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Benstock SE, Weaver K, Hettema JM, Verhulst B. Using Alternative Definitions of Controls to Increase Statistical Power in GWAS. Behav Genet 2024; 54:353-366. [PMID: 38869698 DOI: 10.1007/s10519-024-10187-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 05/29/2024] [Indexed: 06/14/2024]
Abstract
Genome-wide association studies (GWAS) are often underpowered due to small effect sizes of common single nucleotide polymorphisms (SNPs) on phenotypes and extreme multiple testing thresholds. The most common approach for increasing statistical power is to increase sample size. We propose an alternative strategy of redefining case-control outcomes into ordinal case-subthreshold-asymptomatic variables. While maintaining the clinical case threshold, we subdivide controls into two groups: individuals who are symptomatic but do not meet the clinical criteria for diagnosis (subthreshold) and individuals who are effectively asymptomatic. We conducted a simulation study to examine the impact of effect size, minor allele frequency, population prevalence, and the prevalence of the subthreshold group on statistical power to detect genetic associations in three scenarios: a standard case-control, an ordinal, and a case-asymptomatic control analysis. Our results suggest the ordinal model consistently provides the greatest statistical power while the case-control model the least. Power in the case-asymptomatic control model reflects the case-control or ordinal model depending on the population prevalence and size of the subthreshold category. We then analyzed a major depression phenotype from the UK Biobank to corroborate our simulation results. Overall, the ordinal model improves statistical power in GWAS consistent with increasing the sample size by approximately 10%.
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Affiliation(s)
- Sarah E Benstock
- Department of Psychiatry and Behavioral Sciences, Texas A&M University School of Medicine, College Station, TX, USA
| | - Katherine Weaver
- Department of Psychiatry and Behavioral Sciences, Texas A&M University School of Medicine, College Station, TX, USA
| | - John M Hettema
- Department of Psychiatry and Behavioral Sciences, Texas A&M University School of Medicine, College Station, TX, USA
| | - Brad Verhulst
- Department of Psychiatry and Behavioral Sciences, Texas A&M University School of Medicine, College Station, TX, USA.
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2
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Grigoroiu-Serbanescu M, van der Veen T, Bigdeli T, Herms S, Diaconu CC, Neagu AI, Bass N, Thygesen J, Forstner AJ, Nöthen MM, McQuillin A. Schizophrenia polygenic risk scores, clinical variables and genetic pathways as predictors of phenotypic traits of bipolar I disorder. J Affect Disord 2024; 356:507-518. [PMID: 38640977 DOI: 10.1016/j.jad.2024.04.066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Revised: 04/05/2024] [Accepted: 04/16/2024] [Indexed: 04/21/2024]
Abstract
AIM We investigated the predictive value of polygenic risk scores (PRS) derived from the schizophrenia GWAS (Trubetskoy et al., 2022) (SCZ3) for phenotypic traits of bipolar disorder type-I (BP-I) in 1878 BP-I cases and 2751 controls from Romania and UK. METHODS We used PRSice-v2.3.3 and PRS-CS for computing SCZ3-PRS for testing the predictive power of SCZ3-PRS alone and in combination with clinical variables for several BP-I subphenotypes and for pathway analysis. Non-linear predictive models were also used. RESULTS SCZ3-PRS significantly predicted psychosis, incongruent and congruent psychosis, general age-of-onset (AO) of BP-I, AO-depression, AO-Mania, rapid cycling in univariate regressions. A negative correlation between the number of depressive episodes and psychosis, mainly incongruent and an inverse relationship between increased SCZ3-SNP loading and BP-I-rapid cycling were observed. In random forest models comparing the predictive power of SCZ3-PRS alone and in combination with nine clinical variables, the best predictions were provided by combinations of SCZ3-PRS-CS and clinical variables closely followed by models containing only clinical variables. SCZ3-PRS performed worst. Twenty-two significant pathways underlying psychosis were identified. LIMITATIONS The combined RO-UK sample had a certain degree of heterogeneity of the BP-I severity: only the RO sample and partially the UK sample included hospitalized BP-I cases. The hospitalization is an indicator of illness severity. Not all UK subjects had complete subphenotype information. CONCLUSION Our study shows that the SCZ3-PRS have a modest clinical value for predicting phenotypic traits of BP-I. For clinical use their best performance is in combination with clinical variables.
