| 1. |
- Lawrenson, Kate, et al.
(författare)
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Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus
- 2016
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10-20), ER-negative BC (P=1.1 × 10-13), BRCA1-associated BC (P=7.7 × 10-16) and triple negative BC (P-diff=2 × 10-5). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10-3) and ABHD8 (P<2 × 10-3). Chromosome conformation capture identifies interactions between four candidate SNPs and ABHD8, and luciferase assays indicate six risk alleles increased transactivation of the ADHD8 promoter. Targeted deletion of a region containing risk SNP rs56069439 in a putative enhancer induces ANKLE1 downregulation; and mRNA stability assays indicate functional effects for an ANKLE1 3′-UTR SNP. Altogether, these data suggest that multiple SNPs at 19p13 regulate ABHD8 and perhaps ANKLE1 expression, and indicate common mechanisms underlying breast and ovarian cancer risk.
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| 2. |
- Sumaila, U. Rashid, et al.
(författare)
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WTO must ban harmful fisheries subsidies
- 2021
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 374:6567, s. 544-544
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 3. |
- Baldwin, Jessie R., et al.
(författare)
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Adverse Childhood Experiences and Mental Health : A Genetically Informed Study
- 2021
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Ingår i: Behavior Genetics. - : Springer. - 0001-8244 .- 1573-3297. ; 51:6, s. 691-692
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Children exposed to adverse childhood experiences (ACEs) have an elevated risk of mental health problems, but it is unclear whether these associations reflect genetic confounding. We tested (1) whether children with genetic liability to psychopathology are more likely to experience ACEs, and (2) the extent to which the associations between ACEs and mental health are genetically confounded. Par-ticipants were 6411 children from the Avon Longitudinal Study of Parents and Children (ALSPAC). ACEs (including maltreatment, domestic violence, and parental psychopathology, substance abuse, criminality, and separation) were prospectively measured through parent reports at multiple assessments between birth and age 9. Internalizing and externalizing problems at age 9 were assessed through parent reports on the Development and Wellbeing Assessment. We derived polygenic scores for a range of psychiatric disorders. Children with greater genetic liability to psychopathology had a small elevation in risk of ACEs (pooled odds ratio = 1.05, 95% CI 1.01–1.09). Measured polygenic scores accounted for a very small proportion of the associations between ACEs with internalizing problems (pooled average across ACEs = 3.6%) and externalizing problems (pooled average = 4.8%). However, latent polygenic scores capturing SNP heritability in mental health outcomes explained a larger proportion of the associations between ACEs with internalizing problems (pooled average = 63%) and externalizing problems (pooled average = 17%). Risk of mental health problems in children exposed to ACEs is partly, but not completely driven by pre-existing genetic liability to psychopathology. Assuming the absence of nongenetic confounding, these findings are consistent with a partly causal effect of ACEs on mental health.
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| 4. |
- Couch, Fergus J., et al.
(författare)
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Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer
- 2016
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Ingår i: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 7:11375, s. 1-13
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Tidskriftsartikel (refereegranskat)abstract
- Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P<5 x 10(-8)) with oestrogen receptor (ER)-negative breast cancer and BRCA1-associated breast cancer risk. In this study, to identify new ER-negative susceptibility loci, we performed a meta-analysis of 11 genome-wide association studies (GWAS) consisting of 4,939 ER-negative cases and 14,352 controls, combined with 7,333 ER-negative cases and 42,468 controls and 15,252 BRCA1 mutation carriers genotyped on the iCOGS array. We identify four previously unidentified loci including two loci at 13q22 near KLF5, a 2p23.2 locus near WDR43 and a 2q33 locus near PPIL3 that display genome-wide significant associations with ER-negative breast cancer. In addition, 19 known breast cancer risk loci have genome-wide significant associations and 40 had moderate associations (P<0.05) with ER-negative disease. Using functional and eQTL studies we implicate TRMT61B and WDR43 at 2p23.2 and PPIL3 at 2q33 in ER-negative breast cancer aetiology. All ER-negative loci combined account for similar to 11% of familial relative risk for ER-negative disease and may contribute to improved ER-negative and BRCA1 breast cancer risk prediction.
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| 5. |
- Grimes, Poppy, et al.
