| 1. |
- Chen, Chi-Hua, et al.
(författare)
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Leveraging genome characteristics to improve gene discovery for putamen subcortical brain structure
- 2017
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Ingår i: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- Discovering genetic variants associated with human brain structures is an on-going effort. The ENIGMA consortium conducted genome-wide association studies (GWAS) with standard multi-study analytical methodology and identified several significant single nucleotide polymorphisms (SNPs). Here we employ a novel analytical approach that incorporates functional genome annotations (e.g., exon or 5′UTR), total linkage disequilibrium (LD) scores and heterozygosity to construct enrichment scores for improved identification of relevant SNPs. The method provides increased power to detect associated SNPs by estimating stratum-specific false discovery rate (FDR), where strata are classified according to enrichment scores. Applying this approach to the GWAS summary statistics of putamen volume in the ENIGMA cohort, a total of 15 independent significant SNPs were identified (conditional FDR < 0.05). In contrast, 4 SNPs were found based on standard GWAS analysis (P < 5 × 10−8). These 11 novel loci include GATAD2B, ASCC3, DSCAML1, and HELZ, which are previously implicated in various neural related phenotypes. The current findings demonstrate the boost in power with the annotation-informed FDR method, and provide insight into the genetic architecture of the putamen.
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| 2. |
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| 3. |
- Kauppi, Karolina, et al.
(författare)
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Revisiting Antipsychotic Drug Actions Through Gene Networks Associated With Schizophrenia
- 2018
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Ingår i: American Journal of Psychiatry. - : AMER PSYCHIATRIC PUBLISHING, INC. - 0002-953X .- 1535-7228. ; 175:7, s. 674-682
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Tidskriftsartikel (refereegranskat)abstract
- Objective: Antipsychotic drugs were incidentally discovered in the 1950s, but their mechanisms of action are still not understood. Better understanding of schizophrenia pathogenesis could shed light on actions of current drugs and reveal novel "druggable" pathways for unmet therapeutic needs. Recent genome-wide association studies offer unprecedented opportunities to characterize disease gene networks and uncover drug-disease relationships. Polygenic overlap between schizophrenia risk genes and antipsychotic drug targets has been demonstrated, but specific genes and pathways constituting this overlap are undetermined. Risk genes of polygenic disorders do not operate in isolation but in combination with other genes through protein-protein interactions among gene product.Method: The protein interactome was used to map antipsychotic drug targets (N=88) to networks of schizophrenia risk genes (N=328).Results: Schizophrenia risk genes were significantly localized in the interactome, forming a distinct disease module. Core genes of the module were enriched for genes involved in developmental biology and cognition, which may have a central role in schizophrenia etiology. Antipsychotic drug targets overlapped with the core disease module and comprised multiple pathways beyond dopamine. Some important risk genes like CHRN, PCDH, and HCN families were not connected to existing antipsychotics but may be suitable targets for novel drugs or drug repurposing opportunities to treat other aspects of schizophrenia, such as cognitive or negative symptoms.Conclusions: The network medicine approach provides a platform to collate information of disease genetics and drug-gene interactions to shift focus from development of antipsychotics to multitarget antischizophrenia drugs. This approach is transferable to other diseases.
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| 4. |
- Lo, Min-Tzu, et al.
(författare)
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Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders
- 2017
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 49:1, s. 152-156
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Tidskriftsartikel (refereegranskat)abstract
- Personality is influenced by genetic and environmental factors(1) and associated with mental health. However, the underlying genetic determinants are largely unknown. We identified six genetic loci, including five novel loci(2,3), significantly associated with personality traits in a meta-analysis of genome-wide association studies (N = 123,132-260,861). Of these genome-wide significant loci, extraversion was associated with variants in WSCD2 and near PCDH15, and neuroticism with variants on chromosome 8p23.1 and in L3MBTL2. We performed a principal component analysis to extract major dimensions underlying genetic variations among five personality traits and six psychiatric disorders (N = 5,422-18,759). The first genetic dimension separated personality traits and psychiatric disorders, except that neuroticism and openness to experience were clustered with the disorders. High genetic correlations were found between extraversion and attention-deficit- hyperactivity disorder (ADHD) and between openness and schizophrenia and bipolar disorder. The second genetic dimension was closely aligned with extraversion-introversion and grouped neuroticism with internalizing psychopathology (e.g., depression or anxiety).
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| 5. |
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| 6. |
- Lo, Min-Tzu, et al.
