Browsing by Author "Kim, Soyeon"

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    Identifying novel genetic variants for brain amyloid deposition: a genome-wide association study in the Korean population
    (BMC, 2021-06-21) Kim, Hang-Rai; Jung, Sang-Hyuk; Kim, Jaeho; Jang, Hyemin; Kang, Sung Hoon; Hwangbo, Song; Kim, Jun Pyo; Kim, So Yeon; Kim, Beomsu; Kim, Soyeon; Jeong, Jee Hyang; Yoon, Soo Jin; Park, Kyung Won; Kim, Eun-Joo; Yoon, Bora; Jang, Jae-Won; Hong, Jin Yong; Choi, Seong Hye; Noh, Young; Kim, Ko Woon; Kim, Si Eun; Lee, Jin San; Jung, Na-Yeon; Lee, Juyoun; Kim, Byeong C.; Son, Sang Joon; Hong, Chang Hyung; Na, Duk L.; Seo, Sang Won; Won, Hong-Hee; Kim, Hee Jin; Radiology and Imaging Sciences, School of Medicine
    Background: Genome-wide association studies (GWAS) have identified a number of genetic variants for Alzheimer's disease (AD). However, most GWAS were conducted in individuals of European ancestry, and non-European populations are still underrepresented in genetic discovery efforts. Here, we performed GWAS to identify single nucleotide polymorphisms (SNPs) associated with amyloid β (Aβ) positivity using a large sample of Korean population. Methods: One thousand four hundred seventy-four participants of Korean ancestry were recruited from multicenters in South Korea. Discovery dataset consisted of 1190 participants (383 with cognitively unimpaired [CU], 330 with amnestic mild cognitive impairment [aMCI], and 477 with AD dementia [ADD]) and replication dataset consisted of 284 participants (46 with CU, 167 with aMCI, and 71 with ADD). GWAS was conducted to identify SNPs associated with Aβ positivity (measured by amyloid positron emission tomography). Aβ prediction models were developed using the identified SNPs. Furthermore, bioinformatics analysis was conducted for the identified SNPs. Results: In addition to APOE, we identified nine SNPs on chromosome 7, which were associated with a decreased risk of Aβ positivity at a genome-wide suggestive level. Of these nine SNPs, four novel SNPs (rs73375428, rs2903923, rs3828947, and rs11983537) were associated with a decreased risk of Aβ positivity (p < 0.05) in the replication dataset. In a meta-analysis, two SNPs (rs7337542 and rs2903923) reached a genome-wide significant level (p < 5.0 × 10-8). Prediction performance for Aβ positivity increased when rs73375428 were incorporated (area under curve = 0.75; 95% CI = 0.74-0.76) in addition to clinical factors and APOE genotype. Cis-eQTL analysis demonstrated that the rs73375428 was associated with decreased expression levels of FGL2 in the brain. Conclusion: The novel genetic variants associated with FGL2 decreased risk of Aβ positivity in the Korean population. This finding may provide a candidate therapeutic target for AD, highlighting the importance of genetic studies in diverse populations.
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    Shared Genetic Background Between Cerebrospinal Fluid Biomarkers and Risk for Alzheimer’s Disease: A Two-Sample Mendelian Randomization Study
    (IOS, 2021) Kim, Soyeon; Kim, Kiwon; Nho, Kwangsik; Myung, Woojae; Won, Hong-Hee; Radiology and Imaging Sciences, School of Medicine
    Background: Whether the epidemiological association of amyloid beta (Aβ) and tau pathology with Alzheimer’s disease (AD) is causal remains unclear. Recent failures to demonstrate the efficacy of several Aβ-modifying drugs may indicate a possibility that the observed association is not causal, which led to efforts to develop tau-directed treatments whose efficacy remains tentative. Methods: Herein, we conducted a two-sample Mendelian randomisation analysis to investigate shared genetic background between cerebrospinal fluid (CSF) biomarkers for amyloid and tau pathology and risk for AD, and to find genetic evidence for causal association between these CSF biomarkers and risk for AD. We used summary statistics of genome-wide association study (GWAS) for CSF biomarkers (Aβ 1-42 , phosphorylated tau 181 [p-tau], and total tau [t-tau]) in 3,146 individuals and for late-onset AD (LOAD) in 21,982 LOAD cases and 41,944 cognitively-normal controls. We tested association between changes in the genetically-predicted CSF biomarkers and LOAD risk. Results: We found a decrease in the LOAD risk per one-standard deviation (SD) increase in the genetically-predicted CSF Aβ (odds ratio [OR], 2.87×10 -3 for AD; 95% confidence interval [CI], 1.54×10 -4 –0.05; p = 8.91×10 -5 ). Conversely, we observed an increase in the LOAD risk per one-SD increase in the genetically-predicted CSF p-tau (OR, 19.46; 95% CI, 1.50–2.52×10 2 ; p = 0.02) and t-tau (OR, 33.80; 95% CI, 1.57–7.29×10 2 ; p = 0.02). Conclusions: Our findings suggest a shared genetic background between the CSF biomarkers and LOAD risk. Although it requires validation by future studies including more genetic variants identified in large-scale GWASs for CSF biomarkers, our results suggest a causal association between CSF biomarkers and risk for LOAD.