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Affiliation(s)
- Maria Grigoroiu-Serbanescu
- Psychiatric Genetics Research Unit, Alexandru Obregia Clinical Psychiatric Hospital, Bucharest, Romania.
| | - Tracey van der Veen
- Molecular Psychiatry Laboratory, Division of Psychiatry, University College London, London, UK
| | - Tim Bigdeli
- SUNY Downstate Medical Center, Brooklyn, NY, USA
| | - Stefan Herms
- Department of Biomedicine, University of Basel, Basel, Switzerland; Institute of Human Genetics, University of Bonn, School of Medicine, University Hospital Bonn, Germany
| | | | | | - Nicholas Bass
- Molecular Psychiatry Laboratory, Division of Psychiatry, University College London, London, UK
| | - Johan Thygesen
- Molecular Psychiatry Laboratory, Division of Psychiatry, University College London, London, UK; Institute of Health Informatics, University College London, London, UK
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn, School of Medicine, University Hospital Bonn, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine, University Hospital Bonn, Germany
| | - Andrew McQuillin
- Molecular Psychiatry Laboratory, Division of Psychiatry, University College London, London, UK
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3
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Wei W, Ma S, Fu B, Song R, Guo H. Human-specific insights into candidate genes and boosted discoveries of novel loci illuminate roles of neuroglia in reading disorders. GENES, BRAIN, AND BEHAVIOR 2024; 23:e12899. [PMID: 38752599 PMCID: PMC11097622 DOI: 10.1111/gbb.12899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 04/29/2024] [Accepted: 05/02/2024] [Indexed: 05/19/2024]
Abstract
Reading disorders (RD) are human-specific neuropsychological conditions associated with decoding printed words and/or reading comprehension. So far only a handful of candidate genes segregated in families and 42 loci from genome-wide association study (GWAS) have been identified that jointly provided little clues of pathophysiology. Leveraging human-specific genomic information, we critically assessed the RD candidates for the first time and found substantial human-specific features within. The GWAS candidates (i.e., population signals) were distinct from the familial counterparts and were more likely pleiotropic in neuropsychiatric traits and to harbor human-specific regulatory elements (HSREs). Candidate genes associated with human cortical morphology indeed showed human-specific expression in adult brain cortices, particularly in neuroglia likely regulated by HSREs. Expression levels of candidate genes across human brain developmental stages showed a clear pattern of uplifted expression in early brain development crucial to RD development. Following the new insights and loci pleiotropic in cognitive traits, we identified four novel genes from the GWAS sub-significant associations (i.e., FOXO3, MAPT, KMT2E and HTT) and the Semaphorin gene family with functional priors (i.e., SEMA3A, SEMA3E and SEMA5B). These novel genes were related to neuronal plasticity and disorders, mostly conserved the pattern of uplifted expression in early brain development and had evident expression in cortical neuroglial cells. Our findings jointly illuminated the association of RD with neuroglia regulation-an emerging hotspot in studying neurodevelopmental disorders, and highlighted the need of improving RD phenotyping to avoid jeopardizing future genetic studies of RD.
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Affiliation(s)
- Wen‐Hua Wei
- Centre for Biostatistics, Division of Population Health, Health Services Research and Primary CareThe University of ManchesterManchesterUK
| | - Shaowei Ma
- Hebei Key Laboratory of Children's Cognition and Digital Education and School of Foreign LanguagesLangfang Normal UniversityLangfangChina
| | - Bo Fu
- School of Data ScienceFudan UniversityShanghaiChina
| | - Ranran Song
- Department of Maternal and Child Health and MOE (Ministry of Education) Key Laboratory of Environment and Health, School of Public Health, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Hui Guo
- Centre for Biostatistics, Division of Population Health, Health Services Research and Primary CareThe University of ManchesterManchesterUK
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4
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Beck C, Pedersen CB, Plana-Ripoll O, Dalsgaard S, Debost JCP, Laursen TM, Musliner KL, Mortensen PB, Pedersen MG, Petersen LV, Yilmaz Z, McGrath J, Agerbo E. A comprehensive analysis of age of onset and cumulative incidence of mental disorders: A Danish register study. Acta Psychiatr Scand 2024; 149:467-478. [PMID: 38523413 PMCID: PMC11065580 DOI: 10.1111/acps.13682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 03/12/2024] [Accepted: 03/13/2024] [Indexed: 03/26/2024]
Abstract
BACKGROUND The age of onset (AOO), incidence and cumulative incidence of mental disorders are critical epidemiological measures, providing essential insights into the development and course of these disorders across the lifespan. This study aims to provide up-to-date estimates of the AOO, age-specific incidence, and cumulative incidence for a comprehensive range of mental disorders using data from Danish registers. METHODS We conducted a follow-up study encompassing all Danish residents from January 1, 2004, to December 31, 2021, totaling 91,613,465 person-years. Data were sourced from the Danish Psychiatric Central Research Register, identifying individuals treated for various mental disorders in psychiatric hospitals, outpatient departments, and accident/emergency departments, that is, treated in secondary care settings. We investigated specific categories of mental disorders, including substance abuse disorders, schizophrenia, mood disorders, anxiety, eating disorders, borderline personality disorders, intellectual disabilities, pervasive developmental disorders, and behavioral and emotional disorders. Age-sex-specific incidence rates were estimated using Poisson generalized linear models, and cumulative incidence was calculated using Aalen-Johansen's competing risks model. The study provides estimates of AOO, incidence, and cumulative incidence for various mental disorders, including their age and sex distributions. RESULTS The cumulative incidence by age 80 years for any mental disorder was 30.72% (95% confidence interval: 30.62%-30.83%) for males and 34.46% (34.35%-34.57%) for females. The most common types of mental disorders were anxiety-related disorders 16.27% (16.19%-16.36%) for males and 23.39% (23.29%-23.50%) for females, and followed by mood disorder 10.34% (10.27%-10.41%) for males and 16.67% (16.58%-16.77%) for females. For those who develop mental disorder, half will have developed their disorder by approximately age 22 years (median and interquartile range: males 21.37 (11.85-36.00); females 22.55 (16.31-36.08)). CONCLUSIONS Approximately one in three individuals will seek treatment for at least one mental disorder in a secondary care setting by age 80. Given that half of these individuals develop mental disorders before age 22, it is crucial to tailor service planning to meet the specific needs of young individuals. Web-based interactive data-visualization tools are provided for clinical utility.
