Identifying polymorphisms in the Alzheimer's related APP gene using the MinION sequencer

The MinION is a bench top sequencer by Oxford nanopore technologies (ONT) that allows long reads of DNA sequence. Few studies have tested whether polymorphisms can be detected using this device. Several polymorphisms within the APP gene were used to test this capability. Library preparation and sequencing were performed using standard ONT protocols for samples harbouring ive different mutations. Alignments to the reference sequence were analysed in MinoTour and basecalls were manually investigated using proportion of reference calls between samples to identify the variants. MinoTour’s algorithm for variant detection was unable to identify the polymorphisms due to high base calling error rate. By calculating the difference in reference basecall proportions along the amplicon, it was possible to identify the polymorphisms above a Bonferroni-corrected threshold (p<1 × 10-4). The MinION has potential for polymorphism detection when comparing samples; however careful interpretation is needed as high base calling error rates can mask the presence of polymorphisms

Dementia with Lewy Bodies: Genomics, Transcriptomics, and Its Future with Data Science

Dementia with Lewy bodies (DLB) is a significant public health issue. It is the second most common neurodegenerative dementia and presents with severe neuropsychiatric symptoms. Genomic and transcriptomic analyses have provided some insight into disease pathology. Variants within SNCA, GBA, APOE, SNCB, and MAPT have been shown to be associated with DLB in repeated genomic studies. Transcriptomic analysis, conducted predominantly on candidate genes, has identified signatures of synuclein aggregation, protein degradation, amyloid deposition, neuroinflammation, mitochondrial dysfunction, and the upregulation of heat-shock proteins in DLB. Yet, the understanding of DLB molecular pathology is incomplete. This precipitates the current clinical position whereby there are no available disease-modifying treatments or blood-based diagnostic biomarkers. Data science methods have the potential to improve disease understanding, optimising therapeutic intervention and drug development, to reduce disease burden. Genomic prediction will facilitate the early identification of cases and the timely application of future disease-modifying treatments. Transcript-level analyses across the entire transcriptome and machine learning analysis of multi-omic data will uncover novel signatures that may provide clues to DLB pathology and improve drug development. This review will discuss the current genomic and transcriptomic understanding of DLB, highlight gaps in the literature, and describe data science methods that may advance the field

Psychological stress, cognitive decline and the development of dementia in amnestic mild cognitive impairment

To determine the relationship between psychological stress with cognitive outcomes in a multi-centre longitudinal study of people with amnestic mild cognitive impairment (aMCI) we assessed three parameters of psychological stress (Recent Life Changes Questionnaire (RLCQ); the Perceived Stress Scale (PSS) and salivary cortisol) and their relationship with rates of cognitive decline over an 18 month follow up period and conversion to dementia over a 5.5 year period. In 133 aMCI and 68 cognitively intact participants the PSS score was higher in the aMCI compared with control group but neither the RLCQ scores nor salivary cortisol measures were different between groups. In the aMCI group the RLCQ and the PSS showed no significant association with cognitive function at baseline, cognitive decline or with conversion rates to dementia but high salivary cortisol levels were associated with RLCQ scores and poorer cognitive function at baseline and lower rates of cognitive decline. No relationship was found between salivary cortisol levels and conversion rate to dementia. We conclude that psychological stress as measured by the RLCQ or PSS was not associated with adverse cognitive outcomes in an aMCI population and hypothesise that this may reflect diminished cortisol production to psychological stress as the disease progresses.</p

Confirmation that a specific haplotype of the dopamine transporter gene is associated with Combined-Type ADHD

Objective: The primary purpose of this study was to confirm the association of a specific haplotype of the dopamine transporter gene and attention deficit hyperactivity disorder (ADHD), which could be one source of the heterogeneity seen across published studies. Method: The authors previously reported the association of ADHD with a subgroup of chromosomes containing specific alleles of two variable-number tandem repeat polymorphisms within the 3' untranslated region and intron 8 of the dopamine transporter gene. They now report on this association in a sample of ADHD combined-type probands. Results: The original observations were confirmed, with an overall odds ratio of 1.4 across samples. Conclusions: These data challenge results of meta-analyses suggesting that dopamine transporter variation does not have an effect on the risk for ADHD, and they indicate that further investigation of functional variation in the gene is required. <br/

