Local genetic correlation analysis links depression with molecular and brain imaging endophenotypes

Major depressive disorder (MDD) is a heritable psychiatric disorder which is considered one of the leading causes of disability world-wide. Improved understanding of its genetic component could inform novel treatment developments, but so far, gaining functional insights from genome-wide association studies has been difficult. In this study, we sought to generate hypotheses about plausible mechanisms through which genetic variants could influence MDD using a novel approach. Considering the cis-regions of protein coding genes as the loci of interest, we applied local genetic correlation analysis to study the genetic relationship between MDD and a range of brain, endocrine, and immune related endophenotypes across several modalities (tissue specific gene expression and splicing, regional brain volumes, and brain network connectivity). We identify significant genetic relations between MDD and endophenotypes within the cis-regions of multiple genes, and perform endophenotype specific enrichment analyses of the top associated genes. Our results offer potential mechanisms through which MDD related variants in these genomic regions could act, and convergent evidence from multiple endophenotypes implicate FLOT1 as a gene which may exhibit wide-ranging pleiotropic effects and be particularly interesting for functional follow-up. Here, we have illustrated how local genetic correlation analysis applied to lower level endophenotypes has the power to prioritise genes and functional paths which warrant further investigation for their possible role in MDD aetiology.

[1]  S. Djurovic,et al.  Charting the Landscape of Genetic Overlap Between Mental Disorders and Related Traits Beyond Genetic Correlation. , 2022, The American journal of psychiatry.

[2]  M. P. van den Heuvel,et al.  Specificity and overlap in the genetic architectures of functional and structural connectivity within cerebral resting-state networks , 2022, bioRxiv.

[3]  D. Posthuma,et al.  LAVA: An integrated framework for local genetic correlation analysis , 2021, bioRxiv.

[4]  G. Breen,et al.  Genetic architecture of 11 major psychiatric disorders at biobehavioral, functional genomic, and molecular genetic levels of analysis , 2020, Nature Genetics.

[5]  D. J. Ardesch,et al.  Statistical testing in transcriptomic‐neuroimaging studies: A how‐to and evaluation of methods assessing spatial and gene specificity , 2021, Human brain mapping.

[6]  Ming Li,et al.  Transcriptome-wide association study identifies new susceptibility genes and pathways for depression , 2021, Translational Psychiatry.

[7]  T. Andlauer,et al.  The genetic basis of major depression , 2021, Psychological Medicine.

[8]  Nadezhda T. Doncheva,et al.  The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets , 2020, Nucleic Acids Res..

[9]  Jingyun Yang,et al.  Mendelian randomization integrating GWAS and eQTL data revealed genes pleiotropically associated with major depressive disorder , 2020, Translational Psychiatry.

[10]  C. Lewis,et al.  Delineating the Genetic Component of Gene Expression in Major Depression , 2020, Biological Psychiatry.

[11]  C. Orengo,et al.  From Structure to Function , 2021, Models of the Mind.

[12]  N. Itano,et al.  Hyaluronan: Metabolism and Function , 2020, Biomolecules.

[13]  Tricia Z. King,et al.  Linking depressive symptom dimensions to cerebellar subregion volumes in later life , 2020, Translational Psychiatry.

[14]  Jordan E. Pierce,et al.  The basal ganglia and the cerebellum in human emotion , 2020, Social cognitive and affective neuroscience.

[15]  A. Mani,et al.  Screening of potential inhibitors against flotillin-1 as therapeutics for Alzheimer's disease , 2020 .

[16]  J. Hecksher-Sørensen,et al.  Circulating Triglycerides Gate Dopamine-Associated Behaviors through DRD2-Expressing Neurons. , 2020, Cell metabolism.

[17]  B. Milthorpe,et al.  Valproic Acid Promotes Early Neural Differentiation in Adult Mesenchymal Stem Cells Through Protein Signalling Pathways , 2020, Cells.

[18]  Conor Liston,et al.  Causes and Consequences of Diagnostic Heterogeneity in Depression: Paths to Discovering Novel Biological Depression Subtypes , 2020, Biological Psychiatry.

[19]  Christopher D. Brown,et al.  The GTEx Consortium atlas of genetic regulatory effects across human tissues , 2019, Science.

[20]  L. Williams,et al.  Intrinsic connectomes are a predictive biomarker of remission in major depressive disorder , 2019, Molecular Psychiatry.

[21]  Hongtu Zhu,et al.  Genome-wide association analysis of 19,629 individuals identifies variants influencing regional brain volumes and refines their genetic co-architecture with cognitive and mental health traits , 2019, Nature Genetics.

[22]  O. Andreassen,et al.  A global overview of pleiotropy and genetic architecture in complex traits , 2019, Nature Genetics.

[23]  T. Hikida,et al.  Role of basal ganglia neurocircuitry in the pathology of psychiatric disorders , 2019, Psychiatry and clinical neurosciences.

[24]  Harold Snieder,et al.  The genetics of depression: successful genome-wide association studies introduce new challenges , 2019, Translational Psychiatry.

