{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T19:26:51Z","timestamp":1788550011882,"version":"build-2803163510"},"reference-count":64,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2022,10,19]],"date-time":"2022-10-19T00:00:00Z","timestamp":1666137600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"US Army Medical Research and Development Command (USAMRDC)","award":["W911NF-13-1-0376"],"award-info":[{"award-number":["W911NF-13-1-0376"]}]},{"name":"US Army Medical Research and Development Command (USAMRDC)","award":["W911NF-17-2-0086"],"award-info":[{"award-number":["W911NF-17-2-0086"]}]},{"name":"US Army Medical Research and Development Command (USAMRDC)","award":["W911NF-18-2-0056"],"award-info":[{"award-number":["W911NF-18-2-0056"]}]},{"name":"US Army Medical Research and Development Command (USAMRDC)","award":["W911NF-17-1-0069"],"award-info":[{"award-number":["W911NF-17-1-0069"]}]},{"name":"US Army Medical Research and Development Command (USAMRDC)","award":["W81XWH-10-1-0021"],"award-info":[{"award-number":["W81XWH-10-1-0021"]}]},{"name":"US Army Medical Research and Development Command (USAMRDC)","award":["W81XWH09-2-0044"],"award-info":[{"award-number":["W81XWH09-2-0044"]}]},{"name":"US Army Medical Research and Development Command (USAMRDC)","award":["W81XWH-14-1-0043"],"award-info":[{"award-number":["W81XWH-14-1-0043"]}]},{"name":"US Army Medical Research and Development Command (USAMRDC)","award":["W81XWH-10-2-0072"],"award-info":[{"award-number":["W81XWH-10-2-0072"]}]},{"name":"US Army Medical Research and Development Command (USAMRDC)","award":["W81XWH-13-1-0071"],"award-info":[{"award-number":["W81XWH-13-1-0071"]}]},{"name":"U.S. Army Research Office","award":["W911NF-13-1-0376"],"award-info":[{"award-number":["W911NF-13-1-0376"]}]},{"name":"U.S. Army Research Office","award":["W911NF-17-2-0086"],"award-info":[{"award-number":["W911NF-17-2-0086"]}]},{"name":"U.S. Army Research Office","award":["W911NF-18-2-0056"],"award-info":[{"award-number":["W911NF-18-2-0056"]}]},{"name":"U.S. Army Research Office","award":["W911NF-17-1-0069"],"award-info":[{"award-number":["W911NF-17-1-0069"]}]},{"name":"U.S. Army Research Office","award":["W81XWH-10-1-0021"],"award-info":[{"award-number":["W81XWH-10-1-0021"]}]},{"name":"U.S. Army Research Office","award":["W81XWH09-2-0044"],"award-info":[{"award-number":["W81XWH09-2-0044"]}]},{"name":"U.S. Army Research Office","award":["W81XWH-14-1-0043"],"award-info":[{"award-number":["W81XWH-14-1-0043"]}]},{"name":"U.S. Army Research Office","award":["W81XWH-10-2-0072"],"award-info":[{"award-number":["W81XWH-10-2-0072"]}]},{"name":"U.S. Army Research Office","award":["W81XWH-13-1-0071"],"award-info":[{"award-number":["W81XWH-13-1-0071"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJMS"],"abstract":"<jats:p>Post-traumatic stress disorder (PTSD) is a highly debilitating psychiatric disorder that can be triggered by exposure to extreme trauma. Even if PTSD is primarily a psychiatric condition, it is also characterized by adverse somatic comorbidities. One illness commonly co-occurring with PTSD is Metabolic syndrome (MetS), which is defined by a set of health risk\/resilience factors including obesity, elevated blood pressure, lower high-density lipoprotein cholesterol, higher low-density lipoprotein cholesterol, higher triglycerides, higher fasting blood glucose and insulin resistance. Here, phenotypic association between PTSD and components of MetS are tested on a military veteran cohort comprising chronic PTSD presentation (n = 310, 47% cases, 83% male). Consistent with previous observations, we found significant phenotypic correlation between the various components of MetS and PTSD severity scores. To examine if this observed symptom correlations stem from a shared genetic background, we conducted genetic correlation analysis using summary statistics data from large-scale genetic studies. Our results show robust positive genetic correlation between PTSD and MetS (rg[SE] = 0.33 [0.056], p = 4.74E-09), and obesity-related components of MetS (rg = 0.25, SE = 0.05, p = 6.4E-08). Prioritizing genomic regions with larger local genetic correlation implicate three significant loci. Overall, these findings show significant genetic overlap between PTSD and MetS, which may in part account for the markedly increased occurrence of MetS among PTSD patients.