| 1. |
- Escott-Price, Valentina, et al.
(author)
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Gene-Wide Analysis Detects Two New Susceptibility Genes for Alzheimer's Disease
- 2014
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In: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 9:6, s. e94661-
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Journal article (peer-reviewed)abstract
- Background: Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls. Principal Findings: In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p = 1.4x10(-6)) and 14 (IGHV1-67 p = 7.9x10(-8)) which indexed novel susceptibility loci. Significance: The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease.
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| 2. |
- Jones, Lesley, et al.
(author)
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Convergent genetic and expression data implicate immunity in Alzheimer's disease
- 2015
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In: Alzheimer's & Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 11:6, s. 658-671
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Journal article (peer-reviewed)abstract
- Background: Late-onset Alzheimer's disease (AD) is heritable with 20 genes showing genome-wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease, we extended these genetic data in a pathway analysis. Methods: The ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain. Results: ALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (P = 3.27 X 10(-12) after multiple testing correction for pathways), regulation of endocytosis (P = 1.31 X 10(-11)), cholesterol transport (P = 2.96 X 10(-9)), and proteasome-ubiquitin activity (P = 1.34 X 10(-6)). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected P = .002-.05). Conclusions: The immime response, regulation of endocytosis, cholesterol transport, and protein ubiquitination represent prime targets for AD therapeutics.
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| 3. |
- Erzurumluoglu, A. Mesut, et al.
(author)
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Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci
- 2020
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In: Molecular Psychiatry. - : Nature Publishing Group. - 1359-4184 .- 1476-5578. ; 25:10, s. 2392-2409
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Journal article (peer-reviewed)abstract
- Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations with P < 5 × 10-8 in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits (P < 5 × 10-8) in the discovery samples. Ten novel SNVs, including rs12616219 near TMEM182, were followed-up and five of them (rs462779 in REV3L, rs12780116 in CNNM2, rs1190736 in GPR101, rs11539157 in PJA1, and rs12616219 near TMEM182) replicated at a Bonferroni significance threshold (P < 4.5 × 10-3) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, in CCDC141 and two low-frequency SNVs in CEP350 and HDGFRP2. Functional follow-up implied that decreased expression of REV3L may lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation.
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| 4. |
- Chapuis, Julien, et al.
(author)
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Genome-wide, high-content siRNA screening identifies the Alzheimer’s genetic risk factor FERMT2 as a major modulator of APP metabolism
- 2017
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In: Acta Neuropathologica. - : Springer Science and Business Media LLC. - 0001-6322 .- 1432-0533. ; 133:6, s. 955-966
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Journal article (peer-reviewed)abstract
- Genome-wide association studies (GWASs) have identified 19 susceptibility loci for Alzheimer’s disease (AD). However, understanding how these genes are involved in the pathophysiology of AD is one of the main challenges of the “post-GWAS” era. At least 123 genes are located within the 19 susceptibility loci; hence, a conventional approach (studying the genes one by one) would not be time- and cost-effective. We therefore developed a genome-wide, high-content siRNA screening approach and used it to assess the functional impact of gene under-expression on APP metabolism. We found that 832 genes modulated APP metabolism. Eight of these genes were located within AD susceptibility loci. Only FERMT2 (a β3-integrin co-activator) was also significantly associated with a variation in cerebrospinal fluid Aβ peptide levels in 2886 AD cases. Lastly, we showed that the under-expression of FERMT2 increases Aβ peptide production by raising levels of mature APP at the cell surface and facilitating its recycling. Taken as a whole, our data suggest that FERMT2 modulates the AD risk by regulating APP metabolism and Aβ peptide production.
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