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Determining Long-Term Depression Risk

Polygenic scores can provide insight into genetic predisposition for major depressive disorder, long-term risk, and recent studies suggest may also be useful for determining genetic components of resiliency.

The predisposition toward developing a mental health condition can be analyzed by quantitative means via the research tool, polygenic score (PGS).1 The state of polygenicity, as the name suggests, involves the contributing influence of multiple genes and their corresponding effects on susceptible or resilient individual. PGS are widely recognized as a standard in psychiatry and demonstrates a certain degree of predictive value in identifying individuals at risk of acquiring a disease.1 As far as major depressive disorder (MDD) is concerned, genomic-wide association (GWA) studies have examined the overlap in single nucleotide polymorphisms (SNPs) across the genome to identify genetic variants that are particular to the condition.1 It should be noted that the PGS approach draws upon these genomic studies, incorporating the individual polygenic load as it relates to variants of interest and generating an individualized profile based on genetic burdens.1 While PGS can provide further insight about risk stratification and MDD subtypes, it can also be used to determine overall resilience to the disease.1

As it stands now, PGS are a valuable investigative tool that may uncover the biological mechanisms found in psychiatric diseases.1 It lacks generalizability but can be applied readily to smaller data sets that are instrumental for hypothesis testing.1 While the application of PGS is somewhat limited in its predictive scope, an untapped potential remains for side effect sensitivity, drug-to-drug interactivity, and personalized medicine.1

MDD Heterogeneity and Stratification


As a heterogenous construct with as many as 170 distinct symptom presentations, MDD research and treatment may benefit from stratification of the condition.2 Furthermore, a host of medical and mental health illnesses are highly associated with the development of MDD, indicating the possibility of sub-diagnoses.2 These varying symptom profiles are areas to explore, and stratification of MDD allows researchers and clinicians the opportunity to better understand the underlying etiological basis of the disease with the goal of delivering targeted therapy.2

Exploring the Role of Resilience

Chronic exposure to psychosocial stressors plays an influential role in the development of MDD for susceptible individuals.3 Maladaptive stress response appears to be governed by prolonged activation of the hypothalamic–pituitary–adrenal axis (HPA axis) and autonomic nervous system (ANS).3 Despite the ubiquitous nature of stress in daily life, MDD disproportionately affects a particular demographic and is twice as prevalent in women.3 These observations underscore the importance of investigating the role of resilience (or the lack thereof) and, by extension, active coping strategies, as it relates to determinants of MDD and varying symptom presentations.3 Unfortunately, the field of resilience is relatively young, ongoing studies have been largely correlative in scope and much of the pathophysiology behind MDD is yet to be understood.3

Clinical Utility of PGS for MDD

To leverage the clinical utility of PGS for expanding our understanding of the genetic component of resilience, researchers will need to conduct comprehensive GWAS of resilience and long-term adaptive coping mechanisms.4 According to a study conducted by the Department of Psychology, University of Illinois at Urbana-Champaign, the current crop of PGS tends to lack the ability to ascertain individual variations in resilience outcomes within the context of observable mental health correlates.4 Despite setbacks in study design, it is of considerable importance to pursue a research framework that incorporates the notion of resilience with the goal of prevention and streamlined intervention in individuals with high genetic load for developing MDD.5

Recent Developments in the Resilience Frontier

The Health and Retirement Study, a longitudinal cohort study involving 2071 participants set out to explore whether composite polygenic scores in tandem with neural nets can accurately discern depression and resilience development pathways.6 Depression susceptibility and resilience were examined with respect to ongoing psychosocial stressors/events and individual trajectories were analyzed, accordingly.6 The study revealed that individuals on the resilience trajectory exhibited low PGS for metabolic disorders as well as a myriad of mental health conditions, including MDD.6  This study is relevant in providing further support for the clinical utility of PGS in determining long-term risk for depression in a relatively large sample size. While the study’s scope is somewhat limited due to inclusion of U.S participants older than 50 years from a primarily European ancestry, future cohort studies involving multivariate PGS may continue to improve our understanding of resilience by exploring other demographics of interest.



  1. Andlauer TF, Nöthen MM. Polygenic scores for psychiatric disease: from research tool to clinical application. Medizinische Genetik. 2020;32(1):39-45. Accessed August 12, 2021.
  2. Howard DM, Folkersen L, Coleman JR, et al. Genetic stratification of depression in UK Biobank. Translational psychiatry. 2020;10(1):1-8.
  3. Dudek KA, Dion‐Albert L, Kaufmann FN, Tuck E, Lebel M, Menard C. Neurobiology of resilience in depression: immune and vascular insights from human and animal studies. Eur J Neurosci. 2021;53(1):183-221. DOI: 10.1111/ejn.14547
  4. Bucknor B, Derringer J. Current Polygenic Scores Fail to Capture Resilience. 2020.
  5. Choi KW, Stein MB, Dunn EC, Koenen KC, Smoller JW. Genomics and psychological resilience: a research agenda. Mol psychiatry. 2019;24(12):1770-8.
  6. Schultebraucks K, Choi KW, Galatzer-Levy IR, Bonanno GA. Discriminating heterogeneous trajectories of resilience and depression after major life stressors using polygenic scores. JAMA psychiatry.  2021;78(7):744-752doi:10.1001/jamapsychiatry.2021.0228