Jonathan L. Hess, Manuel Mattheisen, the Schizophrenia Working Group of the Psychiatric Genomics Consortium, Tiffany A. Greenwood, Ming T. Tsuang, Howard J. Edenberg, Peter Holmans, Stephen V. Faraone, Stephen J. Glatt
Identifying heritable factors that moderate the genetic risk for schizophrenia (SCZ) could help clarify why some individuals remain unaffected despite having relatively high genetic liability. Previously, we developed a framework to mine genome-wide association (GWAS) data for common genetic variants that protect high-risk unaffected individuals from SCZ, leading to derivation of the first-ever “polygenic resilience score” for SCZ (resilient controls n = 3786; polygenic risk score-matched SCZ cases n = 18,619). Here, we performed a replication study to verify the moderating effect of our polygenic resilience score on SCZ risk (OR = 1.09, p = 4.03 × 10−5) using newly released GWAS data from 23 independent case–control studies collated by the Psychiatric Genomics Consortium (PGC) (resilient controls n = 2821; polygenic risk score-matched SCZ cases n = 5150). Additionally, we sought to optimize our polygenic resilience-scoring formula to improve subsequent modeling of resilience to SCZ and other complex disorders. We found significant replication of the polygenic resilience score, and found that strict pruning of SNPs based on linkage disequilibrium to known risk SNPs and their linked loci optimizes the performance of the polygenic resilience score.
{"title":"A polygenic resilience score moderates the genetic risk for schizophrenia: Replication in 18,090 cases and 28,114 controls from the Psychiatric Genomics Consortium","authors":"Jonathan L. Hess, Manuel Mattheisen, the Schizophrenia Working Group of the Psychiatric Genomics Consortium, Tiffany A. Greenwood, Ming T. Tsuang, Howard J. Edenberg, Peter Holmans, Stephen V. Faraone, Stephen J. Glatt","doi":"10.1002/ajmg.b.32957","DOIUrl":"10.1002/ajmg.b.32957","url":null,"abstract":"<p>Identifying heritable factors that moderate the genetic risk for schizophrenia (SCZ) could help clarify why some individuals remain unaffected despite having relatively high genetic liability. Previously, we developed a framework to mine genome-wide association (GWAS) data for common genetic variants that protect high-risk unaffected individuals from SCZ, leading to derivation of the first-ever “polygenic resilience score” for SCZ (resilient controls <i>n</i> = 3786; polygenic risk score-matched SCZ cases <i>n</i> = 18,619). Here, we performed a replication study to verify the moderating effect of our polygenic resilience score on SCZ risk (OR = 1.09, <i>p</i> = 4.03 × 10<sup>−5</sup>) using newly released GWAS data from 23 independent case–control studies collated by the Psychiatric Genomics Consortium (PGC) (resilient controls <i>n</i> = 2821; polygenic risk score-matched SCZ cases <i>n</i> = 5150). Additionally, we sought to optimize our polygenic resilience-scoring formula to improve subsequent modeling of resilience to SCZ and other complex disorders. We found significant replication of the polygenic resilience score, and found that strict pruning of SNPs based on linkage disequilibrium to known risk SNPs and their linked loci optimizes the performance of the polygenic resilience score.</p>","PeriodicalId":7673,"journal":{"name":"American Journal of Medical Genetics Part B: Neuropsychiatric Genetics","volume":"195 2","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10520885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nikki Hubers, Fiona A. Hagenbeek, René Pool, Sébastien Déjean, Amy C. Harms, Peter J. Roetman, Catharina E. M. van Beijsterveldt, Vassilios Fanos, Erik A. Ehli, Robert R. J. M. Vermeiren, Meike Bartels, Jouke Jan Hottenga, Thomas Hankemeier, Jenny van Dongen, Dorret I. Boomsma
The evolving field of multi-omics combines data and provides methods for simultaneous analysis across several omics levels. Here, we integrated genomics (transmitted and non-transmitted polygenic scores [PGSs]), epigenomics, and metabolomics data in a multi-omics framework to identify biomarkers for Attention-Deficit/Hyperactivity Disorder (ADHD) and investigated the connections among the three omics levels. We first trained single- and next multi-omics models to differentiate between cases and controls in 596 twins (cases = 14.8%) from the Netherlands Twin Register (NTR) demonstrating reasonable in-sample prediction through cross-validation. The multi-omics model selected 30 PGSs, 143 CpGs, and 90 metabolites. We confirmed previous associations of ADHD with glucocorticoid exposure and the transmembrane protein family TMEM, show that the DNA methylation of the MAD1L1 gene associated with ADHD has a relation with parental smoking behavior, and present novel findings including associations between indirect genetic effects and CpGs of the STAP2 gene. However, out-of-sample prediction in NTR participants (N = 258, cases = 14.3%) and in a clinical sample (N = 145, cases = 51%) did not perform well (range misclassification was [0.40, 0.57]). The results highlighted connections between omics levels, with the strongest connections between non-transmitted PGSs, CpGs, and amino acid levels and show that multi-omics designs considering interrelated omics levels can help unravel the complex biology underlying ADHD.