(författare)
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UNVEILING GENETIC ARCHITECTURES FOR STRATIFYING TRAJECTORIES OF ADOLESCENT DEPRESSION
- 2023
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Ingår i: European Neuropsychopharmacology. - : Elsevier. - 0924-977X .- 1873-7862. ; 75:Suppl. 1, s. S127-S127
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Background: Adolescent-onset depression is characterised by high levels of inter-individual variability and genetic heritability. Investigating the genetic factors that underlie trajectories of depression is crucial to enhancing mechanistic understanding of the onset, persistence and severity of adolescent depression. However, predicting trajectories from complex and heterogeneous genetic architectures in psychopathology poses challenges due to the high genetic correlation among traits. It remains unclear whether multi-trait models provide a superior prediction of depression trajectories compared to univariate models focused solely on depression. Addressing this question is important for effective stratification and targeted treatments.Methods: To validate depression trajectories during adolescence, we conducted growth mixture modelling in two longitudinal cohorts (ABCD and ALSPAC; total N=20,509). We then computed polygenic risk scores for seven traits: major depressive disorder (MDD), anxiety, neuroticism, schizophrenia, bipolar disorder, attention-deficit-hyperactivity disorder (ADHD), and autism for participants with European ancestry. We also generated MDD scores for individuals of African, East Asian, and Hispanic ancestries in ABCD. Using genomic structural equation modelling, we compared three multi-trait factor models (common, correlated, hierarchical) to assess the relationships among the seven traits. To generate multi-trait risk scores from these models in our target cohorts, we conducted multivariate genome-wide association analysis to determine the effects of single nucleotide polymorphisms on genetic latent p-factors. Finally, we examined the association between all polygenic risk scores for univariate traits and multi-trait models with depression trajectories.Results: Four distinct trajectories were replicated across two cohorts with partial age-range overlap encompassing adolescents from two generations. Trajectories included stable low, adolescent acute, increasing and decreasing. The hierarchical factor model was the best fit for multi-trait genetic information and was most predictive of adolescent acute trajectories (odds ratio [OR], 1.46; 95% CI, 1.27-1.68), with increasing and decreasing showing comparable risk (OR, 1.32; 95% CI, 1.16-1.50). Multi-trait models showed a similar genetic risk for depression trajectory as MDD-only risk across trajectories. Anxiety was associated with the adolescent acute trajectories (OR, 1.27; 95% CI, 1.10-1.45). Psychotic conditions were associated with later-onset depression patterns and ADHD with earlier-onset, aligning with the developmental timelines of these respective conditions.Discussion: The investigated genetic traits collectively contribute to diverse longitudinal patterns of depression, varying in severity, onset, and duration. A hierarchical factor model of multivariate genetic psychopathology demonstrated a comparable prediction of genetic risk to univariate depression scores for stratifying longitudinal depression in adolescence. It is important to acknowledge the genetic influence of multiple conditions on depression outcomes, particularly at different stages of vulnerability. Taking into account detailed and integrated genetic information will be valuable in effectively stratifying trajectories across adolescence and mental health conditions.
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| 6. |
- Grimes, Poppy Z., et al.
(författare)
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Genetic Architectures of Adolescent Depression Trajectories in 2 Longitudinal Population Cohorts
- 2024
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Ingår i: JAMA psychiatry. - : American Medical Association (AMA). - 2168-6238 .- 2168-622X.
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Tidskriftsartikel (refereegranskat)abstract
- IMPORTANCE: Adolescent depression is characterized by diverse symptom trajectories over time and has a strong genetic influence. Research has determined genetic overlap between depression and other psychiatric conditions; investigating the shared genetic architecture of heterogeneous depression trajectories is crucial for understanding disease etiology, prediction, and early intervention.OBJECTIVE: To investigate univariate and multivariate genetic risk for adolescent depression trajectories and assess generalizability across ancestries.DESIGN, SETTING, AND PARTICIPANTS: This cohort study entailed longitudinal growth modeling followed by polygenic risk score (PRS) association testing for individual and multitrait genetic models. Two longitudinal cohorts from the US and UK were used: the Adolescent Brain and Cognitive Development (ABCD; N = 11 876) study and the Avon Longitudinal Study of Parents and Children (ALSPAC; N = 8787) study. Included were adolescents with genetic information and depression measures at up to 8 and 4 occasions, respectively. Study data were analyzed January to July 2023.MAIN OUTCOMES AND MEASURES: Trajectories were derived from growth mixture modeling of longitudinal depression symptoms. PRSs were computed for depression, anxiety, neuroticism, bipolar disorder, schizophrenia, attention-deficit/hyperactivity disorder, and autism in European ancestry. Genomic structural equation modeling was used to build multitrait genetic models of psychopathology followed by multitrait PRS. Depression PRSs were computed in African, East Asian, and Hispanic ancestries in the ABCD cohort only. Association testing was performed between all PRSs and trajectories for both cohorts.RESULTS: A total sample size of 14 112 adolescents (at baseline: mean [SD] age, 10.5 [0.5] years; 7269 male sex [52%]) from both cohorts were included in this analysis. Distinct depression trajectories (stable low, adolescent persistent, increasing, and decreasing) were replicated in the ALSPAC cohort (6096 participants; 3091 female [51%]) and ABCD cohort (8016 participants; 4274 male [53%]) between ages 10 and 17 years. Most univariate PRSs showed significant uniform associations with persistent trajectories, but fewer were significantly associated with intermediate (increasing and decreasing) trajectories. Multitrait PRSs-derived from a hierarchical factor model-showed the strongest associations for persistent trajectories (ABCD cohort: OR, 1.46; 95% CI, 1.26-1.68; ALSPAC cohort: OR, 1.34; 95% CI, 1.20-1.49), surpassing the effect size of univariate PRS in both cohorts. Multitrait PRSs were associated with intermediate trajectories but to a lesser extent (ABCD cohort: hierarchical increasing, OR, 1.27; 95% CI, 1.13-1.43; decreasing, OR, 1.23; 95% CI, 1.09-1.40; ALSPAC cohort: hierarchical increasing, OR, 1.16; 95% CI, 1.04-1.28; decreasing, OR, 1.32; 95% CI, 1.18-1.47). Transancestral genetic risk for depression showed no evidence for association with trajectories.CONCLUSIONS AND RELEVANCE: Results of this cohort study revealed a high multitrait genetic loading of persistent symptom trajectories, consistent across traits and cohorts. Variability in univariate genetic association with intermediate trajectories may stem from environmental factors. Multitrait genetics may strengthen depression prediction models, but more diverse data are needed for generalizability.
