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Journal of Medical Genetics Nov 2023Polygenic risk score (PRS), calculated based on genome-wide association studies (GWASs), can improve breast cancer (BC) risk assessment. To date, most BC GWASs have been...
BACKGROUND
Polygenic risk score (PRS), calculated based on genome-wide association studies (GWASs), can improve breast cancer (BC) risk assessment. To date, most BC GWASs have been performed in individuals of European (EUR) ancestry, and the generalisation of EUR-based PRS to other populations is a major challenge. In this study, we examined the performance of EUR-based BC PRS models in Ashkenazi Jewish (AJ) women.
METHODS
We generated PRSs based on data on EUR women from the Breast Cancer Association Consortium (BCAC). We tested the performance of the PRSs in a cohort of 2161 AJ women from Israel (1437 cases and 724 controls) from BCAC (BCAC cohort from Israel (BCAC-IL)). In addition, we tested the performance of these EUR-based BC PRSs, as well as the established 313-SNP EUR BC PRS, in an independent cohort of 181 AJ women from Hadassah Medical Center (HMC) in Israel.
RESULTS
In the BCAC-IL cohort, the highest OR per 1 SD was 1.56 (±0.09). The OR for AJ women at the top 10% of the PRS distribution compared with the middle quintile was 2.10 (±0.24). In the HMC cohort, the OR per 1 SD of the EUR-based PRS that performed best in the BCAC-IL cohort was 1.58±0.27. The OR per 1 SD of the commonly used 313-SNP BC PRS was 1.64 (±0.28).
CONCLUSIONS
Extant EUR GWAS data can be used for generating PRSs that identify AJ women with markedly elevated risk of BC and therefore hold promise for improving BC risk assessment in AJ women.
Topics: Humans; Female; Breast Neoplasms; Genome-Wide Association Study; Jews; Israel; Genetic Predisposition to Disease; Risk Factors; Multifactorial Inheritance; Transcription Factors
PubMed: 37451831
DOI: 10.1136/jmg-2023-109185 -
PLoS Computational Biology Nov 2023Phenotype prediction is at the center of many questions in biology. Prediction is often achieved by determining statistical associations between genetic and phenotypic...
Phenotype prediction is at the center of many questions in biology. Prediction is often achieved by determining statistical associations between genetic and phenotypic variation, ignoring the exact processes that cause the phenotype. Here, we present a framework based on genome-scale metabolic reconstructions to reveal the mechanisms behind the associations. We calculated a polygenic score (PGS) that identifies a set of enzymes as predictors of growth, the phenotype. This set arises from the synergy of the functional mode of metabolism in a particular setting and its evolutionary history, and is suitable to infer the phenotype across a variety of conditions. We also find that there is optimal genetic variation for predictability and demonstrate how the linear PGS can still explain phenotypes generated by the underlying nonlinear biochemistry. Therefore, the explicit model interprets the black box statistical associations of the genotype-to-phenotype map and helps to discover what limits the prediction in metabolism.
Topics: Genotype; Phenotype; Genome; Biological Evolution; Multifactorial Inheritance
PubMed: 37948461
DOI: 10.1371/journal.pcbi.1011631 -
Journal of Ovarian Research Feb 2024The etiology of premature ovarian insufficiency, that is, the loss of ovarian activity before 40 years of age, is complex. Studies suggest that genetic factors are... (Observational Study)
Observational Study
BACKGROUND
The etiology of premature ovarian insufficiency, that is, the loss of ovarian activity before 40 years of age, is complex. Studies suggest that genetic factors are involved in 20-25% of cases. The aim of this study was to explore the oligogenic basis of premature ovarian insufficiency.
RESULTS
Whole-exome sequencing of 93 patients with POI and whole-genome sequencing of 465 controls were performed. In the gene-burden analysis, multiple genetic variants, including those associated with DNA damage repair and meiosis, were more common in participants with premature ovarian insufficiency than in controls. The ORVAL-platform analysis confirmed the pathogenicity of the RAD52 and MSH6 combination.