{"title":"Integrative multi-omics analysis of genomic, epigenomic, and metabolomics data leads to new insights for Attention-Deficit/Hyperactivity Disorder","authors":"Nikki Hubers, Fiona A. Hagenbeek, René Pool, Sébastien Déjean, Amy C. Harms, Peter J. Roetman, Catharina E. M. van Beijsterveldt, Vassilios Fanos, Erik A. Ehli, Robert R. J. M. Vermeiren, Meike Bartels, Jouke Jan Hottenga, Thomas Hankemeier, Jenny van Dongen, Dorret I. Boomsma","doi":"10.1002/ajmg.b.32955","DOIUrl":"10.1002/ajmg.b.32955","url":null,"abstract":"<p>The evolving field of multi-omics combines data and provides methods for simultaneous analysis across several omics levels. Here, we integrated genomics (transmitted and non-transmitted polygenic scores [PGSs]), epigenomics, and metabolomics data in a multi-omics framework to identify biomarkers for Attention-Deficit/Hyperactivity Disorder (ADHD) and investigated the connections among the three omics levels. We first trained single- and next multi-omics models to differentiate between cases and controls in 596 twins (cases = 14.8%) from the Netherlands Twin Register (NTR) demonstrating reasonable in-sample prediction through cross-validation. The multi-omics model selected 30 PGSs, 143 CpGs, and 90 metabolites. We confirmed previous associations of ADHD with glucocorticoid exposure and the transmembrane protein family <i>TMEM</i>, show that the DNA methylation of the <i>MAD1L1</i> gene associated with ADHD has a relation with parental smoking behavior, and present novel findings including associations between indirect genetic effects and CpGs of the <i>STAP2</i> gene. However, out-of-sample prediction in NTR participants (<i>N</i> = 258, cases = 14.3%) and in a clinical sample (<i>N</i> = 145, cases = 51%) did not perform well (range misclassification was [0.40, 0.57]). The results highlighted connections between omics levels, with the strongest connections between non-transmitted PGSs, CpGs, and amino acid levels and show that multi-omics designs considering interrelated omics levels can help unravel the complex biology underlying ADHD.</p>","PeriodicalId":7673,"journal":{"name":"American Journal of Medical Genetics Part B: Neuropsychiatric Genetics","volume":"195 2","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajmg.b.32955","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9927784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Valerie Morrill, Kelly Benke, John Brinton, Gnakub N. Soke, Laura A. Schieve, Victoria Fields, Homayoon Farzadegan, Calliope Holingue, Craig J. Newschaffer, Ann M. Reynolds, M. Daniele Fallin, Christine Ladd-Acosta
Children with autism spectrum disorder (ASD) have a greater prevalence of gastrointestinal (GI) symptoms than children without ASD. We tested whether polygenic scores for each of three GI disorders (ulcerative colitis, inflammatory bowel disease, and Crohn's disease) were related to GI symptoms in children with and without ASD. Using genotyping data (564 ASD cases and 715 controls) and external genome-wide association study summary statistics, we computed GI polygenic scores for ulcerative colitis (UC-PGS), inflammatory bowel disease (IDB-PGS), and Crohn's disease (CD-PGS). Multivariable logistic regression models, adjusted for genetic ancestry, were used to estimate associations between each GI-PGS and (1) ASD case–control status, and (2) specific GI symptoms in neurotypical children and separately in ASD children. In children without ASD, polygenic scores for ulcerative colitis were significantly associated with experiencing any GI symptom (adjusted odds ratio (aOR) = 1.36, 95% confidence interval (CI) = 1.03–1.81, p = 0.03) and diarrhea specifically (aOR = 5.35, 95% CI = 1.77–26.20, p = 0.01). Among children without ASD, IBD-PGS, and Crohn's PGS were significantly associated with diarrhea (aOR = 3.55, 95% CI = 1.25–12.34, p = 0.02) and loose stools alternating with constipation (aOR = 2.57, 95% CI = 1.13–6.55, p = 0.03), respectively. However, the three PGS were not associated with GI symptoms in the ASD case group. Furthermore, polygenic scores for ulcerative colitis significantly interacted with ASD status on presentation of any GI symptom within a European ancestry subset (aOR = 0.42, 95% CI = 0.19–0.88, p = 0.02). Genetic risk factors for some GI symptoms differ between children with and without ASD. Furthermore, our finding that increased genetic risks for GI inflammatory disorders are associated with GI symptoms in children without ASD informs future work on the early detection of GI disorders.
