Pub Date : 2024-10-01DOI: 10.1016/j.euroneuro.2024.08.082
{"title":"UPDATE FROM THE “PEDIGREE-BASED WHOLE GENOME SEQUENCING OF AFFECTIVE AND PSYCHOTIC DISORDERS\" CONSORTIUM","authors":"","doi":"10.1016/j.euroneuro.2024.08.082","DOIUrl":"10.1016/j.euroneuro.2024.08.082","url":null,"abstract":"","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"87 ","pages":"Page 33"},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.euroneuro.2024.08.106
{"title":"FAST AND EFFICIENT MIXED-EFFECTS ALGORITHM (FEMA) FOR LONGITUDINAL GWAS AND SNP × TIME INTERACTION: APPLICATIONS AND OPPORTUNITIES IN MOBA","authors":"","doi":"10.1016/j.euroneuro.2024.08.106","DOIUrl":"10.1016/j.euroneuro.2024.08.106","url":null,"abstract":"","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"87 ","pages":"Page 43"},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.euroneuro.2024.08.029
{"title":"THE BASICS OF MENDELIAN RANDOMISATION AND SPECIFIC CONSIDERATIONS FOR MENTAL HEALTH TRAITS","authors":"","doi":"10.1016/j.euroneuro.2024.08.029","DOIUrl":"10.1016/j.euroneuro.2024.08.029","url":null,"abstract":"","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"87 ","pages":"Page 10"},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.euroneuro.2024.08.041
{"title":"PRELIMINARY INVESTIGATIONS INTO THE GUT MICROBIOME'S ROLE IN SCHIZOPHRENIA","authors":"","doi":"10.1016/j.euroneuro.2024.08.041","DOIUrl":"10.1016/j.euroneuro.2024.08.041","url":null,"abstract":"","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"87 ","pages":"Page 14"},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.euroneuro.2024.08.036
Karl Heilbron , Julia Kraft , Alice Braun , Swapnil Awasthi , Georgia Panagiotaropoulou , Marijn Schipper , Nathaniel Bell , Danielle Posthuma , Antonio Pardiñas , Stephan Ripke
The latest schizophrenia GWAS meta-analysis found 287 loci that reached genome-wide statistical significance (67,390 cases and 94,015 controls). In these loci, 120 genes were prioritized using fine-mapping, summary-based Mendelian Randomization (SMR), and enhancer-promoter interaction (via Hi-C). However, these methods only use information within a given locus, ignoring information from the rest of the genome. Combining locus-based approaches with tools that incorporate genome-wide information such as the Polygenic Priority Score (PoPS) have been shown to improve gene prioritization precision. To more accurately characterize genes that play a role in schizophrenia etiology, we prioritized 62 genes based on their distance to GWAS signals, PoPS, fine-mapped coding variants, and ultra-rare coding variant burden tests. We prioritized DRD2, the target of most approved antipsychotics, which was not highlighted by previous efforts. In addition, we prioritized 9 genes that are targeted by approved or investigational drugs and may therefore present drug repurposing opportunities. These included drugs targeting calcium channels (CACNA1C and CACNB2), glutamatergic receptors (GRIN2A and GRM3), and GABAB receptor (GABBR2). We highlighted 3 additional genes (PDE4B, VRK2, and PLCL2) in loci that are shared with a recent addiction GWAS. While it is challenging to assess psychotic symptoms in rodents, high-quality rodent addiction models exist for a wide range of substances. Modulation of these genes could be tested in rodent addiction models and, if successful, may warrant further testing in human clinical trials of addiction and/or schizophrenia. Adding to previous gene prioritization efforts, we hope that our list of prioritized genes will ultimately facilitate the development of new medicines for people living with schizophrenia.