(författare)
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Identification of genetic heterogeneity of Alzheimer's disease across age
- 2019
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Ingår i: Neurobiology of Aging. - : Elsevier. - 0197-4580 .- 1558-1497. ; 84, s. 243.e1-243.e9
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Tidskriftsartikel (refereegranskat)abstract
- The risk of APOE for Alzheimer's disease (AD) is modified by age. Beyond APOE, the polygenic architecture may also be heterogeneous across age. We aim to investigate age-related genetic heterogeneity of AD and identify genomic loci with differential effects across age. Stratified gene-based genome-wide association studies and polygenic variation analyses were performed in the younger (60-79 years, N = 14,895) and older (>= 80 years, N = 6559) age-at-onset groups using Alzheimer's Disease Genetics Consortium data. We showed a moderate genetic correlation (r(g) = 0.64) between the two age groups, supporting genetic heterogeneity. Heritability explained by variants on chromosome 19 (harboring APOE) was significantly larger in younger than in older onset group (p < 0.05). APOE region, BIN1, OR2S2, MS4A4E, and PICALM were identified at the gene-based genome-wide significance (p < 2.73 x 10(-6)) with larger effects at younger age (except MS4A4E). For the novel gene OR2S2, we further performed leave-one-out analyses, which showed consistent effects across subsamples. Our results suggest using genetically more homogeneous individuals may help detect additional susceptible loci. Published by Elsevier Inc.
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| 7. |
- Lo, Min-Tzu, et al.
(författare)
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Modeling prior information of common genetic variants improves gene discovery for neuroticism
- 2017
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Ingår i: Human Molecular Genetics. - : OXFORD UNIV PRESS. - 0964-6906 .- 1460-2083. ; 26:22, s. 4530-4539
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Tidskriftsartikel (refereegranskat)abstract
- Neuroticism reflects emotional instability, and is related to various mental and physical health issues. However, the majority of genetic variants associated with neuroticism remain unclear. Inconsistent genetic variants identified by different genome-wide association studies (GWAS) may be attributable to low statistical power. We proposed a novel framework to improve the power for gene discovery by incorporating prior information of single nucleotide polymorphisms (SNPs) and combining two relevant existing tools, relative enrichment score (RES) and conditional false discovery rate (FDR). Here, SNP's conditional FDR was estimated given its RES based on SNP prior information including linkage disequilibrium (LD)-weighted genic annotation scores, total LD scores and heterozygosity. A known significant locus in chromosome 8p was excluded before estimating FDR due to long-range LD structure. Only one significant LD-independent SNP was detected by analyses of unconditional FDR and traditional GWAS in the discovery sample (N = 59 225), and notably four additional SNPs by conditional FDR. Three of the five SNPs, all identified by conditional FDR, were replicated (P < 0.05) in an independent sample (N = 170 911). These three SNPs are located in intronic regions of CADM2, LINGO2 and EP300 which have been reported to be associated with autism, Parkinson's disease and schizophrenia, respectively. Our approach using a combination of RES and conditional FDR improved power of traditional GWAS for gene discovery providing a useful framework for the analysis of GWAS summary statistics by utilizing SNP prior information, and helping to elucidate the links between neuroticism and complex diseases from a genetic perspective.
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| 8. |
- Sanyal, Nilotpal, et al.
(författare)
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GWASinlps : non-local prior based iterative SNP selection tool for genome-wide association studies
- 2019
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Ingår i: Bioinformatics. - : Oxford University Press. - 1367-4803 .- 1367-4811. ; 35:1, s. 1-11
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Tidskriftsartikel (refereegranskat)abstract
- Motivation: Multiple marker analysis of the genome-wide association study (GWAS) data has gained ample attention in recent years. However, because of the ultra high-dimensionality of GWAS data, such analysis is challenging. Frequently used penalized regression methods often lead to large number of false positives, whereas Bayesian methods are computationally very expensive. Motivated to ameliorate these issues simultaneously, we consider the novel approach of using non-local priors in an iterative variable selection framework.Results: We develop a variable selection method, named, iterative non-local prior based selection for GWAS, or GWASinlps, that combines, in an iterative variable selection framework, the computational efficiency of the screen-and-select approach based on some association learning and the parsimonious uncertainty quantification provided by the use of non-local priors. The hallmark of our method is the introduction of 'structured screen-and-select' strategy, that considers hierarchical screening, which is not only based on response-predictor associations, but also based on response-response associations and concatenates variable selection within that hierarchy. Extensive simulation studies with single nucleotide polymorphisms having realistic linkage disequilibrium structures demonstrate the advantages of our computationally efficient method compared to several frequentist and Bayesian variable selection methods, in terms of true positive rate, false discovery rate, mean squared error and effect size estimation error. Further, we provide empirical power analysis useful for study design. Finally, a real GWAS data application was considered with human height as phenotype.
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