Displaying publications 1 - 20 of 188 in total

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  1. Yu X, Megens HJ, Mengistu SB, Bastiaansen JWM, Mulder HA, Benzie JAH, et al.
    BMC Genomics, 2021 Jun 09;22(1):426.
    PMID: 34107887 DOI: 10.1186/s12864-021-07486-5
    BACKGROUND: Tilapia is one of the most abundant species in aquaculture. Hypoxia is known to depress growth rate, but the genetic mechanism by which this occurs is unknown. In this study, two groups consisting of 3140 fish that were raised in either aerated (normoxia) or non-aerated pond (nocturnal hypoxia). During grow out, fish were sampled five times to determine individual body weight (BW) gains. We applied a genome-wide association study to identify SNPs and genes associated with the hypoxic and normoxic environments in the 16th generation of a Genetically Improved Farmed Tilapia population.

    RESULTS: In the hypoxic environment, 36 SNPs associated with at least one of the five body weight measurements (BW1 till BW5), of which six, located between 19.48 Mb and 21.04 Mb on Linkage group (LG) 8, were significant for body weight in the early growth stage (BW1 to BW2). Further significant associations were found for BW in the later growth stage (BW3 to BW5), located on LG1 and LG8. Analysis of genes within the candidate genomic region suggested that MAPK and VEGF signalling were significantly involved in the later growth stage under the hypoxic environment. Well-known hypoxia-regulated genes such as igf1rb, rora, efna3 and aurk were also associated with growth in the later stage in the hypoxic environment. Conversely, 13 linkage groups containing 29 unique significant and suggestive SNPs were found across the whole growth period under the normoxic environment. A meta-analysis showed that 33 SNPs were significantly associated with BW across the two environments, indicating a shared effect independent of hypoxic or normoxic environment. Functional pathways were involved in nervous system development and organ growth in the early stage, and oocyte maturation in the later stage.

    CONCLUSIONS: There are clear genotype-growth associations in both normoxic and hypoxic environments, although genome architecture involved changed over the growing period, indicating a transition in metabolism along the way. The involvement of pathways important in hypoxia especially at the later growth stage indicates a genotype-by-environment interaction, in which MAPK and VEGF signalling are important components.

    Matched MeSH terms: Genome-Wide Association Study*
  2. Zakaria WNA, Sasongko TH, Al-Rahbi B, Al-Sowayan N, Ahmad AH, Zakaria R, et al.
    Psychiatr Genet, 2023 Apr 01;33(2):37-49.
    PMID: 36825838 DOI: 10.1097/YPG.0000000000000336
    This study aimed to perform a bibliometric analysis on genetic studies in schizophrenia in the pregenome-wide association studies (GWAS) and post-GWAS era. We searched the literature on genes and schizophrenia using the Scopus database. The documents increased with time, especially after the human genome project and International HapMap Project, with the highest citation in 2008. The top occurrence author keywords were discovered to be different in the pre-GWAS and post-GWAS eras, reflecting the progress of genetic studies connected to schizophrenia. Emerging keywords highlighted a trend towards an application of precision medicine, showing an interplay of environmental exposures as well as genetic factors in schizophrenia pathogenesis, progression, and response to therapy. In conclusion, the gene and schizophrenia literature has grown rapidly after the human genome project, and the temporal variation in the author keywords pattern reflects the trend of genetic studies related to schizophrenia in the pre-GWAS and post-GWAS era.
    Matched MeSH terms: Genome-Wide Association Study*
  3. Nor Hashim NA, Ramzi NH, Velapasamy S, Alex L, Chahil JK, Lye SH, et al.
    Asian Pac J Cancer Prev, 2012;13(12):6005-10.
    PMID: 23464394
    BACKGROUND: Nasopharyngeal carcinoma (NPC) is endemic in Southern Chinese and Southeast Asian populations. Geographical and ethnic clustering of the cancer is due to genetic, environmental, and lifestyle risk factors. This case-control study aimed to identify or confirm both genetic and non-genetic risk factors for NPC in one of the endemic countries, Malaysia.

    MATERIALS AND METHOD: A panel of 768 single-nucleotide polymorphisms (SNPs) previously associated with various cancers and known non-genetic risk factors for NPC were selected and analyzed for their associations with NPC in a case-control study.