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Affiliation(s)
- Christoffer Beck
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus V, Denmark
| | - Carsten Bøcker Pedersen
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus V, Denmark
- Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark
- Big Data Centre for Environment and Health, Aarhus University, Aarhus, Denmark
- Hammel Neurorehabilitation Centre and University Research Clinic, Aarhus University, Hammel, Denmark
| | - Oleguer Plana-Ripoll
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus V, Denmark
- Department of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, 8200 Aarhus N, Denmark
| | - Søren Dalsgaard
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus V, Denmark
- Department of Clinical Medicine, University of Copenhagen, 2200 København N. Denmark
- Center for Child and Adolescent Psychiatry, Mental Health Services of the Capital Region, Hellerup, Denmark
| | - Jean-Christophe Philippe Debost
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus V, Denmark
- Aarhus University Hospital Skejby, Department of Affective Disorders, 8200 Aarhus N, Denmark
| | - Thomas Munk Laursen
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus V, Denmark
| | - Katherine Louise Musliner
- Department of Affective Disorders, Aarhus University Hospital - Psychiatry, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Preben Bo Mortensen
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus V, Denmark
- Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark
- Big Data Centre for Environment and Health, Aarhus University, Aarhus, Denmark
| | | | | | - Zeynep Yilmaz
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus V, Denmark
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 65 Solna, Sweden
- Department of Psychiatry, University of North Carolina at Chapel Hill, 27599-7160 Chapel Hill, NC, USA
| | - John McGrath
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus V, Denmark
- Queensland Centre for Mental Health Research, The Park Centre for Mental Health, Brisbane, Queensland 4076, Australia
| | - Esben Agerbo
- National Centre for Register-Based Research, Aarhus University, 8210 Aarhus V, Denmark
- Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark
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5
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Cornwell WK, Levine BD. Unraveling the Unsolved Mysteries of the Athletic Heart. Circulation 2024; 149:1416-1418. [PMID: 38683901 DOI: 10.1161/circulationaha.124.064534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/02/2024]
Affiliation(s)
- William K Cornwell
- Division of Cardiology, Department of Medicine, University of Colorado, Aurora (W.K.C.)
- Clinical Translational Research Center, University of Colorado Anschutz Medical Center, Aurora, CO (W.K.C.)
| | - Benjamin D Levine
- Division of Cardiology, University of Texas Southwestern Medical Center, Dallas (B.D.L.)
- Texas Health Presbyterian Hospital, Institute for Exercise and Environmental Medicine, Dallas (B.D.L.)
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Auwerx C, Jõeloo M, Sadler MC, Tesio N, Ojavee S, Clark CJ, Mägi R, Reymond A, Kutalik Z. Rare copy-number variants as modulators of common disease susceptibility. Genome Med 2024; 16:5. [PMID: 38185688 PMCID: PMC10773105 DOI: 10.1186/s13073-023-01265-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 11/27/2023] [Indexed: 01/09/2024] Open
Abstract
BACKGROUND Copy-number variations (CNVs) have been associated with rare and debilitating genomic disorders (GDs) but their impact on health later in life in the general population remains poorly described. METHODS Assessing four modes of CNV action, we performed genome-wide association scans (GWASs) between the copy-number of CNV-proxy probes and 60 curated ICD-10 based clinical diagnoses in 331,522 unrelated white British UK Biobank (UKBB) participants with replication in the Estonian Biobank. RESULTS We identified 73 signals involving 40 diseases, all of which indicating that CNVs increased disease risk and caused earlier onset. We estimated that 16% of these associations are indirect, acting by increasing body mass index (BMI). Signals mapped to 45 unique, non-overlapping regions, nine of which being linked to known GDs. Number and identity of genes affected by CNVs modulated their pathogenicity, with many associations being supported by colocalization with both common and rare single-nucleotide variant association signals. Dissection of association signals provided insights into the epidemiology of known gene-disease pairs (e.g., deletions in BRCA1 and LDLR increased risk for ovarian cancer and ischemic heart disease, respectively), clarified dosage mechanisms of action (e.g., both increased and decreased dosage of 17q12 impacted renal health), and identified putative causal genes (e.g., ABCC6 for kidney stones). Characterization of the pleiotropic pathological consequences of recurrent CNVs at 15q13, 16p13.11, 16p12.2, and 22q11.2 in adulthood indicated variable expressivity of these regions and the involvement of multiple genes. Finally, we show that while the total burden of rare CNVs-and especially deletions-strongly associated with disease risk, it only accounted for ~ 0.02% of the UKBB disease burden. These associations are mainly driven by CNVs at known GD CNV regions, whose pleiotropic effect on common diseases was broader than anticipated by our CNV-GWAS. CONCLUSIONS Our results shed light on the prominent role of rare CNVs in determining common disease susceptibility within the general population and provide actionable insights for anticipating later-onset comorbidities in carriers of recurrent CNVs.