{"title":"Genetic liability for gastrointestinal inflammation disorders and association with gastrointestinal symptoms in children with and without autism","authors":"Valerie Morrill, Kelly Benke, John Brinton, Gnakub N. Soke, Laura A. Schieve, Victoria Fields, Homayoon Farzadegan, Calliope Holingue, Craig J. Newschaffer, Ann M. Reynolds, M. Daniele Fallin, Christine Ladd-Acosta","doi":"10.1002/ajmg.b.32952","DOIUrl":"10.1002/ajmg.b.32952","url":null,"abstract":"<p>Children with autism spectrum disorder (ASD) have a greater prevalence of gastrointestinal (GI) symptoms than children without ASD. We tested whether polygenic scores for each of three GI disorders (ulcerative colitis, inflammatory bowel disease, and Crohn's disease) were related to GI symptoms in children with and without ASD. Using genotyping data (564 ASD cases and 715 controls) and external genome-wide association study summary statistics, we computed GI polygenic scores for ulcerative colitis (UC-PGS), inflammatory bowel disease (IDB-PGS), and Crohn's disease (CD-PGS). Multivariable logistic regression models, adjusted for genetic ancestry, were used to estimate associations between each GI-PGS and (1) ASD case–control status, and (2) specific GI symptoms in neurotypical children and separately in ASD children. In children without ASD, polygenic scores for ulcerative colitis were significantly associated with experiencing any GI symptom (adjusted odds ratio (aOR) = 1.36, 95% confidence interval (CI) = 1.03–1.81, <i>p</i> = 0.03) and diarrhea specifically (aOR = 5.35, 95% CI = 1.77–26.20, <i>p</i> = 0.01). Among children without ASD, IBD-PGS, and Crohn's PGS were significantly associated with diarrhea (aOR = 3.55, 95% CI = 1.25–12.34, <i>p</i> = 0.02) and loose stools alternating with constipation (aOR = 2.57, 95% CI = 1.13–6.55, <i>p</i> = 0.03), respectively. However, the three PGS were not associated with GI symptoms in the ASD case group. Furthermore, polygenic scores for ulcerative colitis significantly interacted with ASD status on presentation of any GI symptom within a European ancestry subset (aOR = 0.42, 95% CI = 0.19–0.88, <i>p</i> = 0.02). Genetic risk factors for some GI symptoms differ between children with and without ASD. Furthermore, our finding that increased genetic risks for GI inflammatory disorders are associated with GI symptoms in children without ASD informs future work on the early detection of GI disorders.</p>","PeriodicalId":7673,"journal":{"name":"American Journal of Medical Genetics Part B: Neuropsychiatric Genetics","volume":"195 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajmg.b.32952","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9781758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the 19th century, psychiatric genetic studies typically utilized a generic category of “insanity.” This began to change after 1899, with the publication of Kraepelin's 6th edition containing, among other disorders, his mature concept of dementia praecox (DP). We here review an article published by Ryssia Wolfsohn in 1907 from her dissertation at the University of Zurich entitled “Die Heredität bei Dementia praecox” (The Heredity of Dementia Praecox). This work, performed under the supervision of E. Bleuler, was to our knowledge the first formal genetic study of the then new diagnosis of DP. She investigated 550 DP probands admitted to the Burghölzli hospital with known information about their “heredity burden.” For most probands, she had information on parents, siblings, grandparents, and aunts/uncles. Of these patients, only 10% had no psychiatric illness in their families. In the remaining probands, she found rates of the four major categories of psychopathology she investigated: mental illness—56%, nervous disorders—19%, peculiar personalities 12% and alcoholism 13%. Her most novel analyses compared either total familial burden or burden of her four forms of mental disorders on her DP probands divided by subtype and outcome. In neither of these analyses, did she find significant differences.
