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Sökning: WFRF:(Fan Chun Chieh)

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1.
  • Musliner, Katherine L., et al. (författare)
  • Association of Polygenic Liabilities for Major Depression, Bipolar Disorder, and Schizophrenia With Risk for Depression in the Danish Population
  • 2019
  • Ingår i: JAMA psychiatry. - Chicago : American Medical Association. - 2168-6238. ; 76:5, s. 516-525
  • Tidskriftsartikel (refereegranskat)abstract
    • IMPORTANCE: Although the usefulness of polygenic risk scores as a measure of genetic liability for major depression (MD) has been established, their association with depression in the general population remains relatively unexplored.OBJECTIVE: To evaluate whether polygenic risk scores for MD, bipolar disorder (BD), and schizophrenia (SZ) are associated with depression in the general population and explore whether these polygenic liabilities are associated with heterogeneity in terms of age at onset and severity at the initial depression diagnosis.DESIGN SETTING AND PARTICIPANTS: Participants were drawn from the Danish iPSYCH2012 case-cohort study, a representative sample drawn from the population of Denmark born between May 1, 1981, and December 31, 2005. The hazard of depression was estimated using Cox regressions modified to accommodate the case-cohort design. Case-only analyses were conducted using linear and multinomial regressions. The data analysis was conducted from February 2017 to June 2018.EXPOSURES: Polygenic risk scores for MD, BD, and SZ trained using the most recent genome-wide association study results from the Psychiatric Genomics Consortium.MAIN OUTCOMES AND MEASURES: The main outcome was first depressive episode (international Statistical Classification of Diseases and Related Health Problems, Tenth Revision [ICD-10] code F32) treated in hospital-based psychiatric care. Severity at the initial diagnosis was measured using the ICD-10 code severity specifications (mild, moderate, severe without psychosis, and severe with psychosis) and treatment setting (inpatient, outpatient, and emergency).RESULTS: Of 34 573 participants aged 10 to 31 years at censoring, 68% of those with depression were female compared with 48.9% of participants without depression. Each SD increase in polygenic liability for MD, BD, and SZ was associated with 30% (hazard ratio [HR], 1.30; 95% CI, 1.27-1.33), 5% (HR, 1.05; 95% CI, 1.02-1.07), and 12% (HR, 1.12; 95% CI, 1.09-1.15) increases in the hazard of depression, respectively. Among cases, a higher polygenic liability for BD was associated with earlier depression onset (beta =-.07; SE =.02; P =.002).CONCLUSIONS AND RELEVANCE: Polygenic ability for MD is associated with first depress on in the general population, which supports the idea that these scores tap into an underlying liability for developing the disorder. The fact that polygenic risk for BD and polygenic risk for SZ also were associated with depression is consistent with prior evidence that these disorders share some common genetic overlap. Variations in polygenic liability may contribute slightly to heterogeneity in clinical presentation, but these associations appear minimal.
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2.
  • Stahl, Eli A, et al. (författare)
  • Genome-wide association study identifies 30 loci associated with bipolar disorder
  • 2019
  • Ingår i: Nature Genetics. - 1061-4036. ; 51:5, s. 793-803
  • Tidskriftsartikel (refereegranskat)abstract
    • Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10-8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder.
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3.
  • Chen, Chi-Hua, et al. (författare)
  • Leveraging genome characteristics to improve gene discovery for putamen subcortical brain structure
  • 2017
  • Ingår i: Scientific Reports. - Nature Publishing Group. - 2045-2322. ; 7
  • 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.
4.
  • Kauppi, Karolina, et al. (författare)
  • Combining Polygenic Hazard Score With Volumetric MRI and Cognitive Measures Improves Prediction of Progression From Mild Cognitive Impairment to Alzheimer's Disease
  • 2018
  • Ingår i: Frontiers in Neuroscience. - Frontiers Media S.A.. - 1662-4548. ; 12
  • Tidskriftsartikel (refereegranskat)abstract
    • Improved prediction of progression to Alzheimer's Disease (AD) among older individuals with mild cognitive impairment (MCI) is of high clinical and societal importance. We recently developed a polygenic hazard score (PHS) that predicted age of AD onset above and beyond APOE. Here, we used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to further explore the potential clinical utility of PHS for predicting AD development in older adults with MCI. We examined the predictive value of PHS alone and in combination with baseline structural magnetic resonance imaging (MRI) data on performance on the Mini-Mental State Exam (MMSE). In survival analyses, PHS significantly predicted time to progression from MCI to AD over 120 months (p = 1.07e-5), and PHS was significantly more predictive than APOE alone (p = 0.015). Combining PHS with baseline brain atrophy score and/or MMSE score significantly improved prediction compared to models without PHS (three-factor model p = 4.28e-17). Prediction model accuracies, sensitivities and area under the curve were also improved by including PHS in the model, compared to only using atrophy score and MMSE. Further, using linear mixed-effect modeling, PHS improved the prediction of change in the Clinical Dementia Rating—Sum of Boxes (CDR-SB) score and MMSE over 36 months in patients with MCI at baseline, beyond both APOE and baseline levels of brain atrophy. These results illustrate the potential clinical utility of PHS for assessment of risk for AD progression among individuals with MCI both alone, or in conjunction with clinical measures of prodromal disease including measures of cognitive function and regional brain atrophy.
5.
  • Lo, Min-Tzu, et al. (författare)
  • Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders
  • 2017
  • Ingår i: Nature Genetics. - 1061-4036. ; 49:1, s. 152-156
  • 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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7.
  • Lo, Min-Tzu, et al. (författare)
  • Modeling prior information of common genetic variants improves gene discovery for neuroticism
  • 2017
  • Ingår i: Human Molecular Genetics. - OXFORD UNIV PRESS. - 0964-6906. ; 26:22, s. 4530-4539
  • 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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