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Affiliation(s)
- Chiara Auwerx
- Center for Integrative Genomics, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland.
- Department of Computational Biology, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland.
- University Center for Primary Care and Public Health, 1005, Lausanne, Switzerland.
| | - Maarja Jõeloo
- Institute of Molecular and Cell Biology, University of Tartu, 51010, Tartu, Estonia
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia
| | - Marie C Sadler
- Department of Computational Biology, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland
- University Center for Primary Care and Public Health, 1005, Lausanne, Switzerland
| | - Nicolò Tesio
- Center for Integrative Genomics, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland
| | - Sven Ojavee
- Department of Computational Biology, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland
| | - Charlie J Clark
- Center for Integrative Genomics, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia
| | - Alexandre Reymond
- Center for Integrative Genomics, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland.
| | - Zoltán Kutalik
- Department of Computational Biology, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland.
- University Center for Primary Care and Public Health, 1005, Lausanne, Switzerland.
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7
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Dahl A, Thompson M, An U, Krebs M, Appadurai V, Border R, Bacanu SA, Werge T, Flint J, Schork AJ, Sankararaman S, Kendler KS, Cai N. Phenotype integration improves power and preserves specificity in biobank-based genetic studies of major depressive disorder. Nat Genet 2023; 55:2082-2093. [PMID: 37985818 PMCID: PMC10703686 DOI: 10.1038/s41588-023-01559-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 09/18/2023] [Indexed: 11/22/2023]
Abstract
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.
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Affiliation(s)
- Andrew Dahl
- Section of Genetic Medicine, University of Chicago, Chicago, IL, USA.
| | - Michael Thompson
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Ulzee An
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Morten Krebs
- Institute of Biological Psychiatry, Mental Health Center-Sct Hans, Copenhagen University Hospital-Mental Health Services CPH, Copenhagen, Denmark
| | - Vivek Appadurai
- Institute of Biological Psychiatry, Mental Health Center-Sct Hans, Copenhagen University Hospital-Mental Health Services CPH, Copenhagen, Denmark
| | - Richard Border
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Silviu-Alin Bacanu
- Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Center-Sct Hans, Copenhagen University Hospital-Mental Health Services CPH, Copenhagen, Denmark
- Lundbeck Foundation GeoGenetics Centre, Natural History Museum of Denmark, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jonathan Flint
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Andrew J Schork
- Institute of Biological Psychiatry, Mental Health Center-Sct Hans, Copenhagen University Hospital-Mental Health Services CPH, Copenhagen, Denmark
- Neurogenomics Division, The Translational Genomics Research Institute (TGEN), Phoenix, AZ, USA
- Section for Geogenetics, GLOBE Institute, Faculty of Health and Medical Sciences, Copenhagen University, Copenhagen, Denmark
| | - Sriram Sankararaman
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Kenneth S Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Na Cai
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany.
- Computational Health Centre, Helmholtz Zentrum München, Neuherberg, Germany.
- School of Medicine, Technical University of Munich, Munich, Germany.