{"title":"Ryssia Wolfsohn's 1907 dissertation on “the heredity of dementia praecox”","authors":"Kenneth S. Kendler, Astrid Klee","doi":"10.1002/ajmg.b.32953","DOIUrl":"10.1002/ajmg.b.32953","url":null,"abstract":"<p>In the 19th century, psychiatric genetic studies typically utilized a generic category of “insanity.” This began to change after 1899, with the publication of Kraepelin's 6th edition containing, among other disorders, his mature concept of dementia praecox (DP). We here review an article published by Ryssia Wolfsohn in 1907 from her dissertation at the University of Zurich entitled “Die Heredität bei Dementia praecox” (The Heredity of Dementia Praecox). This work, performed under the supervision of E. Bleuler, was to our knowledge the first formal genetic study of the then new diagnosis of DP. She investigated 550 DP probands admitted to the Burghölzli hospital with known information about their “heredity burden.” For most probands, she had information on parents, siblings, grandparents, and aunts/uncles. Of these patients, only 10% had no psychiatric illness in their families. In the remaining probands, she found rates of the four major categories of psychopathology she investigated: mental illness—56%, nervous disorders—19%, peculiar personalities 12% and alcoholism 13%. Her most novel analyses compared either total familial burden or burden of her four forms of mental disorders on her DP probands divided by subtype and outcome. In neither of these analyses, did she find significant differences.</p>","PeriodicalId":7673,"journal":{"name":"American Journal of Medical Genetics Part B: Neuropsychiatric Genetics","volume":"195 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajmg.b.32953","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10132283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lianne P. de Vries, Perline A. Demange, Bart M. L. Baselmans, Christiaan H. Vinkers, Dirk H. M. Pelt, Meike Bartels
Hedonic (happiness) and eudaimonic (meaning in life) well-being are negatively related to depressive symptoms. Genetic variants play a role in this association, reflected in substantial genetic correlations. We investigated the overlap and differences between well-being and depressive symptoms, using results of Genome-Wide Association studies (GWAS) in UK Biobank. Subtracting GWAS summary statistics of depressive symptoms from those of happiness and meaning in life, we obtained GWASs of respectively “pure” happiness (neffective = 216,497) and “pure” meaning (neffective = 102,300). For both, we identified one genome-wide significant SNP (rs1078141 and rs79520962, respectively). After subtraction, SNP heritability reduced from 6.3% to 3.3% for pure happiness and from 6.2% to 4.2% for pure meaning. The genetic correlation between the well-being measures reduced from 0.78 to 0.65. Pure happiness and pure meaning became genetically unrelated to traits strongly associated with depressive symptoms, including loneliness, and psychiatric disorders. For other traits, including ADHD, educational attainment, and smoking, the genetic correlations of well-being versus pure well-being changed substantially. GWAS-by-subtraction allowed us to investigate the genetic variance of well-being unrelated to depressive symptoms. Genetic correlations with different traits led to new insights about this unique part of well-being. Our results can be used as a starting point to test causal relationships with other variables, and design future well-being interventions.
{"title":"Distinguishing happiness and meaning in life from depressive symptoms: A GWAS-by-subtraction study in the UK Biobank","authors":"Lianne P. de Vries, Perline A. Demange, Bart M. L. Baselmans, Christiaan H. Vinkers, Dirk H. M. Pelt, Meike Bartels","doi":"10.1002/ajmg.b.32954","DOIUrl":"10.1002/ajmg.b.32954","url":null,"abstract":"<p>Hedonic (happiness) and eudaimonic (meaning in life) well-being are negatively related to depressive symptoms. Genetic variants play a role in this association, reflected in substantial genetic correlations. We investigated the overlap and differences between well-being and depressive symptoms, using results of Genome-Wide Association studies (GWAS) in UK Biobank. Subtracting GWAS summary statistics of depressive symptoms from those of happiness and meaning in life, we obtained GWASs of respectively “pure” happiness (<i>n</i><sub>effective</sub> = 216,497) and “pure” meaning (<i>n</i><sub>effective</sub> = 102,300). For both, we identified one genome-wide significant SNP (rs1078141 and rs79520962, respectively). After subtraction, SNP heritability reduced from 6.3% to 3.3% for pure happiness and from 6.2% to 4.2% for pure meaning. The genetic correlation between the well-being measures reduced from 0.78 to 0.65. Pure happiness and pure meaning became genetically unrelated to traits strongly associated with depressive symptoms, including loneliness, and psychiatric disorders. For other traits, including ADHD, educational attainment, and smoking, the genetic correlations of well-being versus pure well-being changed substantially. GWAS-by-subtraction allowed us to investigate the genetic variance of well-being unrelated to depressive symptoms. Genetic correlations with different traits led to new insights about this unique part of well-being. Our results can be used as a starting point to test causal relationships with other variables, and design future well-being interventions.</p>","PeriodicalId":7673,"journal":{"name":"American Journal of Medical Genetics Part B: Neuropsychiatric Genetics","volume":"195 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajmg.b.32954","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10147571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Arden Moscati, Annika B. Faucon, Cayetana Arnaiz-Yépez, Sara Larsson Lönn, Jan Sundquist, Kristina Sundquist, Gillian M. Belbin, Girish Nadkarni, Judy H. Cho, Ruth J. F. Loos, Lea K. Davis, Kenneth S. Kendler