[25]  J. Qiu,et al.  Reduced default mode network functional connectivity in patients with recurrent major depressive disorder , 2019, Proceedings of the National Academy of Sciences.

[26]  Xiao-yan Li,et al.  Integration of GWAS and brain eQTL identifies FLOT1 as a risk gene for major depressive disorder , 2019, Neuropsychopharmacology.

[27]  R. Marioni,et al.  Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions , 2018, Nature Neuroscience.

[28]  H. Sitte,et al.  Flotillin‐1 interacts with the serotonin transporter and modulates chronic corticosterone response , 2018, Genes, brain, and behavior.

[29]  Haniye Sadat Sajadi,et al.  Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017 , 2018, The Lancet.

[30]  Karl J. Friston,et al.  A brain network model for depression: From symptom understanding to disease intervention , 2018, CNS neuroscience & therapeutics.

[31]  W. Tam,et al.  Prevalence of Depression in the Community from 30 Countries between 1994 and 2014 , 2018, Scientific Reports.

[32]  P. Sachdev,et al.  Differential gene expression in brain and peripheral tissues in depression across the life span: A review of replicated findings , 2016, Neuroscience & Biobehavioral Reviews.

[33]  G. Kranz,et al.  Commentary: The serotonin transporter in depression: Meta-analysis of in vivo and post mortem findings and implications for understanding and treating depression. , 2016, Journal of affective disorders.

[34]  H. Müller,et al.  Different patterns of 5-HT receptor and transporter dysfunction in neuropsychiatric disorders – a comparative analysis of in vivo imaging findings , 2016, Reviews in the neurosciences.

[35]  O. Howes,et al.  The serotonin transporter in depression: Meta-analysis of in vivo and post mortem findings and implications for understanding and treating depression. , 2015, Journal of affective disorders.

[36]  J. Andrews-Hanna,et al.  Large-Scale Network Dysfunction in Major Depressive Disorder: A Meta-analysis of Resting-State Functional Connectivity. , 2015, JAMA psychiatry.

[37]  M. Daly,et al.  An Atlas of Genetic Correlations across Human Diseases and Traits , 2015, Nature Genetics.

[38]  Jérôme Leprince,et al.  International Union of Basic and Clinical Pharmacology. XCII. Urotensin II, Urotensin II–Related Peptide, and Their Receptor: From Structure to Function , 2015, Pharmacological Reviews.

[39]  R. Eckel,et al.  Dietary triglycerides act on mesolimbic structures to regulate the rewarding and motivational aspects of feeding , 2014, Molecular Psychiatry.

[40]  Rudolf Uher,et al.  MAJOR DEPRESSIVE DISORDER IN DSM‐5: IMPLICATIONS FOR CLINICAL PRACTICE AND RESEARCH OF CHANGES FROM DSM‐IV , 2014, Depression and anxiety.

[41]  Rupert Lanzenberger,et al.  Meta-analysis of molecular imaging of serotonin transporters in major depression , 2014, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[42]  R. Eming,et al.  Flotillins Directly Interact with γ-Catenin and Regulate Epithelial Cell-Cell Adhesion , 2013, PloS one.

[43]  R. Myers,et al.  Circadian patterns of gene expression in the human brain and disruption in major depressive disorder , 2013, Proceedings of the National Academy of Sciences.

[44]  D. Chuang,et al.  Therapeutic Potential of Mood Stabilizers Lithium and Valproic Acid: Beyond Bipolar Disorder , 2013, Pharmacological Reviews.

[45]  G. MacQueen,et al.  Cerebellar vermis volume in major depressive disorder , 2013, Brain Structure and Function.

[46]  Allan R. Jones,et al.  An anatomically comprehensive atlas of the adult human brain transcriptome , 2012, Nature.

[47]  D. Tracy,et al.  The drugs don’t work? antidepressants and the current and future pharmacological management of depression , 2012, Therapeutic advances in psychopharmacology.

[48]  B. Nichols,et al.  The roles of flotillin microdomains – endocytosis and beyond , 2011, Journal of Cell Science.

[49]  D. Steffens,et al.  Structural neuroimaging of geriatric depression. , 2011, The Psychiatric clinics of North America.

[50]  Helga Thorvaldsdóttir,et al.  Molecular signatures database (MSigDB) 3.0 , 2011, Bioinform..

[51]  J. Rothman,et al.  Flotillin-1 is essential for PKC-triggered endocytosis and membrane microdomain localization of DAT , 2011, Nature Neuroscience.

[52]  Grant Blashki,et al.  Antidepressants versus placebo for depression in primary care. , 2009, The Cochrane database of systematic reviews.

[53]  H. Vaudry,et al.  Behavioral actions of urotensin-II , 2008, Peptides.

[54]  B. Nichols,et al.  Flotillin-1 defines a clathrin-independent endocytic pathway in mammalian cells , 2006, Nature Cell Biology.

[55]  平川 聡史.  The Brain Link Protein-1 (BRAL1): cDNA Cloning,Genomic Structure, and Characterization as a Novel Link Protein Expressed in Adult Brain , 2001 .

[56]  David Nachmansohn,et al.  Metabolism and function , 1950 .