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8
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Waszczuk MA, Jonas KG, Bornovalova M, Breen G, Bulik CM, Docherty AR, Eley TC, Hettema JM, Kotov R, Krueger RF, Lencz T, Li JJ, Vassos E, Waldman ID. Dimensional and transdiagnostic phenotypes in psychiatric genome-wide association studies. Mol Psychiatry 2023; 28:4943-4953. [PMID: 37402851 PMCID: PMC10764644 DOI: 10.1038/s41380-023-02142-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 05/17/2023] [Accepted: 06/16/2023] [Indexed: 07/06/2023]
Abstract
Genome-wide association studies (GWAS) provide biological insights into disease onset and progression and have potential to produce clinically useful biomarkers. A growing body of GWAS focuses on quantitative and transdiagnostic phenotypic targets, such as symptom severity or biological markers, to enhance gene discovery and the translational utility of genetic findings. The current review discusses such phenotypic approaches in GWAS across major psychiatric disorders. We identify themes and recommendations that emerge from the literature to date, including issues of sample size, reliability, convergent validity, sources of phenotypic information, phenotypes based on biological and behavioral markers such as neuroimaging and chronotype, and longitudinal phenotypes. We also discuss insights from multi-trait methods such as genomic structural equation modelling. These provide insight into how hierarchical 'splitting' and 'lumping' approaches can be applied to both diagnostic and dimensional phenotypes to model clinical heterogeneity and comorbidity. Overall, dimensional and transdiagnostic phenotypes have enhanced gene discovery in many psychiatric conditions and promises to yield fruitful GWAS targets in the years to come.
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Affiliation(s)
- Monika A Waszczuk
- Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL, USA.
| | - Katherine G Jonas
- Department of Psychiatry, Stony Brook University School of Medicine, Stony Brook, NY, USA
| | | | - Gerome Breen
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Cynthia M Bulik
- Department of Psychiatry, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Anna R Docherty
- Huntsman Mental Health Institute, Department of Psychiatry, University of Utah School of Medicine, Salt Lake City, UT, USA
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
| | - Thalia C Eley
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - John M Hettema
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
- Department of Psychiatry, Texas A&M Health Sciences Center, Bryan, TX, USA
| | - Roman Kotov
- Department of Psychiatry, Stony Brook University School of Medicine, Stony Brook, NY, USA
| | - Robert F Krueger
- Psychology Department, University of Minnesota, Minneapolis, MN, USA
| | - Todd Lencz
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, USA
- Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, USA
| | - James J Li
- Department of Psychology, University of Wisconsin, Madison, WI, USA
- Waisman Center, University of Wisconsin, Madison, WI, USA
| | - Evangelos Vassos
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Irwin D Waldman
- Department of Psychology, Emory University, Atlanta, GA, USA
- Center for Computational and Quantitative Genetics, Emory University, Atlanta, GA, USA
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9
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Pedersen EM, Agerbo E, Plana-Ripoll O, Steinbach J, Krebs MD, Hougaard DM, Werge T, Nordentoft M, Børglum AD, Musliner KL, Ganna A, Schork AJ, Mortensen PB, McGrath JJ, Privé F, Vilhjálmsson BJ. ADuLT: An efficient and robust time-to-event GWAS. Nat Commun 2023; 14:5553. [PMID: 37689771 PMCID: PMC10492844 DOI: 10.1038/s41467-023-41210-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 08/28/2023] [Indexed: 09/11/2023] Open
Abstract
Proportional hazards models have been proposed to analyse time-to-event phenotypes in genome-wide association studies (GWAS). However, little is known about the ability of proportional hazards models to identify genetic associations under different generative models and when ascertainment is present. Here we propose the age-dependent liability threshold (ADuLT) model as an alternative to a Cox regression based GWAS, here represented by SPACox. We compare ADuLT, SPACox, and standard case-control GWAS in simulations under two generative models and with varying degrees of ascertainment as well as in the iPSYCH cohort. We find Cox regression GWAS to be underpowered when cases are strongly ascertained (cases are oversampled by a factor 5), regardless of the generative model used. ADuLT is robust to ascertainment in all simulated scenarios. Then, we analyse four psychiatric disorders in iPSYCH, ADHD, Autism, Depression, and Schizophrenia, with a strong case-ascertainment. Across these psychiatric disorders, ADuLT identifies 20 independent genome-wide significant associations, case-control GWAS finds 17, and SPACox finds 8, which is consistent with simulation results. As more genetic data are being linked to electronic health records, robust GWAS methods that can make use of age-of-onset information will help increase power in analyses for common health outcomes.
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Affiliation(s)
- Emil M Pedersen
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark.
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark.