    RESULTS: Statistical analysis identified 40 SNPs associated with NPC risk in our population, including 5 documented previously by genome-wide association studies (GWAS) and other case-control studies; the associations of the remaining 35 SNPs with NPC were novel. In addition, consistent with previous studies, exposure to occupational hazards, overconsumption of salt-cured foods, red meat, as well as low intake of fruits and vegetables were also associated with NPC risk.

    CONCLUSIONS: In short, this study confirmed and/or identified genetic, environmental and dietary risk factors associated with NPC susceptibility in a Southeast Asian population.

    Matched MeSH terms: Genome-Wide Association Study*
  4. Chen Z, Song J, Tang L
    BMC Oral Health, 2023 Nov 02;23(1):827.
    PMID: 37919698 DOI: 10.1186/s12903-023-03575-x
    OBJECTIVE: Several research has considered the potential correlation between periodontitis and serum lipids. However, serum lipid profiles correlation with periodontitis remains largely unknown. The investigation objective was to examine periodontitis correlation with serum lipid levels using a bidirectional Mendelian randomization (MR) analysis.

    METHODS: The study employed a bidirectional MR analysis with two samples, utilizing a freely accessible genome-wide association study (GWAS). Furthermore, the primary analysis employed the inverse variance weighted (IVW) method. To determine whether the lipid profiles were associated with periodontitis, a variety of sensitivity analyses (including MR-Egger regression, MR-PRESSO, and weighted median), as well as multivariable MR, were employed.

    RESULTS: MR analysis performed by IVW did not reveal any relationship between periodontitis and low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides (TG), or total cholesterol (TC). It was also found that LDL, HDL, TG, and TC were not associated to periodontitis. Furthermore, the MR estimations exhibited consistency with other MR sensitivity and multivariate MR (MVMR) analyses. These results show that the correlation between serum lipid levels and periodontitis could not be established.

    CONCLUSION: The finding indicates a negligible link between periodontitis and serum lipid levels were identified, despite previous observational studies reporting a link between periodontitis and serum lipid levels.

    Matched MeSH terms: Genome-Wide Association Study*
  5. Wang X, Walker A, Revez JA, Ni G, Adams MJ, McIntosh AM, et al.
    Am J Hum Genet, 2023 Jul 06;110(7):1207-1215.
    PMID: 37379836 DOI: 10.1016/j.ajhg.2023.06.006
    In polygenic score (PGS) analysis, the coefficient of determination (R2) is a key statistic to evaluate efficacy. R2 is the proportion of phenotypic variance explained by the PGS, calculated in a cohort that is independent of the genome-wide association study (GWAS) that provided estimates of allelic effect sizes. The SNP-based heritability (hSNP2, the proportion of total phenotypic variances attributable to all common SNPs) is the theoretical upper limit of the out-of-sample prediction R2. However, in real data analyses R2 has been reported to exceed hSNP2, which occurs in parallel with the observation that hSNP2 estimates tend to decline as the number of cohorts being meta-analyzed increases. Here, we quantify why and when these observations are expected. Using theory and simulation, we show that if heterogeneities in cohort-specific hSNP2 exist, or if genetic correlations between cohorts are less than one, hSNP2 estimates can decrease as the number of cohorts being meta-analyzed increases. We derive conditions when the out-of-sample prediction R2 will be greater than hSNP2 and show the validity of our derivations with real data from a binary trait (major depression) and a continuous trait (educational attainment). Our research calls for a better approach to integrating information from multiple cohorts to address issues of between-cohort heterogeneity.
    Matched MeSH terms: Genome-Wide Association Study*
  6. Yun Z, Shen Y, Yan X, Tian S, Wang J, Teo CS, et al.
    J Glob Health, 2024 Mar 15;14:04057.
    PMID: 38487860 DOI: 10.7189/jogh.14.04057
    BACKGROUND: Previous studies have yielded inconsistent results concerning drug use and the risk of cancers. We conducted a large-scale cross-sectional study and a two-sample Mendelian randomisation (MR) study to reveal the causal effect between the use of 19 medications and the risk of four common cancers (breast, lung, colorectal, and prostate).