<\/jats:p>","DOI":"10.3390\/ijms232012504","type":"journal-article","created":{"date-parts":[[2022,10,19]],"date-time":"2022-10-19T02:54:25Z","timestamp":1666148065000},"page":"12504","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["The Genetic Basis for the Increased Prevalence of Metabolic Syndrome among Post-Traumatic Stress Disorder Patients"],"prefix":"10.3390","volume":"23","author":[{"given":"Burook","family":"Misganaw","sequence":"first","affiliation":[{"name":"Medical Readiness Systems Biology, Center for Military Psychiatry and Neuroscience, Walter Reed Army Institute of Research, Silver Spring, MD 20910, USA"},{"name":"Vysnova Partners, Inc., Landover, MD 20785, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruoting","family":"Yang","sequence":"additional","affiliation":[{"name":"Medical Readiness Systems Biology, Center for Military Psychiatry and Neuroscience, Walter Reed Army Institute of Research, Silver Spring, MD 20910, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aarti","family":"Gautam","sequence":"additional","affiliation":[{"name":"Medical Readiness Systems Biology, Center for Military Psychiatry and Neuroscience, Walter Reed Army Institute of Research, Silver Spring, MD 20910, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seid","family":"Muhie","sequence":"additional","affiliation":[{"name":"Medical Readiness Systems Biology, Center for Military Psychiatry and Neuroscience, Walter Reed Army Institute of Research, Silver Spring, MD 20910, USA"},{"name":"The Geneva Foundation, Silver Spring, MD 20910, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Synthia H.","family":"Mellon","sequence":"additional","affiliation":[{"name":"Department of Obstetrics, Gynecology & Reproductive Sciences, University of California, San Francisco, CA 94143, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Owen M.","family":"Wolkowitz","sequence":"additional","affiliation":[{"name":"Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA 94143, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kerry J.","family":"Ressler","sequence":"additional","affiliation":[{"name":"McLean Hospital, Belmont, MA 02478, USA"},{"name":"Department of Psychiatry, Harvard Medical School, Boston, MA 02115, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3293-9114","authenticated-orcid":false,"suffix":"III","given":"Francis J.","family":"Doyle","sequence":"additional","affiliation":[{"name":"Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02134, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Charles R.","family":"Marmar","sequence":"additional","affiliation":[{"name":"Department of Psychiatry, New York University Grossman School of Medicine, New York, NY 10016, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2899-0216","authenticated-orcid":false,"given":"Marti","family":"Jett","sequence":"additional","affiliation":[{"name":"Medical Readiness Systems Biology, Center for Military Psychiatry and Neuroscience, Walter Reed Army Institute of Research, Silver Spring, MD 20910, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rasha","family":"Hammamieh","sequence":"additional","affiliation":[{"name":"Medical Readiness Systems Biology, Center for Military Psychiatry and Neuroscience, Walter Reed Army Institute of Research, Silver Spring, MD 20910, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"15057","DOI":"10.1038\/nrdp.2015.57","article-title":"Post-traumatic stress disorder","volume":"1","author":"Yehuda","year":"2015","journal-title":"Nat. Rev. Dis. Prim."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2459","DOI":"10.1056\/NEJMra1612499","article-title":"Post-traumatic stress disorder","volume":"376","author":"Shalev","year":"2017","journal-title":"N. Engl. J. Med."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"American Psychiatric Association (2013). Diagnostic and Statistical Manual of Mental Disorders (DSM-5\u00ae), American Psychiatric Pub.","DOI":"10.1176\/appi.books.9780890425596"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"593","DOI":"10.1001\/archpsyc.62.6.593","article-title":"Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication","volume":"62","author":"Kessler","year":"2005","journal-title":"Arch. Gen. Psychiatry"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1016\/j.amjmed.2005.09.027","article-title":"Posttraumatic stress disorder: Clinical features, pathophysiology, and treatment","volume":"119","author":"Vieweg","year":"2006","journal-title":"Am. J. Med."