Fibromyalgia is a complex disease of unclear etiology that is complicated by difficulties in diagnosis, treatment, and clinical heterogeneity. To clarify this etiology, healthcare-based data are leveraged to assess the influences on fibromyalgia in several domains. Prevalence is less than 1% of females in our population register data, and about 1/10th that in males. Fibromyalgia often presents with co-occurring conditions including back pain, rheumatoid arthritis, and anxiety. More comorbidities are identified with hospital-associated biobank data, falling into three broad categories of pain-related, autoimmune, and psychiatric disorders. Selecting representative phenotypes with published genome-wide association results for polygenic scoring, we confirm genetic predispositions to psychiatric, pain sensitivity, and autoimmune conditions show associations with fibromyalgia, although these may differ by ancestry group. We conduct a genome-wide association analysis of fibromyalgia in biobank samples, which did not result in any genome-wide significant loci; further studies with increased sample size are necessary to identify specific genetic effects on fibromyalgia. Overall, fibromyalgia appears to have strong clinical and likely genetic links to several disease categories, and could usefully be understood as a composite manifestation of these etiological sources.
{"title":"Life is pain: Fibromyalgia as a nexus of multiple liability distributions","authors":"Arden Moscati, Annika B. Faucon, Cayetana Arnaiz-Yépez, Sara Larsson Lönn, Jan Sundquist, Kristina Sundquist, Gillian M. Belbin, Girish Nadkarni, Judy H. Cho, Ruth J. F. Loos, Lea K. Davis, Kenneth S. Kendler","doi":"10.1002/ajmg.b.32949","DOIUrl":"10.1002/ajmg.b.32949","url":null,"abstract":"<p>Fibromyalgia is a complex disease of unclear etiology that is complicated by difficulties in diagnosis, treatment, and clinical heterogeneity. To clarify this etiology, healthcare-based data are leveraged to assess the influences on fibromyalgia in several domains. Prevalence is less than 1% of females in our population register data, and about 1/10th that in males. Fibromyalgia often presents with co-occurring conditions including back pain, rheumatoid arthritis, and anxiety. More comorbidities are identified with hospital-associated biobank data, falling into three broad categories of pain-related, autoimmune, and psychiatric disorders. Selecting representative phenotypes with published genome-wide association results for polygenic scoring, we confirm genetic predispositions to psychiatric, pain sensitivity, and autoimmune conditions show associations with fibromyalgia, although these may differ by ancestry group. We conduct a genome-wide association analysis of fibromyalgia in biobank samples, which did not result in any genome-wide significant loci; further studies with increased sample size are necessary to identify specific genetic effects on fibromyalgia. Overall, fibromyalgia appears to have strong clinical and likely genetic links to several disease categories, and could usefully be understood as a composite manifestation of these etiological sources.</p>","PeriodicalId":7673,"journal":{"name":"American Journal of Medical Genetics Part B: Neuropsychiatric Genetics","volume":"192 7-8","pages":"171-182"},"PeriodicalIF":2.8,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10037031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yingjie Shi, Emma Sprooten, Peter Mulders, Janna Vrijsen, Janita Bralten, Ditte Demontis, Anders D. Børglum, G. Bragi Walters, Kari Stefansson, Philip van Eijndhoven, Indira Tendolkar, Barbara Franke, Nina Roth Mota
The dense co-occurrence of psychiatric disorders questions the categorical classification tradition and motivates efforts to establish dimensional constructs with neurobiological foundations that transcend diagnostic boundaries. In this study, we examined the genetic liability for eight major psychiatric disorder phenotypes under both a disorder-specific and a transdiagnostic framework. The study sample (n = 513) was deeply phenotyped, consisting of 452 patients from tertiary care with mood disorders, anxiety disorders (ANX), attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders, and/or substance use disorders (SUD) and 61 unaffected comparison individuals. We computed subject-specific polygenic risk score (PRS) profiles and assessed their associations with psychiatric diagnoses, comorbidity status, as well as cross-disorder behavioral dimensions derived from a rich battery of psychopathology assessments. High PRSs for depression were unselectively associated with the diagnosis of SUD, ADHD, ANX, and mood disorders (p < 1e-4). In the dimensional approach, four distinct functional domains were uncovered, namely the negative valence, social, cognitive, and regulatory systems, closely matching the major functional domains proposed by the Research Domain Criteria (RDoC) framework. Critically, the genetic predisposition for depression was selectively reflected in the functional aspect of negative valence systems (R2 = 0.041, p = 5e-4) but not others. This study adds evidence to the ongoing discussion about the misalignment between current psychiatric nosology and the underlying psychiatric genetic etiology and underscores the effectiveness of the dimensional approach in both the functional characterization of psychiatric patients and the delineation of the genetic liability for psychiatric disorders.