    METHODS: We obtained information on medication use and cancer diagnosis from National Health and Nutrition Examination Survey participants. After propensity score matching, we conducted survey-weighted multivariate logistic regression and restricted cubic spline analysis to assess the observed correlation between medication use and cancer while adjusting for multiple covariates. We also performed MR analysis to investigate causality based on summary data from genome-wide association studies on medication use and cancers. We performed sensitivity analyses, replication analysis, genetic correlation analysis, and reverse MR analysis to improve the reliability of MR findings.

    RESULTS: We found that the use of agents acting on the renin-angiotensin system was associated with reduced risk of prostate cancer (odds ratio (OR) = 0.42; 95% confidence interval (CI) = 0.27-0.63, P 

    Matched MeSH terms: Genome-Wide Association Study*
  7. Peñaloza C, Robledo D, Barría A, Trịnh TQ, Mahmuddin M, Wiener P, et al.
    G3 (Bethesda), 2020 08 05;10(8):2777-2785.
    PMID: 32532799 DOI: 10.1534/g3.120.401343
    Tilapia are among the most important farmed fish species worldwide, and are fundamental for the food security of many developing countries. Several genetically improved Nile tilapia (Oreochromis niloticus) strains exist, such as the iconic Genetically Improved Farmed Tilapia (GIFT), and breeding programs typically follow classical pedigree-based selection. The use of genome-wide single-nucleotide polymorphism (SNP) data can enable an understanding of the genetic architecture of economically important traits and the acceleration of genetic gain via genomic selection. Due to the global importance and diversity of Nile tilapia, an open access SNP array would be beneficial for aquaculture research and production. In the current study, a ∼65K SNP array was designed based on SNPs discovered from whole-genome sequence data from a GIFT breeding nucleus population and the overlap with SNP datasets from wild fish populations and several other farmed Nile tilapia strains. The SNP array was applied to clearly distinguish between different tilapia populations across Asia and Africa, with at least ∼30,000 SNPs segregating in each of the diverse population samples tested. It is anticipated that this SNP array will be an enabling tool for population genetics and tilapia breeding research, facilitating consistency and comparison of results across studies.
    Matched MeSH terms: Genome-Wide Association Study
  8. Barría A, Trịnh TQ, Mahmuddin M, Peñaloza C, Papadopoulou A, Gervais O, et al.
    Heredity (Edinb), 2021 Sep;127(3):334-343.
    PMID: 34262170 DOI: 10.1038/s41437-021-00447-4
    Enhancing host resistance to infectious disease has received increasing attention in recent years as a major goal of farm animal breeding programs. Combining field data with genomic tools can provide opportunities to understand the genetic architecture of disease resistance, leading to new opportunities for disease control. In the current study, a genome-wide association study was performed to assess resistance to the Tilapia lake virus (TiLV), one of the biggest threats affecting Nile tilapia (Oreochromis niloticus); a key aquaculture species globally. A pond outbreak of TiLV in a pedigreed population of the GIFT strain was observed, with 950 fish classified as either survivor or mortality, and genotyped using a 65 K SNP array. A significant QTL of large effect was identified on chromosome Oni22. The average mortality rate of tilapia homozygous for the resistance allele at the most significant SNP (P value = 4.51E-10) was 11%, compared to 43% for tilapia homozygous for the susceptibility allele. Several candidate genes related to host response to viral infection were identified within this QTL, including lgals17, vps52, and trim29. These results provide a rare example of a major QTL affecting a trait of major importance to a farmed animal. Genetic markers from the QTL region have potential in marker-assisted selection to improve host resistance, providing a genetic solution to an infectious disease where few other control or mitigation options currently exist.
    Matched MeSH terms: Genome-Wide Association Study
  9. Schumacher-Schuh AF, Bieger A, Okunoye O, Mok KY, Lim SY, Bardien S, et al.
    Mov Disord, 2022 Aug;37(8):1593-1604.
    PMID: 35867623 DOI: 10.1002/mds.29126
    BACKGROUND: Human genetics research lacks diversity; over 80% of genome-wide association studies have been conducted on individuals of European ancestry. In addition to limiting insights regarding disease mechanisms, disproportionate representation can create disparities preventing equitable implementation of personalized medicine.

    OBJECTIVE: This systematic review provides an overview of research involving Parkinson's disease (PD) genetics in underrepresented populations (URP) and sets a baseline to measure the future impact of current efforts in those populations.

