Shared Genetic Contributions to Cognition and Psychiatric Disorder Risk Based on Genome-Wide Data

AbstractBackgroundDespite established clinical associations among major depression (MD), alcohol dependence (AD), and alcohol consumption (AC), the nature of the causal relationship between them is not completely understood. We leveraged genome-wide data from the Psychiatric Genomics Consortium (PGC) and UK Biobank to test for the presence of shared genetic mechanisms and causal relationships among MD, AD, and AC.MethodsLinkage disequilibrium score regression and Mendelian randomization (MR) were performed using genome-wide data from the PGC (MD: 135 458 cases and 344 901 controls; AD: 10 206 cases and 28 480 controls) and UK Biobank (AC-frequency: 438 308 individuals; AC-quantity: 307 098 individuals).ResultsPositive genetic correlation was observed between MD and AD (rgMD−AD = + 0.47, P = 6.6 × 10−10). AC-quantity showed positive genetic correlation with both AD (rgAD−AC quantity = + 0.75, P = 1.8 × 10−14) and MD (rgMD−AC quantity = + 0.14, P = 2.9 × 10−7), while there was negative correlation of AC-frequency with MD (rgMD−AC frequency = −0.17, P = 1.5 × 10−10) and a non-significant result with AD. MR analyses confirmed the presence of pleiotropy among these four traits. However, the MD-AD results reflect a mediated-pleiotropy mechanism (i.e. causal relationship) with an effect of MD on AD (beta = 0.28, P = 1.29 × 10−6). There was no evidence for reverse causation.ConclusionThis study supports a causal role for genetic liability of MD on AD based on genetic datasets including thousands of individuals. Understanding mechanisms underlying MD-AD comorbidity addresses important public health concerns and has the potential to facilitate prevention and intervention efforts.

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Genome-wide landscape of RNA-binding protein dysregulation reveals a major impact on psychiatric disorder risk

10.1101/2020.05.19.102319 ◽

2020 ◽

Author(s):

Christopher Y. Park ◽

Jian Zhou ◽

Aaron K. Wong ◽

Kathleen M. Chen ◽

Chandra L. Theesfeld ◽

...

Keyword(s):

Psychiatric Disorder ◽

Psychiatric Disorders ◽

Large Scale ◽

Complex Disease ◽

Rna Binding ◽

Rna Binding Proteins ◽

Full Range ◽

Coding Region ◽

Genome Wide ◽

Disorder Risk

AbstractDespite the strong genetic basis of psychiatric disorders, the molecular origins of these diseases are still largely unmapped. RNA-binding proteins (RBPs) are responsible for most post-transcriptional regulation, from splicing to translational to localization. RBPs thus act as key gatekeepers of cellular homeostasis, especially in the brain. Here, we leverage a deep learning approach to interrogate variant effects genome-wide, and discover that the dysregulation of RBP target sites is a principal contributor to psychiatric disorder risk. We show that specific modes of RBP regulation are genetically linked to the heritability of psychiatric disorders, and demonstrate that diverse RBP regulatory functions are reflected in distinct genome-wide negative selection signatures. Notably, RBP dysregulation has a stronger impact on psychiatric disorders than common coding region variants and explains heritability not currently captured by large-scale molecular QTL studies (expression QTLs and splicing QTLs). We share genome-wide profiles of RBP target site dysregulation, which we used to identify DDHD2 as a candidate schizophrenia risk gene, in a public web server. This resource provides a novel analytical framework to connect the full range of RNA regulation to complex disease.

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Evidence of causal effect of major depression on alcohol dependence: Findings from the Psychiatric Genomics Consortium

10.1101/412098 ◽

2018 ◽

Cited By ~ 4

Author(s):

Renato Polimanti ◽

Roseann E. Peterson ◽

Jue-Sheng Ong ◽

Stuart MacGregor ◽

Alexis C. Edwards ◽

...

Keyword(s):