{"title":"Multi-polygenic scores in psychiatry: From disorder specific to transdiagnostic perspectives","authors":"Yingjie Shi, Emma Sprooten, Peter Mulders, Janna Vrijsen, Janita Bralten, Ditte Demontis, Anders D. Børglum, G. Bragi Walters, Kari Stefansson, Philip van Eijndhoven, Indira Tendolkar, Barbara Franke, Nina Roth Mota","doi":"10.1002/ajmg.b.32951","DOIUrl":"10.1002/ajmg.b.32951","url":null,"abstract":"<p>The dense co-occurrence of psychiatric disorders questions the categorical classification tradition and motivates efforts to establish dimensional constructs with neurobiological foundations that transcend diagnostic boundaries. In this study, we examined the genetic liability for eight major psychiatric disorder phenotypes under both a disorder-specific and a transdiagnostic framework. The study sample (<i>n</i> = 513) was deeply phenotyped, consisting of 452 patients from tertiary care with mood disorders, anxiety disorders (ANX), attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders, and/or substance use disorders (SUD) and 61 unaffected comparison individuals. We computed subject-specific polygenic risk score (PRS) profiles and assessed their associations with psychiatric diagnoses, comorbidity status, as well as cross-disorder behavioral dimensions derived from a rich battery of psychopathology assessments. High PRSs for depression were unselectively associated with the diagnosis of SUD, ADHD, ANX, and mood disorders (<i>p</i> < 1e-4). In the dimensional approach, four distinct functional domains were uncovered, namely the negative valence, social, cognitive, and regulatory systems, closely matching the major functional domains proposed by the Research Domain Criteria (RDoC) framework. Critically, the genetic predisposition for depression was selectively reflected in the functional aspect of negative valence systems (<i>R</i><sup>2</sup> = 0.041, <i>p =</i> 5e-4) but not others. This study adds evidence to the ongoing discussion about the misalignment between current psychiatric nosology and the underlying psychiatric genetic etiology and underscores the effectiveness of the dimensional approach in both the functional characterization of psychiatric patients and the delineation of the genetic liability for psychiatric disorders.</p>","PeriodicalId":7673,"journal":{"name":"American Journal of Medical Genetics Part B: Neuropsychiatric Genetics","volume":"195 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajmg.b.32951","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9711659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the first two decades of the 20th century, a new approach to psychiatric genetics research emerged in Germany from three roots: (i) the wide-spread acceptance of Kraepelin's diagnostic system, (ii) increasing interest in pedigree research, and (iii) excitement about Mendelian models. We review two relevant papers, reporting analyses of, respectively, 62 and 81 pedigrees: S. Schuppius in 1912 and E. Wittermann in 1913. While most prior asylum based studies only reported a patient's “hereditary burden,” they examined diagnoses of individual relatives at a particular place in a pedigree. Both authors focused on the segregation of dementia praecox (DP) and manic-depressive insanity (MDI). Schuppius reported that the two disorders frequently co-occurred in his pedigrees while Wittermann found them to be largely independent. Schuppius was skeptical of the feasibility of evaluating Mendelian models in humans. Wittermann, by contrast, with advice from Wilhelm Weinberg, applied algebraic models with proband correction to DP in his sibships with results consistent with autosomal recessive transmission. While he had less data, Wittermann suggested that MDI was likely an autosomal dominant disorder. Both authors were interested in other disorders or traits appearing in pedigrees dense with DP (e.g., idiocy) or MDI (e.g., highly excitable individuals).