Investigating splicing variants uncovered by next-generation sequencing the Alzheimer’s disease candidate genes, CLU, PICALM, CR1, ABCA7, BIN1, the MS4A locus, CD2AP, EPHA1 and CD33

Late onset Alzheimer’s disease (LOAD), the most common cause of late onset dementia, has a strong genetic component. To date, 21 disease-risk loci have been identified through genome wide association studies (GWAS). However, the causative functional variant(s) within these loci are yet to be discovered. This study aimed to identify potential functional splicing mutations in the nine original GWAS-risk genes: CLU, PICALM, CR1, ABCA7, BIN1, the MS4A locus, CD2AP, EPHA1 and CD33. Target enriched next generation sequencing (NGS) was used to resequence the entire genetic region for each of these GWAS-risk loci in 96 LOAD patients and in silico databases were used to annotate the variants for functionality. Predicted splicing variants were further functionally characterised using splicing prediction software and minigene splicing assays. Following in silico annotation, 21 variants were predicted to influence splicing and, upon further annotation, four of these were examined utilising the in vitro minigene assay. Two variants, rs881768 A>G in ABCA7 and a novel variant 11: 60179827 T>G in MS4A6A were shown, in these cell assays, to affect the splicing of these genes. The method employed in the paper successfully identified potential splicing variants in GWAS-risk genes. Further investigation will be needed to understand the full effect of these variants on LOAD risk. However, these results suggest a possible pipeline in order to identify putative functional variants as a result of NGS in disease-associated loci although improvements are needed within the current prediction programme in order to reduce the number of false positives

Association study between the monoamine oxidase A gene and attention deficit hyperactivity disorder in Taiwanese samples

BACKGROUND: Attention deficit hyperactivity disorder (ADHD) is a common and highly heritable disorder of childhood characterized by inattention, hyperactivity and impulsivity. Molecular genetic and pharmacological studies suggest the involvement of the dopaminergic, serotonergic and noradrenergic neurotransmitter systems in the pathogenesis of ADHD. Monoamine oxidase A (MAO-A) encodes an enzyme that degrades biogenic amines, including neurotransmitters such as norepinephrine, dopamine and serotonin. In this study we examined a 30 bp promoter variable number tandem repeat (VNTR) and a functional G/T single nucleotide polymorphism (SNP) at position 941 in exon 8 (941G/T) of MAO-A for association with ADHD in a Taiwanese sample of 212 ADHD probands. METHODS: Within-family transmission disequilibrium test (TDT) was used to analyse association of MAO-A polymorphisms with ADHD in a Taiwanese population. RESULTS: A nominally significant association was found between the G-allele of 941G/T in MAO-A and ADHD (TDT: P = 0.034. OR = 1.57). Haplotype analysis identified increased transmission of a haplotype consisting of the 3-repeat allele of the promoter VNTR and the G-allele of the 941G/T SNP (P = 0.045) to ADHD cases which the strong association with the G-allele drove. CONCLUSION: These findings suggest the importance of the 941G/T MAO-A polymorphism in the development of ADHD in the Taiwanese population. These results replicate previously published findings in a Caucasian sample

A genetic link between risk for Alzheimer's disease and severe COVID-19 outcomes via the OAS1 gene

Recently, we reported oligoadenylate synthetase 1 (OAS1) contributed to the risk of Alzheimer’s disease, by its enrichment in transcriptional networks expressed by microglia. However, the function of OAS1 within microglia was not known. Using genotyping from 1313 individuals with sporadic Alzheimer’s disease and 1234 control individuals, we confirm the OAS1 variant, rs1131454, is associated with increased risk for Alzheimer’s disease. The same OAS1 locus has been recently associated with severe coronavirus disease 2019 (COVID-19) outcomes, linking risk for both diseases. The single nucleotide polymorphisms rs1131454(A) and rs4766676(T) are associated with Alzheimer’s disease, and rs10735079(A) and rs6489867(T) are associated with severe COVID-19, where the risk alleles are linked with decreased OAS1 expression. Analysing single-cell RNA-sequencing data of myeloid cells from Alzheimer’s disease and COVID-19 patients, we identify co-expression networks containing interferon (IFN)-responsive genes, including OAS1, which are significantly upregulated with age and both diseases. In human induced pluripotent stem cell-derived microglia with lowered OAS1 expression, we show exaggerated production of TNF-α with IFN-γ stimulation, indicating OAS1 is required to limit the pro-inflammatory response of myeloid cells. Collectively, our data support a link between genetic risk for Alzheimer’s disease and susceptibility to critical illness with COVID-19 centred on OAS1, a finding with potential implications for future treatments of Alzheimer’s disease and COVID-19, and development of biomarkers to track disease progression