CONCLUSIONS
The results of this study indicate that oligogenic inheritance is an important cause of premature ovarian insufficiency and provide insights into the biological mechanisms underlying premature ovarian insufficiency.
Topics: Female; Humans; Primary Ovarian Insufficiency; Menopause, Premature
PubMed: 38310280
DOI: 10.1186/s13048-024-01351-1 -
Frontiers in Endocrinology 2023Very tall people attract much attention and represent a clinically and genetically heterogenous group of individuals. Identifying the genetic etiology can provide...
Very tall people attract much attention and represent a clinically and genetically heterogenous group of individuals. Identifying the genetic etiology can provide important insights into the molecular mechanisms regulating linear growth. We studied a three-generation pedigree with five isolated (non-syndromic) tall members and one individual with normal stature by whole exome sequencing; the tallest man had a height of 211 cm. Six heterozygous gene variants predicted as damaging were shared among the four genetically related tall individuals and not present in a family member with normal height. To gain insight into the putative role of these candidate genes in bone growth, we assessed the transcriptome of murine growth plate by microarray and RNA Seq. Two () of the six genes were well-expressed in the growth plate. (-value 1.91E-62) as well as (-value of 2.98E-06) showed significant downregulation of gene expression between the proliferative and hypertrophic zone, suggesting that these genes may be involved in the regulation of chondrocyte proliferation and/or hypertrophic differentiation. and have also significantly associated with height in GWAS studies. Pathway and network analysis indicated functional connections between , and and previously associated (tall) stature genes. Knockout of the all-trans retinoic acid responsive gene, neuron navigator 2 , in supports its functional role as a growth promotor. Collectively, our data expand the spectrum of genes with a putative role in tall stature phenotypes and, among other genes, highlight as an interesting gene to this phenotype.
Topics: Animals; Humans; Male; Mice; Bone Development; Growth Plate; Tretinoin; Body Height; DNA Helicases
PubMed: 38152138
DOI: 10.3389/fendo.2023.1258313 -
Molecular Psychiatry Oct 2023Deficits in effective executive function, including inhibitory control are associated with risk for a number of psychiatric disorders and significantly impact everyday... (Meta-Analysis)
Meta-Analysis
Deficits in effective executive function, including inhibitory control are associated with risk for a number of psychiatric disorders and significantly impact everyday functioning. These complex traits have been proposed to serve as endophenotypes, however, their genetic architecture is not yet well understood. To identify the common genetic variation associated with inhibitory control in the general population we performed the first trans-ancestry genome wide association study (GWAS) combining data across 8 sites and four ancestries (N = 14,877) using cognitive traits derived from the stop-signal task, namely - go reaction time (GoRT), go reaction time variability (GoRT SD) and stop signal reaction time (SSRT). Although we did not identify genome wide significant associations for any of the three traits, GoRT SD and SSRT demonstrated significant and similar SNP heritability of 8.2%, indicative of an influence of genetic factors. Power analyses demonstrated that the number of common causal variants contributing to the heritability of these phenotypes is relatively high and larger sample sizes are necessary to robustly identify associations. In Europeans, the polygenic risk for ADHD was significantly associated with GoRT SD and the polygenic risk for schizophrenia was associated with GoRT, while in East Asians polygenic risk for schizophrenia was associated with SSRT. These results support the potential of executive function measures as endophenotypes of neuropsychiatric disorders. Together these findings provide the first evidence indicating the influence of common genetic variation in the genetic architecture of inhibitory control quantified using objective behavioural traits derived from the stop-signal task.
Topics: Humans; Genome-Wide Association Study; Schizophrenia; Executive Function; Multifactorial Inheritance; Endophenotypes; Polymorphism, Single Nucleotide; Genetic Predisposition to Disease
PubMed: 37500827
DOI: 10.1038/s41380-023-02187-9 -
Communications Biology Oct 2023Schizophrenia may represent a trade-off in the evolution of human-specific ontogenetic mechanisms that guide neurodevelopment. Human Accelerated Regions (HARs) are...