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| 7. |
- Hollis, Ben, et al.
(författare)
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Genomic analysis of male puberty timing highlights shared genetic basis with hair colour and lifespan.
- 2020
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- The timing of puberty is highly variable and is associated with long-term health outcomes. To date, understanding of the genetic control of puberty timing is based largely on studies in women. Here, we report a multi-trait genome-wide association study for male puberty timing with an effective sample size of 205,354 men. We find moderately strong genomic correlation in puberty timing between sexes (rg = 0.68) and identify 76 independent signals for male puberty timing. Implicated mechanisms include an unexpected link between puberty timing and natural hair colour, possibly reflecting common effects of pituitary hormones on puberty and pigmentation. Earlier male puberty timing is genetically correlated with several adverse health outcomes and Mendelian randomization analyses show a genetic association between male puberty timing and shorter lifespan. These findings highlight the relationships between puberty timing and health outcomes, and demonstrate the value of genetic studies of puberty timing in both sexes.
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| 8. |
- Khalili, Bita, et al.
(författare)
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Associations between common genetic variants and income provide insights about the socioeconomic health gradient
- 2024
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- We conducted a genome-wide association study (GWAS) on income among individuals of European descent and leveraged the results to investigate the socio-economic health gradient (N=668,288). We found 162 genomic loci associated with a common genetic factor underlying various income measures, all with small effect sizes. Our GWAS-derived polygenic index captures 1 - 4% of income variance, with only one-fourth attributed to direct genetic effects. A phenome-wide association study using this polygenic index showed reduced risks for a broad spectrum of diseases, including hypertension, obesity, type 2 diabetes, coronary atherosclerosis, depression, asthma, and back pain. The income factor showed a substantial genetic correlation (0.92, s.e. = .006) with educational attainment (EA). Accounting for EA's genetic overlap with income revealed that the remaining genetic signal for higher income related to better mental health but reduced physical health benefits and increased participation in risky behaviours such as drinking and smoking.
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| 9. |
- Zeng, Chenjie, et al.
(författare)
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Identification of independent association signals and putative functional variants for breast cancer risk through fine-scale mapping of the 12p11 locus
- 2016
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Ingår i: Breast Cancer Research. - : Springer Science and Business Media LLC. - 1465-5411 .- 1465-542X. ; 18
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Tidskriftsartikel (refereegranskat)abstract
- Background: Multiple recent genome-wide association studies (GWAS) have identified a single nucleotide polymorphism (SNP), rs10771399, at 12p11 that is associated with breast cancer risk. Method: We performed a fine-scale mapping study of a 700 kb region including 441 genotyped and more than 1300 imputed genetic variants in 48,155 cases and 43,612 controls of European descent, 6269 cases and 6624 controls of East Asian descent and 1116 cases and 932 controls of African descent in the Breast Cancer Association Consortium (BCAC; http://bcac.ccge.medschl.cam.ac.uk/), and in 15,252 BRCA1 mutation carriers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Stepwise regression analyses were performed to identify independent association signals. Data from the Encyclopedia of DNA Elements project (ENCODE) and the Cancer Genome Atlas (TCGA) were used for functional annotation. Results: Analysis of data from European descendants found evidence for four independent association signals at 12p11, represented by rs7297051 (odds ratio (OR) = 1.09, 95 % confidence interval (CI) = 1.06-1.12; P = 3 x 10(-9)), rs805510 (OR = 1.08, 95 % CI = 1.04-1.12, P = 2 x 10(-5)), and rs1871152 (OR = 1.04, 95 % CI = 1.02-1.06; P = 2 x 10(-4)) identified in the general populations, and rs113824616 (P = 7 x 10(-5)) identified in the meta-analysis of BCAC ER-negative cases and BRCA1 mutation carriers. SNPs rs7297051, rs805510 and rs113824616 were also associated with breast cancer risk at P < 0.05 in East Asians, but none of the associations were statistically significant in African descendants. Multiple candidate functional variants are located in putative enhancer sequences. Chromatin interaction data suggested that PTHLH was the likely target gene of these enhancers. Of the six variants with the strongest evidence of potential functionality, rs11049453 was statistically significantly associated with the expression of PTHLH and its nearby gene CCDC91 at P < 0.05. Conclusion: This study identified four independent association signals at 12p11 and revealed potentially functional variants, providing additional insights into the underlying biological mechanism(s) for the association observed between variants at 12p11 and breast cancer risk.
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