| | - Esben Agerbo
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Centre for Integrated Register-based Research at Aarhus University, Aarhus, Denmark
| | - Oleguer Plana-Ripoll
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
- Department of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, Aarhus, Denmark
| | - Jette Steinbach
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
| | - Morten D Krebs
- Institute of Biological Psychiatry, Mental Health Center - Sct Hans, Copenhagen University Hospital - Mental Health Services CPH, Copenhagen, Denmark
| | - David M Hougaard
- Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Center - Sct Hans, Copenhagen University Hospital - Mental Health Services CPH, Copenhagen, Denmark
- Department of Clinical Sciences, Copenhagen University, Copenhagen, Denmark
- Section for Geogenetics, GLOBE Institute, Faculty of Health and Medical Science, Copenhagen University, Copenhagen, Denmark
| | - Merete Nordentoft
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- CORE- Copenhagen Centre for Research in Mental Health, Mental Health Center-Copenhagen, Copenhagen University Hospital - Mental Health Services CPH, Copenhagen, Denmark
| | - Anders D Børglum
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Department of Biomedicine and iSEQ Centre, Aarhus University, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, CGPM, Aarhus University, Aarhus, Denmark
| | - Katherine L Musliner
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
- Department of Affective Disorders, Aarhus University Hospital-Psychiatry, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Andrea Ganna
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Andrew J Schork
- Institute of Biological Psychiatry, Mental Health Center - Sct Hans, Copenhagen University Hospital - Mental Health Services CPH, Copenhagen, Denmark
- Section for Geogenetics, GLOBE Institute, Faculty of Health and Medical Science, Copenhagen University, Copenhagen, Denmark
- Neurogenomics Division, The Translational Genomics Research Institute (TGEN), Phoenix, AZ, USA
| | - Preben B Mortensen
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
| | - John J McGrath
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
- Queensland Brain Institute, University of Queensland, St Lucia, QLD, Australia
- Queensland Centre for Mental Health Research, The Park Centre for Mental Health, Wacol, QLD, Australia
| | - Florian Privé
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
| | - Bjarni J Vilhjálmsson
- National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark.
- Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark.
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark.
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, the Broad Institute of MIT and Harvard, Massachusetts, USA.
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10
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Ojavee SE, Darrous L, Patxot M, Läll K, Fischer K, Mägi R, Kutalik Z, Robinson MR. Genetic insights into the age-specific biological mechanisms governing human ovarian aging. Am J Hum Genet 2023; 110:1549-1563. [PMID: 37543033 PMCID: PMC10502738 DOI: 10.1016/j.ajhg.2023.07.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 07/07/2023] [Accepted: 07/09/2023] [Indexed: 08/07/2023] Open
Abstract
There is currently little evidence that the genetic basis of human phenotype varies significantly across the lifespan. However, time-to-event phenotypes are understudied and can be thought of as reflecting an underlying hazard, which is unlikely to be constant through life when values take a broad range. Here, we find that 74% of 245 genome-wide significant genetic associations with age at natural menopause (ANM) in the UK Biobank show a form of age-specific effect. Nineteen of these replicated discoveries are identified only by our modeling framework, which determines the time dependency of DNA-variant age-at-onset associations without a significant multiple-testing burden. Across the range of early to late menopause, we find evidence for significantly different underlying biological pathways, changes in the signs of genetic correlations of ANM to health indicators and outcomes, and differences in inferred causal relationships. We find that DNA damage response processes only act to shape ovarian reserve and depletion for women of early ANM. Genetically mediated delays in ANM were associated with increased relative risk of breast cancer and leiomyoma at all ages and with high cholesterol and heart failure for late-ANM women. These findings suggest that a better understanding of the age dependency of genetic risk factor relationships among health indicators and outcomes is achievable through appropriate statistical modeling of large-scale biobank data.
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Affiliation(s)
- Sven E Ojavee
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland.
| | - Liza Darrous
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland; University Center for Primary Care and Public Health, Lausanne, Switzerland
| | - Marion Patxot
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Kristi Läll
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Krista Fischer
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia; Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Zoltan Kutalik
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland; University Center for Primary Care and Public Health, Lausanne, Switzerland
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11