Schizophrenia may represent a trade-off in the evolution of human-specific ontogenetic mechanisms that guide neurodevelopment. Human Accelerated Regions (HARs) are evolutionary markers functioning as neurodevelopmental transcription enhancers that have been associated with brain configuration, neural information processing, and schizophrenia risk. Here, we have investigated the influence of HARs' polygenic load on neuroanatomical measures through a case-control approach (128 patients with schizophrenia and 115 controls). To this end, we have calculated the global schizophrenia Polygenic Risk Score (Global PRS) and that specific to HARs (HARs PRS). We have also estimated the polygenic burden restricted to the HARs linked to transcriptional regulatory elements active in the foetal brain (FB-HARs PRS) and the adult brain (AB-HARs PRS). We have explored the main effects of the PRSs and the PRSs x diagnosis interactions on brain regional cortical thickness (CT) and surface area (SA). The results indicate that a higher FB-HARs PRS is associated with patients' lower SA in the lateral orbitofrontal cortex, the superior temporal cortex, the pars triangularis and the paracentral lobule. While noHARs-derived PRSs show an effect on the risk, our neuroanatomical findings suggest that the human-specific transcriptional regulation during the prenatal period underlies SA variability, highlighting the role of these evolutionary markers in the schizophrenia genomic architecture.
Topics: Adult; Humans; Schizophrenia; Brain; Prefrontal Cortex; Multifactorial Inheritance; Gene Expression Regulation
PubMed: 37833414
DOI: 10.1038/s42003-023-05356-2 -
Nature Genetics Dec 2023Biobanks often contain several phenotypes relevant to diseases such as major depressive disorder (MDD), with partly distinct genetic architectures. Researchers face...
Biobanks often contain several phenotypes relevant to diseases such as major depressive disorder (MDD), with partly distinct genetic architectures. Researchers face complex tradeoffs between shallow (large sample size, low specificity/sensitivity) and deep (small sample size, high specificity/sensitivity) phenotypes, and the optimal choices are often unclear. Here we propose to integrate these phenotypes to combine the benefits of each. We use phenotype imputation to integrate information across hundreds of MDD-relevant phenotypes, which significantly increases genome-wide association study (GWAS) power and polygenic risk score (PRS) prediction accuracy of the deepest available MDD phenotype in UK Biobank, LifetimeMDD. We demonstrate that imputation preserves specificity in its genetic architecture using a novel PRS-based pleiotropy metric. We further find that integration via summary statistics also enhances GWAS power and PRS predictions, but can introduce nonspecific genetic effects depending on input. Our work provides a simple and scalable approach to improve genetic studies in large biobanks by integrating shallow and deep phenotypes.
Topics: Humans; Depressive Disorder, Major; Genetic Predisposition to Disease; Biological Specimen Banks; Genome-Wide Association Study; Multifactorial Inheritance; Phenotype; Polymorphism, Single Nucleotide
PubMed: 37985818
DOI: 10.1038/s41588-023-01559-9 -
Cell Genomics Jan 2024Chronic kidney disease is a leading cause of death and disability globally and impacts individuals of African ancestry (AFR) or with ancestry in the Americas (AMS) who... (Meta-Analysis)
Meta-Analysis
Chronic kidney disease is a leading cause of death and disability globally and impacts individuals of African ancestry (AFR) or with ancestry in the Americas (AMS) who are under-represented in genome-wide association studies (GWASs) of kidney function. To address this bias, we conducted a large meta-analysis of GWASs of estimated glomerular filtration rate (eGFR) in 145,732 AFR and AMS individuals. We identified 41 loci at genome-wide significance (p < 5 × 10), of which two have not been previously reported in any ancestry group. We integrated fine-mapped loci with epigenomic and transcriptomic resources to highlight potential effector genes relevant to kidney physiology and disease, and reveal key regulatory elements and pathways involved in renal function and development. We demonstrate the varying but increased predictive power offered by a multi-ancestry polygenic score for eGFR and highlight the importance of population diversity in GWASs and multi-omics resources to enhance opportunities for clinical translation for all.