    METHODS: We searched PubMed and EMBASE until October 2021 using search strings for "PD," "genetics," the main "URP," and and the countries in Latin America, Caribbean, Africa, Asia, and Oceania (excluding Australia and New Zealand). Inclusion criteria were original studies, written in English, reporting genetic results on PD from non-European populations. Two levels of independent reviewers identified and extracted information.

    RESULTS: We observed imbalances in PD genetic studies among URPs. Asian participants from Greater China were described in the majority of the articles published (57%), but other populations were less well studied; for example, Blacks were represented in just 4.0% of the publications. Also, although idiopathic PD was more studied than monogenic forms of the disease, most studies analyzed a limited number of genetic variants. We identified just nine studies using a genome-wide approach published up to 2021, including URPs.

    CONCLUSION: This review provides insight into the significant lack of population diversity in PD research highlighting the immediate need for better representation. The Global Parkinson's Genetics Program (GP2) and similar initiatives aim to impact research in URPs, and the early metrics presented here can be used to measure progress in the field of PD genetics in the future. © 2022 International Parkinson and Movement Disorder Society.

    Matched MeSH terms: Genome-Wide Association Study
  10. Zhang Y, Liu S, De Meyer M, Liao Z, Zhao Y, Virgilio M, et al.
    J Adv Res, 2023 Nov;53:61-74.
    PMID: 36574947 DOI: 10.1016/j.jare.2022.12.012
    INTRODUCTION: The oriental fruit fly Bactrocera dorsalis is one of the most destructive agricultural pests worldwide, with highly debated species delimitation, origin, and global spread routes.

    OBJECTIVES: Our study intended to (i) resolve the taxonomic uncertainties between B. dorsalis and B. carambolae, (ii) reveal the population structure and global invasion routes of B. dorsalis across Asia, Africa, and Oceania, and (iii) identify genomic regions that are responsible for the thermal adaptation of B. dorsalis.

    METHODS: Based on a high-quality chromosome-level reference genome assembly, we explored the population relationship using a genome-scale single nucleotide polymorphism dataset generated from the resequencing data of 487 B. dorsalis genomes and 25 B. carambolae genomes. Genome-wide association studies and silencing using RNA interference were used to identify and verify the candidate genes associated with extreme thermal stress.

    RESULTS: We showed that B. dorsalis originates from the Southern India region with three independent invasion and spread routes worldwide: (i) from Northern India to Northern Southeast Asia, then to Southern Southeast Asia; (ii) from Northern India to Northern Southeast Asian, then to China and Hawaii; and (iii) from Southern India toward the African mainland, then to Madagascar, which is mainly facilitated by human activities including trade and immigration. Twenty-seven genes were identified by a genome-wide association study to be associated with 11 temperature bioclimatic variables. The Cyp6a9 gene may enhance the thermal adaptation of B. dorsalis and thus boost its invasion, which tended to be upregulated at a hardening temperature of 38 °C. Functional verification using RNA interference silencing against Cyp6a9, led to the specific decrease in Cyp6a9 expression, reducing the survival rate of dsRNA-feeding larvae exposed to extreme thermal stress of 45 °C after heat hardening treatments in B. dorsalis.

    CONCLUSION: This study provides insights into the evolutionary history and genetic basis of temperature adaptation in B. dorsalis.

