hypothesis, we examined seven SNPs spanning GRM3 in a UK case-control sample (schizophrenic cases n = 674, controls n = 716). These included all SNPs previously reported to be associated, alone or in haplotypes, with schizophrenia in European or European American samples. RESULTS: Our data showed no evidence for association with single markers, or 2, 3, 4 and 5 marker haplotypes, nor did any specific haplotypes show evidence for association according to previously observed patterns. CONCLUSION: Examination of our own data and those of other groups leads us to conclude that at present, GRM3 should not be viewed as a gene for which there is replicated evidence for association with schizophrenia