{"title":"IDENTIFYING DRUG TARGETS FOR SCHIZOPHRENIA THROUGH GENE PRIORITIZATION","authors":"Karl Heilbron , Julia Kraft , Alice Braun , Swapnil Awasthi , Georgia Panagiotaropoulou , Marijn Schipper , Nathaniel Bell , Danielle Posthuma , Antonio Pardiñas , Stephan Ripke","doi":"10.1016/j.euroneuro.2024.08.036","DOIUrl":"10.1016/j.euroneuro.2024.08.036","url":null,"abstract":"<div><div>The latest schizophrenia GWAS meta-analysis found 287 loci that reached genome-wide statistical significance (67,390 cases and 94,015 controls). In these loci, 120 genes were prioritized using fine-mapping, summary-based Mendelian Randomization (SMR), and enhancer-promoter interaction (via Hi-C). However, these methods only use information within a given locus, ignoring information from the rest of the genome. Combining locus-based approaches with tools that incorporate genome-wide information such as the Polygenic Priority Score (PoPS) have been shown to improve gene prioritization precision. To more accurately characterize genes that play a role in schizophrenia etiology, we prioritized 62 genes based on their distance to GWAS signals, PoPS, fine-mapped coding variants, and ultra-rare coding variant burden tests. We prioritized DRD2, the target of most approved antipsychotics, which was not highlighted by previous efforts. In addition, we prioritized 9 genes that are targeted by approved or investigational drugs and may therefore present drug repurposing opportunities. These included drugs targeting calcium channels (CACNA1C and CACNB2), glutamatergic receptors (GRIN2A and GRM3), and GABAB receptor (GABBR2). We highlighted 3 additional genes (PDE4B, VRK2, and PLCL2) in loci that are shared with a recent addiction GWAS. While it is challenging to assess psychotic symptoms in rodents, high-quality rodent addiction models exist for a wide range of substances. Modulation of these genes could be tested in rodent addiction models and, if successful, may warrant further testing in human clinical trials of addiction and/or schizophrenia. Adding to previous gene prioritization efforts, we hope that our list of prioritized genes will ultimately facilitate the development of new medicines for people living with schizophrenia.</div></div>","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"87 ","pages":"Page 12"},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.euroneuro.2024.08.049
Sarah Colbert , The Suicide Working Group of the Psychiatric Genomics Consortium , Douglas Ruderfer , Anna Docherty , Niamh Mullins
<div><div>Suicidal thoughts and behaviors, specifically suicidal ideation (SI), suicide attempt (SA) and suicide death (SD), are substantially heritable, with twin and family studies estimating heritabilities in the range of 30-55%. Recently, genome-wide association studies (GWAS) have reached sufficient sample sizes to conduct well-powered analyses, leading to the identification of 4, 12 and 2 loci associated with SI, SA, and SD, respectively. Importantly, these phenotypes show strong, yet incomplete, genetic correlations with each other, motivating genetic studies of each phenotype separately to understand their underlying biology and the progression from one to the next. Here, we present an update on the progress of the latest and most extensive GWAS of SI, SA, and SD, conducted by the Psychiatric Genomics Consortium Suicide Working Group (PGC SUI).</div><div><strong>Methods:</strong> Data comprise 30 cohorts contributing to the SI GWAS (N cases=256,257, N controls=1,298,106), 42 cohorts contributing to the SA GWAS (N cases=73,087, N controls=1,327,350), and 6 cohorts contributing to the SD GWAS (N cases=6,775, N controls=841,216). Notably, these cohorts comprise individuals from four diverse genetic ancestry groups: admixed European ancestries (EUR), admixed African ancestries (AA), East Asian ancestries (EA) and admixed Latino ancestries (LAT). New phenotyping and analytic protocols have been developed by PGC SUI to ensure exceptional rigor and comparability across cohorts. GWAS meta-analyses will be conducted via inverse variance-weighted fixed effects models to identify novel genetic risk loci. Post-GWAS analyses include pathway, tissue and drug target enrichment, and examination of the SNP-heritabilities (h2SNP), and genetic relationships between SI, SA, and SD.