    Matched MeSH terms: Genome-Wide Association Study
  11. Sullivan P, 96 Psychiatric Genetics Investigators
    Mol Psychiatry, 2012 Jan;17(1):2-3.
    PMID: 21826059 DOI: 10.1038/mp.2011.94
    Matched MeSH terms: Genome-Wide Association Study*
  12. Hoh BP, Deng L, Julia-Ashazila MJ, Zuraihan Z, Nur-Hasnah M, Nur-Shafawati AR, et al.
    Hum Genomics, 2015 Jul 22;9:16.
    PMID: 26194999 DOI: 10.1186/s40246-015-0039-x
    Fine scale population structure of Malays - the major population in Malaysia, has not been well studied. This may have important implications for both evolutionary and medical studies. Here, we investigated the population sub-structure of Malay involving 431 samples collected from all states from peninsular Malaysia and Singapore. We identified two major clusters of individuals corresponding to the north and south peninsular Malaysia. On an even finer scale, the genetic coordinates of the geographical Malay populations are in correlation with the latitudes (R(2) = 0.3925; P = 0.029). This finding is further supported by the pairwise FST of Malay sub-populations, of which the north and south regions showed the highest differentiation (FST [North-south] = 0.0011). The collective findings therefore suggest that population sub-structure of Malays are more heterogenous than previously expected even within a small geographical region, possibly due to factors like different genetic origins, geographical isolation, could result in spurious association as demonstrated in our analysis. We suggest that cautions should be taken during the stage of study design or interpreting the association signals in disease mapping studies which are expected to be conducted in Malay population in the near future.
    Matched MeSH terms: Genome-Wide Association Study*
  13. Jia G, Ping J, Shu X, Yang Y, Cai Q, Kweon SS, et al.
    Am J Hum Genet, 2022 Dec 01;109(12):2185-2195.
    PMID: 36356581 DOI: 10.1016/j.ajhg.2022.10.011
    By combining data from 160,500 individuals with breast cancer and 226,196 controls of Asian and European ancestry, we conducted genome- and transcriptome-wide association studies of breast cancer. We identified 222 genetic risk loci and 137 genes that were associated with breast cancer risk at a p 
    Matched MeSH terms: Genome-Wide Association Study*
  14. Morales Berstein F, McCartney DL, Lu AT, Tsilidis KK, Bouras E, Haycock P, et al.
    Elife, 2022 Mar 29;11.
    PMID: 35346416 DOI: 10.7554/eLife.75374
    BACKGROUND: Epigenetic clocks have been associated with cancer risk in several observational studies. Nevertheless, it is unclear whether they play a causal role in cancer risk or if they act as a non-causal biomarker.

    METHODS: We conducted a two-sample Mendelian randomization (MR) study to examine the genetically predicted effects of epigenetic age acceleration as measured by HannumAge (nine single-nucleotide polymorphisms (SNPs)), Horvath Intrinsic Age (24 SNPs), PhenoAge (11 SNPs), and GrimAge (4 SNPs) on multiple cancers (i.e. breast, prostate, colorectal, ovarian and lung cancer). We obtained genome-wide association data for biological ageing from a meta-analysis (N = 34,710), and for cancer from the UK Biobank (N cases = 2671-13,879; N controls = 173,493-372,016), FinnGen (N cases = 719-8401; N controls = 74,685-174,006) and several international cancer genetic consortia (N cases = 11,348-122,977; N controls = 15,861-105,974). Main analyses were performed using multiplicative random effects inverse variance weighted (IVW) MR. Individual study estimates were pooled using fixed effect meta-analysis. Sensitivity analyses included MR-Egger, weighted median, weighted mode and Causal Analysis using Summary Effect Estimates (CAUSE) methods, which are robust to some of the assumptions of the IVW approach.

    RESULTS: Meta-analysed IVW MR findings suggested that higher GrimAge acceleration increased the risk of colorectal cancer (OR = 1.12 per year increase in GrimAge acceleration, 95% CI 1.04-1.20, p = 0.002). The direction of the genetically predicted effects was consistent across main and sensitivity MR analyses. Among subtypes, the genetically predicted effect of GrimAge acceleration was greater for colon cancer (IVW OR = 1.15, 95% CI 1.09-1.21, p = 0.006), than rectal cancer (IVW OR = 1.05, 95% CI 0.97-1.13, p = 0.24). Results were less consistent for associations between other epigenetic clocks and cancers.

    CONCLUSIONS: GrimAge acceleration may increase the risk of colorectal cancer. Findings for other clocks and cancers were inconsistent. Further work is required to investigate the potential mechanisms underlying the results.

    FUNDING: FMB was supported by a Wellcome Trust PhD studentship in Molecular, Genetic and Lifecourse Epidemiology (224982/Z/22/Z which is part of grant 218495/Z/19/Z). KKT was supported by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme) and by the Hellenic Republic's Operational Programme 'Competitiveness, Entrepreneurship & Innovation' (OΠΣ 5047228). PH was supported by Cancer Research UK (C18281/A29019). RMM was supported by the NIHR Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol and by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme). RMM is a National Institute for Health Research Senior Investigator (NIHR202411). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. GDS and CLR were supported by the Medical Research Council (MC_UU_00011/1 and MC_UU_00011/5, respectively) and by a Cancer Research UK (C18281/A29019) programme grant (the Integrative Cancer Epidemiology Programme). REM was supported by an Alzheimer's Society project grant (AS-PG-19b-010) and NIH grant (U01 AG-18-018, PI: Steve Horvath). RCR is a de Pass Vice Chancellor's Research Fellow at the University of Bristol.