No evidence for the association of DRD4 with ADHD in a Taiwanese population within-family study

BACKGROUND: Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent and highly heritable childhood disorder. The dopamine D4 receptor (DRD4) gene has shown a genetic association with ADHD in Caucasian populations with meta-analysis indicating a small but significant effect across datasets. It remains uncertain whether this association can be generalised to non-Caucasian ethnic groups. Here we investigate two markers within the DRD4 gene in a Taiwanese population, the exon 3 variable number tandem repeat (VNTR) and a 5' 120 base-pair duplication. METHODS: Within-family transmission disequilibrium tests of association of the 5' 120 base-pair duplication, and exon 3 VNTR in a Taiwanese population. RESULTS: No evidence of association of ADHD with either polymorphism in this population was observed. CONCLUSION: The DRD4 gene markers investigated were not found to be associated with ADHD in this Taiwanese sample. Further work in Taiwanese and other Asian populations will therefore be required to establish whether the reports of association of DRD4 genetic variants in Caucasian samples can be generalised to Asian populations

Observations of extensive gene expression differences in the cerebellum and potential relevance to Alzheimer's disease

Objectives: In order to determine how gene expression is altered in disease it is of fundamental importance that the global distribution of gene expression levels across the disease-free brain are understood and how differences between tissue types might inform tissue choice for investigation of altered expression in disease state. The aim of this pilot project was to use RNA-sequencing to investigate gene expression differences between five general areas of post-mortem human brain (frontal, temporal, occipital, parietal and cerebellum), and in particular changes in gene expression in the cerebellum compared to cortex regions for genes relevant to Alzheimer’s disease, as the cerebellum is largely preserved from disease pathology and could be an area of interest for neuroprotective pathways. Results: General gene expression profiles were found to be similar between cortical regions of the brain, however the cerebellum presented a distinct expression profile. Focused exploration of gene expression for genes associated with Alzheimer’s disease suggest that those involved in the immunity pathway show little expression in the brain. Furthermore some Alzheimer’s disease associated genes display significantly different expression in the cerebellum compared with other brain regions, which might indicate potential neuroprotective measures

Recalibrating the epigenetic clock: implications for assessing biological age in the human cortex.

Human DNA methylation data have been used to develop biomarkers of ageing, referred to as 'epigenetic clocks', which have been widely used to identify differences between chronological age and biological age in health and disease including neurodegeneration, dementia and other brain phenotypes. Existing DNA methylation clocks have been shown to be highly accurate in blood but are less precise when used in older samples or in tissue types not included in training the model, including brain. We aimed to develop a novel epigenetic clock that performs optimally in human cortex tissue and has the potential to identify phenotypes associated with biological ageing in the brain. We generated an extensive dataset of human cortex DNA methylation data spanning the life course (n = 1397, ages = 1 to 108 years). This dataset was split into 'training' and 'testing' samples (training: n = 1047; testing: n = 350). DNA methylation age estimators were derived using a transformed version of chronological age on DNA methylation at specific sites using elastic net regression, a supervised machine learning method. The cortical clock was subsequently validated in a novel independent human cortex dataset (n = 1221, ages = 41 to 104 years) and tested for specificity in a large whole blood dataset (n = 1175, ages = 28 to 98 years). We identified a set of 347 DNA methylation sites that, in combination, optimally predict age in the human cortex. The sum of DNA methylation levels at these sites weighted by their regression coefficients provide the cortical DNA methylation clock age estimate. The novel clock dramatically outperformed previously reported clocks in additional cortical datasets. Our findings suggest that previous associations between predicted DNA methylation age and neurodegenerative phenotypes might represent false positives resulting from clocks not robustly calibrated to the tissue being tested and for phenotypes that become manifest in older ages. The age distribution and tissue type of samples included in training datasets need to be considered when building and applying epigenetic clock algorithms to human epidemiological or disease cohorts