</div><div>Preliminary analysis using the currently available SA data (SA cases = 47,174, controls = 941,010 from 26 cohorts) yielded a h2SNP of 5.6% (se = 0.003, p = 1.2e-68) and ten replicated and three novel genome-wide significant (GWS) loci, containing FYN, AIG1, and DCC. Eight GWS loci were identified in the EUR meta-analysis (h2SNP = 7%, se = 0.004) which replicated previous findings. No GWS loci were identified in the AA (h2SNP = 9.8%, se = 0.02), EA (h2SNP 5.1%, se = 0.04) or LAT (h2SNP = 10%, se =0.07) GWAS meta-analyses. We also identified significant enrichment in genes expressed in several brain tissues from GTEx and summary data-based Mendelian Randomization revealed two novel genes (GMPPB, FURIN) significantly associated with SA. This SA GWAS showed significant genetic correlations with published GWAS of SI (rg = 0.80, se = 0.04), SD (rg = 0.77, se = 0.05), and several psychiatric disorders (rgs = 0.26-0.70).</div><div>Additional data intake is almost complete within PGC SUI, and this presentation will share the final GWAS results and novel biological insights. Increased sample sizes in combination with streamlined protocols for phenotyping and analyzing suicidal tho
{"title":"GENOME-WIDE ASSOCIATION STUDIES OF SUICIDAL THOUGHTS AND BEHAVIORS: AN UPDATE FROM THE PSYCHIATRIC GENOMICS CONSORTIUM SUICIDE WORKING GROUP","authors":"Sarah Colbert , The Suicide Working Group of the Psychiatric Genomics Consortium , Douglas Ruderfer , Anna Docherty , Niamh Mullins","doi":"10.1016/j.euroneuro.2024.08.049","DOIUrl":"10.1016/j.euroneuro.2024.08.049","url":null,"abstract":"<div><div>Suicidal thoughts and behaviors, specifically suicidal ideation (SI), suicide attempt (SA) and suicide death (SD), are substantially heritable, with twin and family studies estimating heritabilities in the range of 30-55%. Recently, genome-wide association studies (GWAS) have reached sufficient sample sizes to conduct well-powered analyses, leading to the identification of 4, 12 and 2 loci associated with SI, SA, and SD, respectively. Importantly, these phenotypes show strong, yet incomplete, genetic correlations with each other, motivating genetic studies of each phenotype separately to understand their underlying biology and the progression from one to the next. Here, we present an update on the progress of the latest and most extensive GWAS of SI, SA, and SD, conducted by the Psychiatric Genomics Consortium Suicide Working Group (PGC SUI).</div><div><strong>Methods:</strong> Data comprise 30 cohorts contributing to the SI GWAS (N cases=256,257, N controls=1,298,106), 42 cohorts contributing to the SA GWAS (N cases=73,087, N controls=1,327,350), and 6 cohorts contributing to the SD GWAS (N cases=6,775, N controls=841,216). Notably, these cohorts comprise individuals from four diverse genetic ancestry groups: admixed European ancestries (EUR), admixed African ancestries (AA), East Asian ancestries (EA) and admixed Latino ancestries (LAT). New phenotyping and analytic protocols have been developed by PGC SUI to ensure exceptional rigor and comparability across cohorts. GWAS meta-analyses will be conducted via inverse variance-weighted fixed effects models to identify novel genetic risk loci. Post-GWAS analyses include pathway, tissue and drug target enrichment, and examination of the SNP-heritabilities (h2SNP), and genetic relationships between SI, SA, and SD.