    Matched MeSH terms: Genome-Wide Association Study/methods
  15. Mueller SH, Lai AG, Valkovskaya M, Michailidou K, Bolla MK, Wang Q, et al.
    Genome Med, 2023 Jan 26;15(1):7.
    PMID: 36703164 DOI: 10.1186/s13073-022-01152-5
    BACKGROUND: Low-frequency variants play an important role in breast cancer (BC) susceptibility. Gene-based methods can increase power by combining multiple variants in the same gene and help identify target genes.

    METHODS: We evaluated the potential of gene-based aggregation in the Breast Cancer Association Consortium cohorts including 83,471 cases and 59,199 controls. Low-frequency variants were aggregated for individual genes' coding and regulatory regions. Association results in European ancestry samples were compared to single-marker association results in the same cohort. Gene-based associations were also combined in meta-analysis across individuals with European, Asian, African, and Latin American and Hispanic ancestry.

    RESULTS: In European ancestry samples, 14 genes were significantly associated (q 

    Matched MeSH terms: Genome-Wide Association Study/methods
  16. Papadimitriou N, Muller D, van den Brandt PA, Geybels M, Patel CJ, Gunter MJ, et al.
    Eur J Nutr, 2020 Oct;59(7):2929-2937.
    PMID: 31705265 DOI: 10.1007/s00394-019-02132-z
    PURPOSE: The evidence from the literature regarding the association of dietary factors and risk of prostate cancer is inconclusive.

    METHODS: A nutrient-wide association study was conducted to systematically and comprehensively evaluate the associations between 92 foods or nutrients and risk of prostate cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC). Cox proportional hazard regression models adjusted for total energy intake, smoking status, body mass index, physical activity, diabetes and education were used to estimate hazard ratios and 95% confidence intervals for standardized dietary intakes. As in genome-wide association studies, correction for multiple comparisons was applied using the false discovery rate (FDR 

    Matched MeSH terms: Genome-Wide Association Study*
  17. Tang H, Jiang L, Stolzenberg-Solomon RZ, Arslan AA, Beane Freeman LE, Bracci PM, et al.
    Cancer Epidemiol Biomarkers Prev, 2020 Sep;29(9):1784-1791.
    PMID: 32546605 DOI: 10.1158/1055-9965.EPI-20-0275
    BACKGROUND: Obesity and diabetes are major modifiable risk factors for pancreatic cancer. Interactions between genetic variants and diabetes/obesity have not previously been comprehensively investigated in pancreatic cancer at the genome-wide level.

    METHODS: We conducted a gene-environment interaction (GxE) analysis including 8,255 cases and 11,900 controls from four pancreatic cancer genome-wide association study (GWAS) datasets (Pancreatic Cancer Cohort Consortium I-III and Pancreatic Cancer Case Control Consortium). Obesity (body mass index ≥30 kg/m2) and diabetes (duration ≥3 years) were the environmental variables of interest. Approximately 870,000 SNPs (minor allele frequency ≥0.005, genotyped in at least one dataset) were analyzed. Case-control (CC), case-only (CO), and joint-effect test methods were used for SNP-level GxE analysis. As a complementary approach, gene-based GxE analysis was also performed. Age, sex, study site, and principal components accounting for population substructure were included as covariates. Meta-analysis was applied to combine individual GWAS summary statistics.

    RESULTS: No genome-wide significant interactions (departures from a log-additive odds model) with diabetes or obesity were detected at the SNP level by the CC or CO approaches. The joint-effect test detected numerous genome-wide significant GxE signals in the GWAS main effects top hit regions, but the significance diminished after adjusting for the GWAS top hits. In the gene-based analysis, a significant interaction of diabetes with variants in the FAM63A (family with sequence similarity 63 member A) gene (significance threshold P < 1.25 × 10-6) was observed in the meta-analysis (P GxE = 1.2 ×10-6, P Joint = 4.2 ×10-7).

    CONCLUSIONS: This analysis did not find significant GxE interactions at the SNP level but found one significant interaction with diabetes at the gene level. A larger sample size might unveil additional genetic factors via GxE scans.