},{"key":"ref_6","unstructured":"Kulka, R.A., Schlenger, W.E., Fairbank, J.A., Hough, R.L., Jordan, B.K., Marmar, C.R., and Weiss, D.S. (1990). Trauma and the Vietnam War Generation: Report of Findings from the National Vietnam Veterans Readjustment Study, Brunner\/Mazel."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Tanielian, T., and Jaycox, L.H. (2008). Prevalence of PTSD, depression, and TBI among returning servicemembers. Invisible Wounds of War: Psychological and Cognitive Injuries, Their Consequences, and Services to Assist Recovery, RAND Corporation.","DOI":"10.1037\/e527612010-001"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.janxdis.2012.08.004","article-title":"The physical health consequences of PTSD and PTSD symptoms: A meta-analytic review","volume":"27","author":"Pacella","year":"2013","journal-title":"J. Anxiety Disord."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"926","DOI":"10.1016\/j.metabol.2015.04.009","article-title":"The prevalence and risk of metabolic syndrome and its components among people with posttraumatic stress disorder: A systematic review and meta-analysis","volume":"64","author":"Rosenbaum","year":"2015","journal-title":"Metabolism"},{"key":"ref_10","first-page":"100","article-title":"The metabolic syndrome: Definitions, prevalence and management","volume":"1","author":"Levesque","year":"2008","journal-title":"J. Nutr. Nutr."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"866","DOI":"10.1016\/j.biopsych.2018.02.007","article-title":"Metabolism, Metabolomics, and Inflammation in Posttraumatic Stress Disorder","volume":"83","author":"Mellon","year":"2018","journal-title":"Biol. Psychiatry"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/j.expneurol.2016.05.038","article-title":"Posttraumatic Stress Disorder: A Metabolic Disorder in Disguise?","volume":"284","author":"Michopoulos","year":"2016","journal-title":"Exp. Neurol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1489","DOI":"10.1126\/science.aaa8954","article-title":"Genetics and genomics of psychiatric disease","volume":"349","author":"Geschwind","year":"2015","journal-title":"Science"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/j.cpr.2013.12.002","article-title":"Etiology of depression comorbidity in combat-related PTSD: A review of the literature","volume":"34","author":"Stander","year":"2014","journal-title":"Clin. Psychol. Rev."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1186\/s40842-021-00117-8","article-title":"The relationship between depression and risk of metabolic syndrome: A meta-analysis of observational studies","volume":"7","author":"Moradi","year":"2021","journal-title":"Clin. Diabetes Endocrinol."},{"key":"ref_16","first-page":"e26523","article-title":"The Relationship Between Depression and Metabolic Syndrome: Systematic Review and Meta-Analysis Study","volume":"18","author":"Gheshlagh","year":"2016","journal-title":"Iran. Red Crescent Med. J."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1038\/s41398-021-01759-z","article-title":"The association between depression and metabolic syndrome and its components: A bidirectional two-sample Mendelian randomization study","volume":"11","author":"Zhang","year":"2021","journal-title":"Transl. Psychiatry"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"4558","DOI":"10.1038\/s41467-019-12576-w","article-title":"International meta-analysis of PTSD genome-wide association studies identifies sex-and ancestry-specific genetic risk loci","volume":"10","author":"Nievergelt","year":"2019","journal-title":"Nat. Commun."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1038\/s41588-020-00767-x","article-title":"Genome-wide association analyses of post-traumatic stress disorder and its symptom subdomains in the Million Veteran Program","volume":"53","author":"Stein","year":"2021","journal-title":"Nat. Genet."