</div><div>Preliminary analysis using the currently available SA data (SA cases = 47,174, controls = 941,010 from 26 cohorts) yielded a h2SNP of 5.6% (se = 0.003, p = 1.2e-68) and ten replicated and three novel genome-wide significant (GWS) loci, containing FYN, AIG1, and DCC. Eight GWS loci were identified in the EUR meta-analysis (h2SNP = 7%, se = 0.004) which replicated previous findings. No GWS loci were identified in the AA (h2SNP = 9.8%, se = 0.02), EA (h2SNP 5.1%, se = 0.04) or LAT (h2SNP = 10%, se =0.07) GWAS meta-analyses. We also identified significant enrichment in genes expressed in several brain tissues from GTEx and summary data-based Mendelian Randomization revealed two novel genes (GMPPB, FURIN) significantly associated with SA. This SA GWAS showed significant genetic correlations with published GWAS of SI (rg = 0.80, se = 0.04), SD (rg = 0.77, se = 0.05), and several psychiatric disorders (rgs = 0.26-0.70).</div><div>Additional data intake is almost complete within PGC SUI, and this presentation will share the final GWAS results and novel biological insights. Increased sample sizes in combination with streamlined protocols for phenotyping and analyzing suicidal tho","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"87 ","pages":"Page 18"},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
While the longitudinal aspect of mental disorders is critical for investigating disease mechanisms and improving treatment, psychiatric genetics have mostly focused on cross-sectional data. Longitudinal datasets from diverse ancestries are paramount to make progress in understanding mental health and illnesses. Availability of trajectories of phenotypes covering premorbid and prodromal stages, and the course of illnesses, coupled with genetics and other biological material will enable us to chart how mental disorders develop, characterize resilience and treatment, allow population stratification, and pave the way for early detection.
This session will present four large diverse longitudinal datasets covering the lifespan – from childhood to old age. The presenters will describe the datasets and new methods developed to take advantage of the longitudinal aspects, and novel results highlighting the opportunities for the field.
Dr. Parekh will introduce the Norwegian Mother, Father and Child Cohort Study (MoBa), an ongoing study following children from birth. This talk will present FEMA (and FEMA-GWAS) statistical methods for longitudinal data and present results that highlight longitudinal, time dependent genetic effects.
Ms. Smith will introduce the Adolescent Brain Cognitive Development (ABCD) Study, an ongoing study on adolescents in the United States. This talk will showcase multimodal imaging-genetics results using FEMA as well as shared resources that will allow any investigator to perform real-time analyses in the ABCD Study.
Dr. Viswanath will introduce the Centre for Brain and Mind (CBM) - Accelerator program for Discovery in Brain disorders using Stem cells (ADBS), an ongoing study on adults in India. This talk will highlight the opportunities and present results linking neuroimaging and rare damaging variants in patients with psychiatric illnesses.
Dr. Namba will introduce the BioBank Japan (BBJ), an ongoing study with extensive registry, biological, laboratory examinations, and other information across a wide range of 47 diseases across the lifespan. This talk will showcase ongoing studies of genetic risk variants, and present opportunities for ongoing collaborative endeavors towards precision medicine.
Dr. Parker, the symposium discussant, will discuss how these lifespan datasets can be integrated and used to generate insights to advance our understanding of the neurobiology of psychiatric illnesses and the goals of precision psychiatry. We will conclude the symposium with remarks on how diverse lifespan datasets can provide valuable knowledge and provide novel opportunities for the field.