    IMPACT: This study may contribute to discovering the mechanism of diabetes-associated pancreatic cancer.

    Matched MeSH terms: Genome-Wide Association Study/methods*
  18. Amare AT, Schubert KO, Hou L, Clark SR, Papiol S, Cearns M, et al.
    Mol Psychiatry, 2021 Jun;26(6):2457-2470.
    PMID: 32203155 DOI: 10.1038/s41380-020-0689-5
    Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi+Gen) study. Summary statistics from genome-wide association studies in MD (135,458 cases and 344,901 controls) from the Psychiatric Genomics Consortium (PGC) were used for PGS weighting. Response to lithium treatment was defined by continuous scores and categorical outcome (responders versus non-responders) using measurements on the Alda scale. Associations between PGSs of MD and lithium treatment response were assessed using a linear and binary logistic regression modeling for the continuous and categorical outcomes, respectively. The analysis was performed for the entire cohort, and for European and Asian sub-samples. The PGSs for MD were significantly associated with lithium treatment response in multi-ethnic, European or Asian populations, at various p value thresholds. Bipolar patients with a low polygenic load for MD were more likely to respond well to lithium, compared to those patients with high polygenic load [lowest vs highest PGS quartiles, multi-ethnic sample: OR = 1.54 (95% CI: 1.18-2.01) and European sample: OR = 1.75 (95% CI: 1.30-2.36)]. While our analysis in the Asian sample found equivalent effect size in the same direction: OR = 1.71 (95% CI: 0.61-4.90), this was not statistically significant. Using PGS decile comparison, we found a similar trend of association between a high genetic loading for MD and lower response to lithium. Our findings underscore the genetic contribution to lithium response in BD and support the emerging concept of a lithium-responsive biotype in BD.
    Matched MeSH terms: Genome-Wide Association Study
  19. Mullins N, Kang J, Campos AI, Coleman JRI, Edwards AC, Galfalvy H, et al.
    Biol Psychiatry, 2022 Feb 01;91(3):313-327.
    PMID: 34861974 DOI: 10.1016/j.biopsych.2021.05.029
    BACKGROUND: Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders.

    METHODS: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors.

    RESULTS: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged.

    CONCLUSIONS: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.

    Matched MeSH terms: Genome-Wide Association Study
  20. Coleman JRI, Gaspar HA, Bryois J, Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Breen G
    Biol Psychiatry, 2020 Jul 15;88(2):169-184.
    PMID: 31926635 DOI: 10.1016/j.biopsych.2019.10.015
    BACKGROUND: Mood disorders (including major depressive disorder and bipolar disorder) affect 10% to 20% of the population. They range from brief, mild episodes to severe, incapacitating conditions that markedly impact lives. Multiple approaches have shown considerable sharing of risk factors across mood disorders despite their diagnostic distinction.

    METHODS: To clarify the shared molecular genetic basis of major depressive disorder and bipolar disorder and to highlight disorder-specific associations, we meta-analyzed data from the latest Psychiatric Genomics Consortium genome-wide association studies of major depression (including data from 23andMe) and bipolar disorder, and an additional major depressive disorder cohort from UK Biobank (total: 185,285 cases, 439,741 controls; nonoverlapping N = 609,424).

    RESULTS: Seventy-three loci reached genome-wide significance in the meta-analysis, including 15 that are novel for mood disorders. More loci from the Psychiatric Genomics Consortium analysis of major depression than from that for bipolar disorder reached genome-wide significance. Genetic correlations revealed that type 2 bipolar disorder correlates strongly with recurrent and single-episode major depressive disorder. Systems biology analyses highlight both similarities and differences between the mood disorders, particularly in the mouse brain cell types implicated by the expression patterns of associated genes. The mood disorders also differ in their genetic correlation with educational attainment-the relationship is positive in bipolar disorder but negative in major depressive disorder.

    CONCLUSIONS: The mood disorders share several genetic associations, and genetic studies of major depressive disorder and bipolar disorder can be combined effectively to enable the discovery of variants not identified by studying either disorder alone. However, we demonstrate several differences between these disorders. Analyzing subtypes of major depressive disorder and bipolar disorder provides evidence for a genetic mood disorders spectrum.

    Matched MeSH terms: Genome-Wide Association Study
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