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McGrath JJ, Al-Hamzawi A, Alonso J, Altwaijri Y, Andrade LH, Bromet EJ, Bruffaerts R, de Almeida JMC, Chardoul S, Chiu WT, Degenhardt L, Demler OV, Ferry F, Gureje O, Haro JM, Karam EG, Karam G, Khaled SM, Kovess-Masfety V, Magno M, Medina-Mora ME, Moskalewicz J, Navarro-Mateu F, Nishi D, Plana-Ripoll O, Posada-Villa J, Rapsey C, Sampson NA, Stagnaro JC, Stein DJ, Ten Have M, Torres Y, Vladescu C, Woodruff PW, Zarkov Z, Kessler RC. Age of onset and cumulative risk of mental disorders: a cross-national analysis of population surveys from 29 countries. Lancet Psychiatry 2023; 10:668-681. [PMID: 37531964 PMCID: PMC10529120 DOI: 10.1016/s2215-0366(23)00193-1] [Citation(s) in RCA: 54] [Impact Index Per Article: 54.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 05/18/2023] [Accepted: 05/31/2023] [Indexed: 08/04/2023]
Abstract
BACKGROUND Information on the frequency and timing of mental disorder onsets across the lifespan is of fundamental importance for public health planning. Broad, cross-national estimates of this information from coordinated general population surveys were last updated in 2007. We aimed to provide updated and improved estimates of age-of-onset distributions, lifetime prevalence, and morbid risk. METHODS In this cross-national analysis, we analysed data from respondents aged 18 years or older to the World Mental Health surveys, a coordinated series of cross-sectional, face-to-face community epidemiological surveys administered between 2001 and 2022. In the surveys, the WHO Composite International Diagnostic Interview, a fully structured psychiatric diagnostic interview, was used to assess age of onset, lifetime prevalence, and morbid risk of 13 DSM-IV mental disorders until age 75 years across surveys by sex. We did not assess ethnicity. The surveys were geographically clustered and weighted to adjust for selection probability, and standard errors of incidence rates and cumulative incidence curves were calculated using the jackknife repeated replications simulation method, taking weighting and geographical clustering of data into account. FINDINGS We included 156 331 respondents from 32 surveys in 29 countries, including 12 low-income and middle-income countries and 17 high-income countries, and including 85 308 (54·5%) female respondents and 71 023 (45·4%) male respondents. The lifetime prevalence of any mental disorder was 28·6% (95% CI 27·9-29·2) for male respondents and 29·8% (29·2-30·3) for female respondents. Morbid risk of any mental disorder by age 75 years was 46·4% (44·9-47·8) for male respondents and 53·1% (51·9-54·3) for female respondents. Conditional probabilities of first onset peaked at approximately age 15 years, with a median age of onset of 19 years (IQR 14-32) for male respondents and 20 years (12-36) for female respondents. The two most prevalent disorders were alcohol use disorder and major depressive disorder for male respondents and major depressive disorder and specific phobia for female respondents. INTERPRETATION By age 75 years, approximately half the population can expect to develop one or more of the 13 mental disorders considered in this Article. These disorders typically first emerge in childhood, adolescence, or young adulthood. Services should have the capacity to detect and treat common mental disorders promptly and to optimise care that suits people at these crucial parts of the life course. FUNDING None.
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Affiliation(s)
- John J McGrath
- Queensland Centre for Mental Health Research, Brisbane, QLD, Australia; Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia; National Centre for Register-based Research, Aarhus University, Aarhus, Denmark.
| | - Ali Al-Hamzawi
- College of Medicine, University of Al-Qadisiya, Al Diwaniya, Iraq
| | - Jordi Alonso
- Health Services Research Unit, Hospital del Mar Medical Research Institute, Barcelona, Spain; Department of Medicine and Life Sciences, Pompeu Fabra University, Barcelona, Spain; Centro de Investigación Biomédica en Red en Epidemiología y Salud Pública, Barcelona, Spain
| | - Yasmin Altwaijri
- Epidemiology Section, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Laura H Andrade
- Section of Psychiatric Epidemiology, Institute of Psychiatry, University of São Paulo Medical School, University of São Paulo, São Paulo, Brazil
| | - Evelyn J Bromet
- Department of Psychiatry, Stony Brook University School of Medicine, Stony Brook University, Stony Brook, NY, USA
| | - Ronny Bruffaerts
- Universitair Psychiatrisch Centrum, Katholieke Universiteit Leuven, Leuven, Belgium
| | - José Miguel Caldas de Almeida
- Lisbon Institute of Global Mental Health and Chronic Diseases Research Center, Faculdade de Ciências Médicas, Universidade Nova de Lisboa, Lisbon, Portugal
| | - Stephanie Chardoul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Wai Tat Chiu
- Department of Health Care Policy, Harvard Medical School, Harvard University, Boston, MA, USA
| | - Louisa Degenhardt
- National Drug and Alcohol Research Centre, University of New South Wales, Sydney, NSW, Australia
| | - Olga V Demler
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Harvard University, Boston, MA, USA; Department of Computer Science, Eidgenössische Technische Hochschule Zurich, Zurich, Switzerland
| | - Finola Ferry
- School of Psychology, Ulster University, Belfast, UK
| | - Oye Gureje
- Department of Psychiatry, University College Hospital, Ibadan, Nigeria
| | - Josep Maria Haro
- Research, Teaching and Innovation Unit, Parc Sanitari Sant Joan de Déu, Sant Boi de Llobregat, Barcelona, Spain; Centre for Biomedical Research on Mental Health, Madrid, Spain; Departament de Medicine, Universitat de Barcelona, Barcelona, Spain
| | - Elie G Karam
- Department of Psychiatry and Clinical Psychology, St George Hospital University Medical Center, Beirut, Lebanon; Faculty of Medicine, University of Balamand, Beirut, Lebanon; Institute for Development, Research, Advocacy and Applied Care, Beirut, Lebanon