Major Depression ◽

Alcohol Consumption ◽

Alcohol Dependence ◽

Mendelian Randomization ◽

Causal Effect ◽

Causal Relationships ◽

Genome Wide ◽

Genome Wide Data ◽

Genetic Mechanisms ◽

Shared Genetic

ABSTRACTBackgroundDespite established clinical associations among major depression (MD), alcohol dependence (AD), and alcohol consumption (AC), the nature of the causal relationship between them is not completely understood.MethodsThis study was conducted using genome-wide data from the Psychiatric Genomics Consortium (MD: 135,458 cases and 344,901 controls; AD: 10,206 cases and 28,480 controls) and UK Biobank (AC-Frequency: from “daily or almost daily” to “never”, 438,308 individuals; AC-Quantity: total units of alcohol per week, 307,098 individuals). Linkage disequilibrium score regression and Mendelian Randomization (MR) analyses were applied to investigate shared genetic mechanisms (horizontal pleiotropy) and causal relationships (mediated pleiotropy) among these traits.OutcomesPositive genetic correlation was observed between MD and AD (rgMD-AD=+0.47, P=6.6×10-10). AC-Quantity showed positive genetic correlation with both AD (rgAD-AC-Quantity=+0.75, P=1.8×10-14) and MD (rgMD-AC-Quantity=+0.14, P=2.9×10-7), while there was negative correlation of AC-Frequency with MD (rgMD-AC-Frequency=-0.17, P=1.5×10-10) and a non-significant result with AD. MR analyses confirmed the presence of pleiotropy among these traits. However, the MD-AD results reflect a mediated-pleiotropy mechanism (i.e., causal relationship) with a causal role of MD on AD (beta=0.28, P=1.29×10-6) that does not appear to be biased by confounding such as horizontal pleiotropy. No evidence of reverse causation was observed as the AD genetic instrument did not show a causal effect on MD.InterpretationResults support a causal role for MD on AD based on genetic datasets including thousands of individuals. Understanding mechanisms underlying MD-AD comorbidity not only addresses important public health concerns but also has the potential to facilitate prevention and intervention efforts.FundingNational Institute of Mental Health and National Institute on Drug Abuse.Putting data into contextEvidence before this studyWe searched PubMed up to August 24, 2018, for research studies that investigated causality among alcohol-and depression related phenotypes using Mendelian randomization approaches. We used the search terms “alcohol” AND “depression” AND “Mendelian Randomization”. No restrictions were applied to language, date, or article type. Ten articles were retrieved, but only two were focused on alcohol consumption and depression-related traits. The studies were based on genetic variants in alcohol dehydrogenase (ADH) genes only, did not find evidence for a causal effect of alcohol consumption on depression phenotypes, with one study finding a causal effect of alcohol consumption on alcoholism. Both studies noted that future studies are needed with increased sample sizes and clinically derived phenotypes. To our knowledge, no previous study has applied two-sample Mendelian randomization to investigate causal relationships between alcohol dependence and major depression.Twin studies show genetic factors influence susceptibility to MD, AD, and alcohol consumption. Differently from observational approaches where several studies have investigated the relationship between alcohol-and depression-related phenotypes, very limited use of molecular genetic data has been applied to investigate this issue. Additionally, the use of genetic information has been shown to be less biased by confounders and reverse causation than observation data. However, genetic approaches, like Mendelian randomization, require large sample sizes to be informative.Added value of this studyIn this study, we used genome-wide data from the Psychiatric Genomic Consortium and UK Biobank, which include information regarding hundred thousands of individuals, to test the presence of shared genetic mechanisms and causal relationships among major depression, alcohol dependence, and alcohol consumption. The results support a causal influence of MD on AD, while alcohol consumption showed shared genetic mechanisms with respect to both major depression and alcohol dependence.Implications of all the available evidenceGiven the significant morbidity and mortality associated with MD, AD, and the comorbid condition, understanding mechanisms underlying these associations not only address important public health concerns but also has the potential to facilitate prevention and intervention efforts.

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Shared and distinct genetic influences between cognitive domains and psychiatric disorder risk based on genome-wide data

10.1101/2020.09.16.297408 ◽

2020 ◽

Author(s):

CE Carey ◽

Y Huang ◽

RW Strong ◽

S Aslibekyan ◽

RC Gentleman ◽

...

Keyword(s):

Psychiatric Disorder ◽

Genetic Correlation ◽

Cognitive Abilities ◽

Vocabulary Knowledge ◽

Digit Symbol ◽

Visual Change ◽

Genome Wide ◽

Symbol Substitution ◽

Visual Change Detection ◽

Disorder Risk

AbstractGroup-level cognitive performance differences are found in psychiatric disorders ranging from depression to autism to schizophrenia. To investigate the genetics of individual differences in fluid and crystallized cognitive abilities and their associations with psychiatric disorder risk, we conducted genome-wide association studies (GWAS) of a total of 335,227 consented 23andMe customers of European descent between the ages of 50 and 85, who completed at least one online test of crystallized cognitive ability (vocabulary knowledge, N=188,434) and/or fluid cognitive ability (visual change detection, N=158 888; digit-symbol substitution, N=132,807). All cognitive measures were significantly heritable (h2=0.10-0.16), and GWAS identified 25 novel genome-wide significant loci. Genetic correlation analyses highlight variable profiles of genetic relationships across tasks and disorders. While schizophrenia had moderate negative genetic correlations with tests of fluid cognition (visual change detection rg=−0.27, p<9.2e-24; digit-symbol substitution rg=−0.26, p<5.2e-27), it was only weakly negatively associated with crystalized cognition (vocabulary knowledge rg=−0.07, p<0.004). Autism, in contrast, showed a robust positive genetic correlation with vocabulary knowledge (rg=0.30, p<5.6e-13) and little to no genetic correlation with either fluid cognition task (rg’s<0.08, p’s>0.005). Crystalized and fluid cognitive abilities thus have correlated but distinct genetic architectures that relate to those of psychiatric disorders. Understanding the genetic underpinnings of specific cognitive abilities, and their relationships to psychiatric disorder risk, can inform the understanding of disease biology nosology and etiology.