{"title":"The examination of Kraepelin's diagnoses of dementia praecox and manic-depressive insanity in pedigrees: Studies of Schuppius in 1912 and Wittermann in 1913","authors":"Kenneth S. Kendler, Astrid Klee","doi":"10.1002/ajmg.b.32950","DOIUrl":"10.1002/ajmg.b.32950","url":null,"abstract":"<p>In the first two decades of the 20th century, a new approach to psychiatric genetics research emerged in Germany from three roots: (i) the wide-spread acceptance of Kraepelin's diagnostic system, (ii) increasing interest in pedigree research, and (iii) excitement about Mendelian models. We review two relevant papers, reporting analyses of, respectively, 62 and 81 pedigrees: S. Schuppius in 1912 and E. Wittermann in 1913. While most prior asylum based studies only reported a patient's “hereditary burden,” they examined diagnoses of individual relatives at a particular place in a pedigree. Both authors focused on the segregation of dementia praecox (DP) and manic-depressive insanity (MDI). Schuppius reported that the two disorders frequently co-occurred in his pedigrees while Wittermann found them to be largely independent. Schuppius was skeptical of the feasibility of evaluating Mendelian models in humans. Wittermann, by contrast, with advice from Wilhelm Weinberg, applied algebraic models with proband correction to DP in his sibships with results consistent with autosomal recessive transmission. While he had less data, Wittermann suggested that MDI was likely an autosomal dominant disorder. Both authors were interested in other disorders or traits appearing in pedigrees dense with DP (e.g., idiocy) or MDI (e.g., highly excitable individuals).</p>","PeriodicalId":7673,"journal":{"name":"American Journal of Medical Genetics Part B: Neuropsychiatric Genetics","volume":"192 7-8","pages":"113-123"},"PeriodicalIF":2.8,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajmg.b.32950","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9584130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jessica Mundy, Christopher Hübel, Brett N. Adey, Helena L. Davies, Molly R. Davies, Jonathan R. I. Coleman, Matthew Hotopf, Gursharan Kalsi, Sang Hyuck Lee, Andrew M. McIntosh, Henry C. Rogers, Thalia C. Eley, Robin M. Murray, Evangelos Vassos, Gerome Breen
The Mood Disorder Questionnaire (MDQ) is a common screening tool for bipolar disorder that assesses manic symptoms. Its utility for genetic studies of mania or bipolar traits has not been fully examined. We psychometrically compared the MDQ to self-reported bipolar disorder in participants from the United Kingdom National Institute of Health and Care Research Mental Health BioResource. We conducted genome-wide association studies of manic symptom quantitative traits and symptom subgroups, derived from the MDQ items (N = 11,568–19,859). We calculated genetic correlations with bipolar disorder and other psychiatric and behavioral traits. The MDQ screener showed low positive predictive value (0.29) for self-reported bipolar disorder. Neither concurrent nor lifetime manic symptoms were genetically correlated with bipolar disorder. Lifetime manic symptoms had a highest genetic correlation (rg = 1.0) with posttraumatic stress disorder although this was not confirmed by within-cohort phenotypic correlations (rp = 0.41). Other significant genetic correlations included attention deficit hyperactivity disorder (rg = 0.69), insomnia (rg = 0.55), and major depressive disorder (rg = 0.42). Our study adds to existing literature questioning the MDQ's validity and suggests it may capture symptoms of general distress or psychopathology, rather than hypomania/mania specifically, in at-risk populations.