{"title":"LONGITUDINAL GENETIC APPROACHES IN MENTAL HEALTH: INTERNATIONAL PERSPECTIVES AND OPPORTUNITIES","authors":"Ole Andreassen (Chair) , Helga Ask (Co-chair) , Nadine Parker (Discussant)","doi":"10.1016/j.euroneuro.2024.08.105","DOIUrl":"10.1016/j.euroneuro.2024.08.105","url":null,"abstract":"<div><div>While the longitudinal aspect of mental disorders is critical for investigating disease mechanisms and improving treatment, psychiatric genetics have mostly focused on cross-sectional data. Longitudinal datasets from diverse ancestries are paramount to make progress in understanding mental health and illnesses. Availability of trajectories of phenotypes covering premorbid and prodromal stages, and the course of illnesses, coupled with genetics and other biological material will enable us to chart how mental disorders develop, characterize resilience and treatment, allow population stratification, and pave the way for early detection.</div><div>This session will present four large diverse longitudinal datasets covering the lifespan – from childhood to old age. The presenters will describe the datasets and new methods developed to take advantage of the longitudinal aspects, and novel results highlighting the opportunities for the field.</div><div>Dr. Parekh will introduce the Norwegian Mother, Father and Child Cohort Study (MoBa), an ongoing study following children from birth. This talk will present FEMA (and FEMA-GWAS) statistical methods for longitudinal data and present results that highlight longitudinal, time dependent genetic effects.</div><div>Ms. Smith will introduce the Adolescent Brain Cognitive Development (ABCD) Study, an ongoing study on adolescents in the United States. This talk will showcase multimodal imaging-genetics results using FEMA as well as shared resources that will allow any investigator to perform real-time analyses in the ABCD Study.</div><div>Dr. Viswanath will introduce the Centre for Brain and Mind (CBM) - Accelerator program for Discovery in Brain disorders using Stem cells (ADBS), an ongoing study on adults in India. This talk will highlight the opportunities and present results linking neuroimaging and rare damaging variants in patients with psychiatric illnesses.</div><div>Dr. Namba will introduce the BioBank Japan (BBJ), an ongoing study with extensive registry, biological, laboratory examinations, and other information across a wide range of 47 diseases across the lifespan. This talk will showcase ongoing studies of genetic risk variants, and present opportunities for ongoing collaborative endeavors towards precision medicine.</div><div>Dr. Parker, the symposium discussant, will discuss how these lifespan datasets can be integrated and used to generate insights to advance our understanding of the neurobiology of psychiatric illnesses and the goals of precision psychiatry. We will conclude the symposium with remarks on how diverse lifespan datasets can provide valuable knowledge and provide novel opportunities for the field.</div></div>","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"87 ","pages":"Pages 42-43"},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.euroneuro.2024.08.085
Alexander Neumann , Sara Sammallahti , Marta Cosin-Tomas , Sarah Reese , Henning Tiemeier , Stephanie London , Janine Felix , Charlotte Cecil
<div><div>DNA methylation (DNAm) is a developmentally dynamic epigenetic process, yet, most studies linking DNAm to health phenotypes measure DNAm only once. Thus, it is largely unknown (i) whether the relationship between DNAm and health outcomes varies across development (ii) at which developmental periods DNAm profiles could be most informative for these outcomes, and (iii) to what extent DNAm-health associations at one timepoint can be generalized to other timepoints.</div><div>In most pediatric population studies, DNAm is either measured in cord blood samples at birth and associated with a child outcome at a later timepoint (i.e. prospective epigenome-wide association study [EWAS]) or DNAm is measured from a blood sample at the same timepoint as the child outcome (i.e. cross-sectional EWAS). Recently, the Pregnancy And Childhood Epigenetics (PACE) Consortium published five multi-cohort EWAS meta-analyses that investigated DNAm using both designs in relation to the same child outcome, spanning mental and physical health domains, namely: ADHD, general psychopathology (measured as a latent factor; GPF), sleep duration, body mass index (BMI) and asthma.</div><div>Here, we re-analyzed the five PACE meta-analyses (Npooled=2178-4641, 26 cohorts) to explore timing effects on DNAm-health associations during development. For each outcome, we integrated results from the prospective EWAS (cord blood DNAm at birth) and the cross-sectional EWAS (whole blood DNAm in childhood) into a longitudinal meta-regression model. This model systematically quantified changes in effect sizes and statistical significance between timepoints, and we also explored a range of factors that may contribute to the observed temporal trends. We then correlated DNAm associations between timepoints (to assess generalizability of epigenetic signals from one timepoint to another) and across health outcomes (to explore presence of shared DNAm associations).