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Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging

Genome Biology ◽

10.1186/s13059-021-02398-9 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Daniel L. McCartney ◽

Josine L. Min ◽

Rebecca C. Richmond ◽

Ake T. Lu ◽

Maria K. Sobczyk ◽

...

Keyword(s):

Dna Methylation ◽

Genome Wide Association Study ◽

Association Studies ◽

Genome Wide Association ◽

Biological Aging ◽

Genome Wide Association Studies ◽

Genetic Loci ◽

Biomarkers Of Aging ◽

Genome Wide ◽

Shared Genetic

Abstract Background Biological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field. Results Leveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels. Conclusion This study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.

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Genetic analysis of amyotrophic lateral sclerosis identifies contributing pathways and cell types

Science Advances ◽

10.1126/sciadv.abd9036 ◽

2021 ◽

Vol 7 (3) ◽

pp. eabd9036

Author(s):

Sara Saez-Atienzar ◽

Sara Bandres-Ciga ◽

Rebekah G. Langston ◽

Jonggeol J. Kim ◽

Shing Wan Choi ◽

...

Keyword(s):

Amyotrophic Lateral Sclerosis ◽

Membrane Trafficking ◽

Molecular Mechanisms ◽

Cell Types ◽

Polygenic Risk Score ◽

Genome Wide ◽

Genome Wide Data ◽

Data Driven Approach ◽

Single Nucleus ◽

Lateral Sclerosis

Despite the considerable progress in unraveling the genetic causes of amyotrophic lateral sclerosis (ALS), we do not fully understand the molecular mechanisms underlying the disease. We analyzed genome-wide data involving 78,500 individuals using a polygenic risk score approach to identify the biological pathways and cell types involved in ALS. This data-driven approach identified multiple aspects of the biology underlying the disease that resolved into broader themes, namely, neuron projection morphogenesis, membrane trafficking, and signal transduction mediated by ribonucleotides. We also found that genomic risk in ALS maps consistently to GABAergic interneurons and oligodendrocytes, as confirmed in human single-nucleus RNA-seq data. Using two-sample Mendelian randomization, we nominated six differentially expressed genes (ATG16L2, ACSL5, MAP1LC3A, MAPKAPK3, PLXNB2, and SCFD1) within the significant pathways as relevant to ALS. We conclude that the disparate genetic etiologies of this fatal neurological disease converge on a smaller number of final common pathways and cell types.

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Ancient genomic time transect from the Central Asian Steppe unravels the history of the Scythians

Science Advances ◽

10.1126/sciadv.abe4414 ◽

2021 ◽

Vol 7 (13) ◽

pp. eabe4414

Author(s):

Guido Alberto Gnecchi-Ruscone ◽

Elmira Khussainova ◽

Nurzhibek Kahbatkyzy ◽

Lyazzat Musralina ◽

Maria A. Spyrou ◽

...

Keyword(s):

Bronze Age ◽

Iron Age ◽

Gene Pools ◽

Social Rules ◽

Eurasian Steppe ◽

Central Asian ◽

Genome Wide ◽

Genome Wide Data ◽

History Of ◽

First Millennium

The Scythians were a multitude of horse-warrior nomad cultures dwelling in the Eurasian steppe during the first millennium BCE. Because of the lack of first-hand written records, little is known about the origins and relations among the different cultures. To address these questions, we produced genome-wide data for 111 ancient individuals retrieved from 39 archaeological sites from the first millennia BCE and CE across the Central Asian Steppe. We uncovered major admixture events in the Late Bronze Age forming the genetic substratum for two main Iron Age gene-pools emerging around the Altai and the Urals respectively. Their demise was mirrored by new genetic turnovers, linked to the spread of the eastern nomad empires in the first centuries CE. Compared to the high genetic heterogeneity of the past, the homogenization of the present-day Kazakhs gene pool is notable, likely a result of 400 years of strict exogamous social rules.

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