| | - Georges Karam
- Department of Psychiatry and Clinical Psychology, St George Hospital University Medical Center, Beirut, Lebanon; Faculty of Medicine, University of Balamand, Beirut, Lebanon; Institute for Development, Research, Advocacy and Applied Care, Beirut, Lebanon
| | - Salma M Khaled
- Social and Economic Survey Research Institute, Qatar University, Doha, Qatar
| | | | - Marta Magno
- Unit of Epidemiological and Evaluation Psychiatry, Istituto di Ricovero e Cura a Carattere Scientifico Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | | | | | - Fernando Navarro-Mateu
- Unidad de Docencia, Investigación y Formación en Salud Mental (UDIF-SM), Gerencia Salud Mental, Servicio Murciano de Salud, Murcia, Spain; Murcia Biomedical Research Institute, Murcia, Spain; Centro de Investigación Biomédica en Red Epidemiology and Public Health-Murcia, Murcia, Spain
| | - Daisuke Nishi
- Department of Mental Health, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Oleguer Plana-Ripoll
- National Centre for Register-based Research, Aarhus University, Aarhus, Denmark; Department of Clinical Epidemiology, Aarhus University, Aarhus, Denmark
| | - José Posada-Villa
- Faculty of Social Sciences, Colegio Mayor de Cundinamarca University, Bogota, Colombia
| | - Charlene Rapsey
- Department of Psychological Medicine, University of Otago, Dunedin, New Zealand
| | - Nancy A Sampson
- Department of Health Care Policy, Harvard Medical School, Harvard University, Boston, MA, USA
| | - Juan Carlos Stagnaro
- Departamento de Psiquiatría y Salud Mental, Facultad de Medicina, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Dan J Stein
- Department of Psychiatry and Mental Health and South African Medical Council Research Unit on Risk and Resilience in Mental Disorders, University of Cape Town and Groote Schuur Hospital, Cape Town, South Africa
| | - Margreet Ten Have
- Trimbos-Instituut, Netherlands Institute of Mental Health and Addiction, Utrecht, Netherlands
| | - Yolanda Torres
- Center for Excellence on Research in Mental Health, Instituto de Ciencias de la Salud, Medellín, Colombia
| | - Cristian Vladescu
- National Institute for Health Services Management, Bucharest, Romania
| | - Peter W Woodruff
- Department of Neuroscience, University of Sheffield, Sheffield, UK
| | - Zahari Zarkov
- Department of Mental Health, National Center of Public Health and Analyses, Sofia, Bulgaria
| | - Ronald C Kessler
- Department of Health Care Policy, Harvard Medical School, Harvard University, Boston, MA, USA
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12
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Gusev A. Germline mechanisms of immunotherapy toxicities in the era of genome-wide association studies. Immunol Rev 2023; 318:138-156. [PMID: 37515388 DOI: 10.1111/imr.13253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 06/29/2023] [Indexed: 07/30/2023]
Abstract
Cancer immunotherapy has revolutionized the treatment of advanced cancers and is quickly becoming an option for early-stage disease. By reactivating the host immune system, immunotherapy harnesses patients' innate defenses to eradicate the tumor. By putatively similar mechanisms, immunotherapy can also substantially increase the risk of toxicities or immune-related adverse events (irAEs). Severe irAEs can lead to hospitalization, treatment discontinuation, lifelong immune complications, or even death. Many irAEs present with similar symptoms to heritable autoimmune diseases, suggesting that germline genetics may contribute to their onset. Recently, genome-wide association studies (GWAS) of irAEs have identified common germline associations and putative mechanisms, lending support to this hypothesis. A wide range of well-established GWAS methods can potentially be harnessed to understand the etiology of irAEs specifically and immunotherapy outcomes broadly. This review summarizes current findings regarding germline effects on immunotherapy outcomes and discusses opportunities and challenges for leveraging germline genetics to understand, predict, and treat irAEs.
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Affiliation(s)
- Alexander Gusev
- Division of Population Sciences, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, USA
- Division of Genetics, Brigham & Women's Hospital, Boston, Massachusetts, USA
- The Broad Institute, Cambridge, Massachusetts, USA
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13
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Jespersen A, Yilmaz Z, Vilhjálmsson BJ. Harnessing the Power of Population Cohorts to Study the Relationship Between Endocrine-Metabolic Disorders and Depression. Am J Psychiatry 2022; 179:788-790. [PMID: 36317332 DOI: 10.1176/appi.ajp.20220798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
Affiliation(s)
- Anders Jespersen
- National Center for Register-Based Research (Jespersen, Yilmaz, Vilhjálmsson), Department of Biomedicine (Yilmaz), and Bioinformatics Research Center (Vilhjálmsson), Aarhus University, Aarhus, Denmark; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm (Yilmaz)
| | - Zeynep Yilmaz
- National Center for Register-Based Research (Jespersen, Yilmaz, Vilhjálmsson), Department of Biomedicine (Yilmaz), and Bioinformatics Research Center (Vilhjálmsson), Aarhus University, Aarhus, Denmark; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm (Yilmaz)
| | - Bjarni J Vilhjálmsson
- National Center for Register-Based Research (Jespersen, Yilmaz, Vilhjálmsson), Department of Biomedicine (Yilmaz), and Bioinformatics Research Center (Vilhjálmsson), Aarhus University, Aarhus, Denmark; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm (Yilmaz)
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