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"668","DOI":"10.1038\/s41588-018-0090-3","article-title":"Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression","volume":"50","author":"Wray","year":"2018","journal-title":"Nat. Genet."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1089\/met.2019.0070","article-title":"Genome-Wide Association Study of the Metabolic Syndrome in UK Biobank","volume":"17","author":"Lind","year":"2019","journal-title":"Metab. Syndr. Relat. Disord."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1089\/met.2013.0010","article-title":"Metabolic syndrome in people suffering from posttraumatic stress disorder: A systematic review and meta-analysis","volume":"11","author":"Bartoli","year":"2013","journal-title":"Metab. Syndr. Relat. Disord."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1001\/jamapsychiatry.2020.3436","article-title":"Dissecting the Association Between Inflammation, Metabolic Dysregulation, and Specific Depressive Symptoms: A Genetic Correlation and 2-Sample Mendelian Randomization Study","volume":"78","author":"Kappelmann","year":"2021","journal-title":"JAMA Psychiatry"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1002\/ajmg.b.32652","article-title":"Genetic correlations among psychiatric and immune-related phenotypes based on genome-wide association data","volume":"177","author":"Tylee","year":"2018","journal-title":"Am. J. Med. Genet. Part B Neuropsychiatric Genet."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1196\/annals.1314.011","article-title":"Posttraumatic stress disorder and physical illness: Results from clinical and epidemiologic studies","volume":"1032","author":"Boscarino","year":"2004","journal-title":"Ann. N. Y. Acad. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"941","DOI":"10.1534\/genetics.117.300630","article-title":"Comparison of Genotypic and Phenotypic Correlations: Cheverud\u2019s Conjecture in Humans","volume":"209","author":"Sodini","year":"2018","journal-title":"Genetics"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1016\/j.annepidem.2005.03.009","article-title":"Posttraumatic stress disorder and mortality among U.S. Army veterans 30 years after military service","volume":"16","author":"Boscarino","year":"2006","journal-title":"Ann. Epidemiol."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"858","DOI":"10.2174\/15701611113116660176","article-title":"Metabolic syndrome and cardiometabolic risk factors","volume":"11","author":"Papakonstantinou","year":"2013","journal-title":"Curr. Vasc. Pharmacol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"209S","DOI":"10.1592\/phco.26.12part2.209S","article-title":"Challenges associated with metabolic syndrome","volume":"26","author":"Spinler","year":"2006","journal-title":"Pharmacotherapy"},{"key":"ref_30","first-page":"57","article-title":"Cardiovascular consequences of metabolic syndrome","volume":"183","author":"Tune","year":"2017","journal-title":"Transl. Res. J. Lab. Clin. Med."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"683","DOI":"10.2337\/diacare.24.4.683","article-title":"Cardiovascular morbidity and mortality associated with the metabolic syndrome","volume":"24","author":"Isomaa","year":"2001","journal-title":"Diabetes Care"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Seligowski, A.V., Misganaw, B., Duffy, L.A., Ressler, K.J., and Guffanti, G. (2022). Leveraging Large-Scale Genetics of PTSD and Cardiovascular Disease to Demonstrate Robust Shared Risk and Improve Risk Prediction Accuracy. Am. J. Psychiatry, appiajp21111113.","DOI":"10.1101\/2022.07.25.22278004"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1463","DOI":"10.1016\/j.metabol.2014.08.009","article-title":"Stress- and PTSD-associated obesity and metabolic dysfunction: A growing problem requiring further research and novel treatments","volume":"63","author":"Farr","year":"2014","journal-title":"Metabolism"},{"key":"ref_34","first-page":"22710","article-title":"A Review of Posttraumatic Stress Disorder and Obesity: Exploring the Link","volume":"18","author":"Masodkar","year":"2016","journal-title":"Prim. Care Companion CNS Disord."