</div><div>Our findings reveal three new insights: (i) across outcomes, effects sizes are larger when DNAm is measured in childhood and cross-sectionally associated with child health outcomes, compared to when DNAm is assessed at birth and prospectively associated with later health development; (ii) higher effect sizes do not necessarily translate into more significant findings, as associations also become noisier in childhood for most outcomes (i.e. showing larger standard errors); and (iii) DNAm signals are highly time-specific, while showing pleiotropy across health outcomes: regression coefficients at birth did not correlate with those in childhood with few exceptions.</div><div>Overall, our results suggest developmentally-specific associations between DNAm and child health outcomes, when assessing DNAm at birth vs childhood. This implies that EWAS results from one timepoint are unlikely to generalize to another, at least based on birth vs childhood comparisons. Longitudinal studies with repeated epigenetic assessments are direl
{"title":"EPIGENETIC TIMING EFFECTS ON CHILD DEVELOPMENTAL OUTCOMES: A LONGITUDINAL META-REGRESSION OF FINDINGS FROM THE PREGNANCY AND CHILDHOOD EPIGENETICS CONSORTIUM","authors":"Alexander Neumann , Sara Sammallahti , Marta Cosin-Tomas , Sarah Reese , Henning Tiemeier , Stephanie London , Janine Felix , Charlotte Cecil","doi":"10.1016/j.euroneuro.2024.08.085","DOIUrl":"10.1016/j.euroneuro.2024.08.085","url":null,"abstract":"<div><div>DNA methylation (DNAm) is a developmentally dynamic epigenetic process, yet, most studies linking DNAm to health phenotypes measure DNAm only once. Thus, it is largely unknown (i) whether the relationship between DNAm and health outcomes varies across development (ii) at which developmental periods DNAm profiles could be most informative for these outcomes, and (iii) to what extent DNAm-health associations at one timepoint can be generalized to other timepoints.</div><div>In most pediatric population studies, DNAm is either measured in cord blood samples at birth and associated with a child outcome at a later timepoint (i.e. prospective epigenome-wide association study [EWAS]) or DNAm is measured from a blood sample at the same timepoint as the child outcome (i.e. cross-sectional EWAS). Recently, the Pregnancy And Childhood Epigenetics (PACE) Consortium published five multi-cohort EWAS meta-analyses that investigated DNAm using both designs in relation to the same child outcome, spanning mental and physical health domains, namely: ADHD, general psychopathology (measured as a latent factor; GPF), sleep duration, body mass index (BMI) and asthma.</div><div>Here, we re-analyzed the five PACE meta-analyses (Npooled=2178-4641, 26 cohorts) to explore timing effects on DNAm-health associations during development. For each outcome, we integrated results from the prospective EWAS (cord blood DNAm at birth) and the cross-sectional EWAS (whole blood DNAm in childhood) into a longitudinal meta-regression model. This model systematically quantified changes in effect sizes and statistical significance between timepoints, and we also explored a range of factors that may contribute to the observed temporal trends. We then correlated DNAm associations between timepoints (to assess generalizability of epigenetic signals from one timepoint to another) and across health outcomes (to explore presence of shared DNAm associations).</div><div>Our findings reveal three new insights: (i) across outcomes, effects sizes are larger when DNAm is measured in childhood and cross-sectionally associated with child health outcomes, compared to when DNAm is assessed at birth and prospectively associated with later health development; (ii) higher effect sizes do not necessarily translate into more significant findings, as associations also become noisier in childhood for most outcomes (i.e. showing larger standard errors); and (iii) DNAm signals are highly time-specific, while showing pleiotropy across health outcomes: regression coefficients at birth did not correlate with those in childhood with few exceptions.</div><div>Overall, our results suggest developmentally-specific associations between DNAm and child health outcomes, when assessing DNAm at birth vs childhood. This implies that EWAS results from one timepoint are unlikely to generalize to another, at least based on birth vs childhood comparisons. Longitudinal studies with repeated epigenetic assessments are direl","PeriodicalId":12049,"journal":{"name":"European Neuropsychopharmacology","volume":"87 ","pages":"Pages 34-35"},"PeriodicalIF":6.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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