Topics: Humans; Genome-Wide Association Study; Renal Insufficiency, Chronic; Glomerular Filtration Rate; Multifactorial Inheritance; Kidney
PubMed: 38190104
DOI: 10.1016/j.xgen.2023.100468 -
JAMA Psychiatry Aug 2023Modeling genetic nurture (ie, the effects of parental genotypes through influences on the environment experienced by their children) is essential to accurately...
IMPORTANCE
Modeling genetic nurture (ie, the effects of parental genotypes through influences on the environment experienced by their children) is essential to accurately disentangle genetic and environmental influences on phenotypic variance. However, these influences are often ignored in both epidemiologic and genetic studies of depression.
OBJECTIVE
To estimate the association of genetic nurture with depression and neuroticism.
DESIGN, SETTING, AND PARTICIPANTS
This cross-sectional study jointly modeled parental and offspring polygenic scores (PGSs) across 9 traits to test for the association of genetic nurture with lifetime broad depression and neuroticism using data from nuclear families in the UK Biobank, with data collected between 2006 and 2019. A broad depression phenotype was measured in 38 702 offspring from 20 905 independent nuclear families, with most of these participants also reporting neuroticism scores. Parental genotypes were imputed from sibships or parent-offspring duos and used to calculate parental PGSs. Data were analyzed between March 2021 and January 2023.
MAIN OUTCOMES AND MEASURES
Estimates of genetic nurture and direct genetic regression coefficients on broad depression and neuroticism.
RESULTS
This study of 38 702 offspring with data on broad depression (mean [SD] age, 55.5 [8.2] years at study entry; 58% female) found limited preliminary evidence for a statistically significant association of genetic nurture with lifetime depression and neuroticism in adults. The estimated regression coefficient of the parental depression PGS on offspring neuroticism (β = 0.04, SE = 0.02, P = 6.63 × 10-3) was estimated to be approximately two-thirds (66%) that of the offspring's depression PGS (β = 0.06, SE = 0.01, P = 6.13 × 10-11). Evidence for an association between parental cannabis use disorder PGS and offspring depression was also found (β = 0.08, SE = 0.03, P = .02), which was estimated to be 2 times greater than the association between the offspring's cannabis use disorder PGS and their own depression status (β = 0.04, SE = 0.02, P = .07).
CONCLUSIONS AND RELEVANCE
The results of this cross-sectional study highlight the potential for genetic nurture to bias results from epidemiologic and genetic studies on depression or neuroticism and, with further replication and larger samples, identify potential avenues for future prevention and intervention efforts.
Topics: Humans; Female; Male; Neuroticism; Depression; Cross-Sectional Studies; Marijuana Abuse; Genotype; Multifactorial Inheritance; Genome-Wide Association Study
PubMed: 37285136
DOI: 10.1001/jamapsychiatry.2023.1544 -
Biological Psychiatry Jul 2023The clinically heterogeneous presentation of schizophrenia is compounded by the heterogeneity of risk factors and neurobiological correlates of the disorder. Genome-wide... (Review)
Review
The clinically heterogeneous presentation of schizophrenia is compounded by the heterogeneity of risk factors and neurobiological correlates of the disorder. Genome-wide association studies in schizophrenia have uncovered a remarkably high number of genetic variants, but the biological pathways they impact upon remain largely unidentified. Among the diverse methodological approaches employed to provide a more granular understanding of genetic risk for schizophrenia, the use of biological labels, such as gene ontologies, regulome approaches, and gene coexpression have all provided novel perspectives into how genetic risk translates into the neurobiology of schizophrenia. Here, we review the salient aspects of parsing polygenic risk for schizophrenia into biological pathways. We argue that parsed scores, compared to standard polygenic risk scores, may afford a more biologically plausible and accurate physiological modeling of the different dimensions involved in translating genetic risk into brain mechanisms, including multiple brain regions, cell types, and maturation stages. We discuss caveats, opportunities, and pitfalls inherent in the parsed risk approach.
Topics: Humans; Genome-Wide Association Study; Schizophrenia; Brain; Risk Factors; Multifactorial Inheritance; Genetic Predisposition to Disease
PubMed: 36740470
DOI: 10.1016/j.biopsych.2022.10.009