{"title":"Genetic examination of the Mood Disorder Questionnaire and its relationship with bipolar disorder","authors":"Jessica Mundy, Christopher Hübel, Brett N. Adey, Helena L. Davies, Molly R. Davies, Jonathan R. I. Coleman, Matthew Hotopf, Gursharan Kalsi, Sang Hyuck Lee, Andrew M. McIntosh, Henry C. Rogers, Thalia C. Eley, Robin M. Murray, Evangelos Vassos, Gerome Breen","doi":"10.1002/ajmg.b.32938","DOIUrl":"10.1002/ajmg.b.32938","url":null,"abstract":"<p>The Mood Disorder Questionnaire (MDQ) is a common screening tool for bipolar disorder that assesses manic symptoms. Its utility for genetic studies of mania or bipolar traits has not been fully examined. We psychometrically compared the MDQ to self-reported bipolar disorder in participants from the United Kingdom National Institute of Health and Care Research Mental Health BioResource. We conducted genome-wide association studies of manic symptom quantitative traits and symptom subgroups, derived from the MDQ items (<i>N</i> = 11,568–19,859). We calculated genetic correlations with bipolar disorder and other psychiatric and behavioral traits. The MDQ screener showed low positive predictive value (0.29) for self-reported bipolar disorder. Neither concurrent nor lifetime manic symptoms were genetically correlated with bipolar disorder. Lifetime manic symptoms had a highest genetic correlation (<i>r</i><sub>g</sub> = 1.0) with posttraumatic stress disorder although this was not confirmed by within-cohort phenotypic correlations (<i>r</i><sub>p</sub> = 0.41). Other significant genetic correlations included attention deficit hyperactivity disorder (<i>r</i><sub>g</sub> = 0.69), insomnia (<i>r</i><sub>g</sub> = 0.55), and major depressive disorder (<i>r</i><sub>g</sub> = 0.42). Our study adds to existing literature questioning the MDQ's validity and suggests it may capture symptoms of general distress or psychopathology, rather than hypomania/mania specifically, in at-risk populations.</p>","PeriodicalId":7673,"journal":{"name":"American Journal of Medical Genetics Part B: Neuropsychiatric Genetics","volume":"192 7-8","pages":"147-160"},"PeriodicalIF":2.8,"publicationDate":"2023-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajmg.b.32938","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9447115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tiahna Moorthy, Huyen Nguyen, Ying Chen, Jehannine Austin, Jordan W. Smoller, Laura Hercher, Maya Sabatello
Polygenic risk scores (PRS) are promising for identifying common variant-related inheritance for psychiatric conditions but their integration into clinical practice depends on their clinical utility and psychiatrists' understanding of PRS. Our online survey explored these issues with 276 professionals working in psychiatric genetics (RR: 19%). Overall, participants demonstrated knowledge of how to interpret PRS results. Their performance on knowledge-based questions was positively correlated with participants' self-reported familiarity with PRS (r = 0.21, p = 0.0006) although differences were not statistically significant (Wald Chi-square = 3.29, df = 1, p = 0.07). However, only 48.9% of all participants answered all knowledge questions correctly. Many participants (56.5%), especially researchers (42%), indicated having at least occasional conversations about the role of genetics in psychiatric conditions with patients and/or family members. Most participants (62.7%) indicated that PRS are not yet sufficiently robust for assessment of susceptibility to schizophrenia; most significant obstacles were low predictive power and lack of population diversity in available PRS (selected, respectively, by 53.6% and 29.3% of participants). Nevertheless, 89.8% of participants were optimistic about the use of PRS in the next 10 years, suggesting a belief that current shortcomings could be addressed. Our findings inform about the perceptions of psychiatric professionals regarding PRS and the application of PRS in psychiatry.
{"title":"How do experts in psychiatric genetics view the clinical utility of polygenic risk scores for schizophrenia?","authors":"Tiahna Moorthy, Huyen Nguyen, Ying Chen, Jehannine Austin, Jordan W. Smoller, Laura Hercher, Maya Sabatello","doi":"10.1002/ajmg.b.32939","DOIUrl":"10.1002/ajmg.b.32939","url":null,"abstract":"<p>Polygenic risk scores (PRS) are promising for identifying common variant-related inheritance for psychiatric conditions but their integration into clinical practice depends on their clinical utility and psychiatrists' understanding of PRS. Our online survey explored these issues with 276 professionals working in psychiatric genetics (RR: 19%). Overall, participants demonstrated knowledge of how to interpret PRS results. Their performance on knowledge-based questions was positively correlated with participants' self-reported familiarity with PRS (<i>r</i> = 0.21, <i>p</i> = 0.0006) although differences were not statistically significant (Wald Chi-square = 3.29, df = 1, <i>p</i> = 0.07). However, only 48.9% of all participants answered all knowledge questions correctly. Many participants (56.5%), especially researchers (42%), indicated having at least occasional conversations about the role of genetics in psychiatric conditions with patients and/or family members. Most participants (62.7%) indicated that PRS are not yet sufficiently robust for assessment of susceptibility to schizophrenia; most significant obstacles were low predictive power and lack of population diversity in available PRS (selected, respectively, by 53.6% and 29.3% of participants). Nevertheless, 89.8% of participants were optimistic about the use of PRS in the next 10 years, suggesting a belief that current shortcomings could be addressed. Our findings inform about the perceptions of psychiatric professionals regarding PRS and the application of PRS in psychiatry.</p>","PeriodicalId":7673,"journal":{"name":"American Journal of Medical Genetics Part B: Neuropsychiatric Genetics","volume":"192 7-8","pages":"161-170"},"PeriodicalIF":2.8,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ajmg.b.32939","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9798904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}