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"847310","DOI":"10.3389\/fpsyt.2022.847310","article-title":"A Systematic Review and Meta-Analysis of Lipid Signatures in Post-traumatic Stress Disorder","volume":"13","author":"Bharti","year":"2022","journal-title":"Front. Psychiatry"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/j.psyneuen.2017.04.016","article-title":"Biological predictors of insulin resistance associated with posttraumatic stress disorder in young military veterans","volume":"82","author":"Blessing","year":"2017","journal-title":"Psychoneuroendocrinology"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1017\/S1092852913000667","article-title":"Metabolic syndrome and major depression","volume":"19","author":"Marazziti","year":"2014","journal-title":"CNS Spectr."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"63","DOI":"10.31887\/DCNS.2018.20.1\/bpenninx","article-title":"Metabolic syndrome in psychiatric patients: Overview, mechanisms, and implications","volume":"20","author":"Penninx","year":"2018","journal-title":"Dialogues Clin. Neurosci."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1002\/da.20379","article-title":"Depression and the metabolic syndrome: Gender-dependent associations","volume":"25","author":"Toker","year":"2008","journal-title":"Depress. Anxiety"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1038\/s41588-020-00751-5","article-title":"A cross-platform approach identifies genetic regulators of human metabolism and health","volume":"53","author":"Lotta","year":"2021","journal-title":"Nat. Genet."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"543","DOI":"10.1038\/ng.2982","article-title":"An atlas of genetic influences on human blood metabolites","volume":"46","author":"Shin","year":"2014","journal-title":"Nat. Genet."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Mellon, S.H., Bersani, F.S., Lindqvist, D., Hammamieh, R., Donohue, D., Dean, K., Jett, M., Yehuda, R., Flory, J., and Reus, V.I. (2019). Metabolomic analysis of male combat veterans with post traumatic stress disorder. PLoS ONE, 14.","DOI":"10.1371\/journal.pone.0213839"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1001\/jamapsychiatry.2013.4374","article-title":"Assessment of plasma C-reactive protein as a biomarker of posttraumatic stress disorder risk","volume":"71","author":"Eraly","year":"2014","journal-title":"JAMA Psychiatry"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1038\/s41467-019-13770-6","article-title":"Heritability estimates for 361 blood metabolites across 40 genome-wide association studies","volume":"11","author":"Hagenbeek","year":"2020","journal-title":"Nat. Commun."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"5765","DOI":"10.1038\/s41467-019-13544-0","article-title":"Genetic correlations of psychiatric traits with body composition and glycemic traits are sex- and age-dependent","volume":"10","author":"Gaspar","year":"2019","journal-title":"Nat. Commun."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1001\/archpsyc.1993.01820160019002","article-title":"A twin study of genetic and environmental contributions to liability for posttraumatic stress symptoms","volume":"50","author":"True","year":"1993","journal-title":"Arch. Gen. Psychiatry"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"3337","DOI":"10.1038\/s41380-019-0496-z","article-title":"Multi-omic biomarker identification and validation for diagnosing warzone-related post-traumatic stress disorder","volume":"25","author":"Dean","year":"2020","journal-title":"Mol. Psychiatry"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1038\/s41398-019-0497-3","article-title":"Polygenic risk associated with post-traumatic stress disorder onset and severity","volume":"9","author":"Misganaw","year":"2019","journal-title":"Transl. Psychiatry"},{"key":"ref_49","first-page":"75","article-title":"The development of a Clinician-Administered PTSD Scale","volume":"8","author":"Blake","year":"1995","journal-title":"J. Trauma. Stress"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1002\/jts.22059","article-title":"The Posttraumatic Stress Disorder Checklist for DSM-5 (PCL-5): Development and Initial Psychometric Evaluation","volume":"28","author":"Blevins","year":"2015","journal-title":"J. Trauma. Stress"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"5011","DOI":"10.1038\/s41380-020-0789-2","article-title":"Pre-deployment risk factors for PTSD in active-duty personnel deployed to Afghanistan: A machine-learning approach for analyzing multivariate predictors","volume":"26","author":"Schultebraucks","year":"2021","journal-title":"Mol. Psychiatry"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1038\/s41593-018-0326-7","article-title":"Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions","volume":"22","author":"Howard","year":"2019","journal-title":"Nat. Neurosci."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1470","DOI":"10.1038\/s41467-018-03819-3","article-title":"Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways","volume":"9","author":"Howard","year":"2018","journal-title":"Nat. Commun."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1534\/genetics.118.301479","article-title":"A Large Multiethnic Genome-Wide Association Study of Adult Body Mass Index Identifies Novel Loci","volume":"210","author":"Hoffmann","year":"2018","journal-title":"Genetics"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"906","DOI":"10.1038\/s41588-018-0144-6","article-title":"Mixed-model association for biobank-scale datasets","volume":"50","author":"Loh","year":"2018","journal-title":"Nat. Genet."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"2194","DOI":"10.2337\/db19-1134","article-title":"Phenotypic and Genetic Characterization of Lower LDL Cholesterol and Increased Type 2 Diabetes Risk in the UK Biobank","volume":"69","author":"Klimentidis","year":"2020","journal-title":"Diabetes"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Richardson, T.G., Leyden, G.M., Wang, Q., Bell, J.A., Elsworth, B., Davey Smith, G., and Holmes, M.V. (2022). Characterising metabolomic signatures of lipid-modifying therapies through drug target mendelian randomisation. PLoS Biol., 20.","DOI":"10.1371\/journal.pbio.3001547"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"840","DOI":"10.1038\/s41588-021-00852-9","article-title":"The trans-ancestral genomic architecture of glycemic traits","volume":"53","author":"Chen","year":"2021","journal-title":"Nat. Genet."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1038\/ng.3211","article-title":"LD Score regression distinguishes confounding from polygenicity in genome-wide association studies","volume":"47","author":"Loh","year":"2015","journal-title":"Nat. Genet."},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"1000 Genomes Project Consortium (2015). A global reference for human genetic variation. Nature, 526, 68\u201374.","DOI":"10.1038\/nature15393"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1038\/s41588-022-01017-y","article-title":"An integrated framework for local genetic correlation analysis","volume":"54","author":"Werme","year":"2022","journal-title":"Nat. Genet."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"2336","DOI":"10.1093\/bioinformatics\/btq419","article-title":"LocusZoom: Regional visualization of genome-wide association scan results","volume":"26","author":"Pruim","year":"2010","journal-title":"Bioinforma. Oxf. Engl."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"658","DOI":"10.1002\/gepi.21758","article-title":"Mendelian randomization analysis with multiple genetic variants using summarized data","volume":"37","author":"Burgess","year":"2013","journal-title":"Genet. Epidemiol."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"e34408","DOI":"10.7554\/eLife.34408","article-title":"The MR-Base platform supports systematic causal inference across the human phenome","volume":"7","author":"Hemani","year":"2018","journal-title":"eLife"}],"container-title":["International Journal of Molecular Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1422-0067\/23\/20\/12504\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:56:59Z","timestamp":1760144219000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1422-0067\/23\/20\/12504"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,19]]},"references-count":64,"journal-issue":{"issue":"20","published-online":{"date-parts":[[2022,10]]}},"alternative-id":["ijms232012504"],"URL":"https:\/\/doi.org\/10.3390\/ijms232012504","relation":{},"ISSN":["1422-0067"],"issn-type":[{"value":"1422-0067","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10,19]]}}}