From: APA Communications [email protected]
To: Velandy Manohar, MD.,
Fri 10/22/2021 7:57 AM
Psychiatric Treatment/Disorders
Increased White Blood Cell Count May Be Tied To Increased Depression Polygenic Scores, Researchers Say
Healio (10/21, Gramigna) reports, “Increased white blood cell count appeared linked to increased depression polygenic scores, with a potential bidirectional association,” researchers concluded in a “genetic association study” that analyzed “EHR data from 382,452 participants.” The findings were published online Oct. 20 in JAMA Psychiatry.
Original Investigation
October 20, 2021
Use of the Psyche MERGE Network to Investigate the Association Between Depression Polygenic Scores and White Blood Cell Count
Julia M. Sealock, BSc1,2; Younga H. Lee, PhD3,4,5; Arden Moscati, PhD6; et alSanan Venkatesh, BSc7,8,9,10,11,12; Georgios Voloudakis, MD, PhD7,8,9,10,11,12; Peter Straub, MS1,2; Kritika Singh, BSc1,2; Yen-Chen A. Feng, PhD3,4; Tian Ge, PhD3,4; Panos Roussos, MD, PhD7,8,9,10,11,12; Jordan W. Smoller, MD, ScD3,4,5; Guanhua Chen, PhD13; Lea K. Davis, PhD1,2,14,15,16,17
Author Affiliations Article Information
JAMA Psychiatry. Published online October 20, 2021. doi:10.1001/jamapsychiatry.2021.2959
Key Points
Question: Are genes that increase predisposition to depression associated with increased inflammatory biomarkers, specifically white blood cell count?
Findings In this genetic association study of 382,485 participants, an association was noted between depression polygenic scores and white blood cell count across 4 independent biobanks. Mediation analyses suggest a bidirectional association between white blood cell count and depression diagnosis and implicate neutrophils as the main driver of the association.
Meaning These findings suggest that genes associated with depression (rather than only the clinical presentation of depressive symptoms) may be implicated in the proinflammatory state observed in clinical depression; this outcome may motivate future development of targeted biomarker panels and treatments.
Abstract
Importance Although depression is a common psychiatric disorder, its underlying biological basis remains poorly understood. Pairing depression polygenic scores with the results of clinical laboratory tests can reveal biological processes involved in depression etiology and in the physiological changes resulting from depression.
Objective To characterize the association between depression polygenic scores and an inflammatory biomarker, ie, white blood cell count.
Design, Setting, and Participants This genetic association study was conducted from May 19, 2019, to June 5, 2021, using electronic health record data from 382 452 patients across 4 health care systems. Analyses were conducted separately in each health care system and meta-analyzed across all systems. Primary analyses were conducted in Vanderbilt University Medical Center’s biobank. Replication analyses were conducted across 3 other PsycheMERGE sites: Icahn School of Medicine at Mount Sinai, Mass General Brigham, and the Million Veteran Program. All patients with available genetic data and recorded white blood cell count measurements were included in the analyses. Primary analyses were conducted in individuals of European descent and then repeated in a population of individuals of African descent.
Exposures Depression polygenic scores.
Main Outcomes and Measures White blood cell count.
Results Across the 4 PsycheMERGE sites, there were 382 452 total participants of European ancestry (18.7% female; median age, 57.9 years) and 12 383 participants of African ancestry (61.1% female; median age, 39.0 [range, birth-90.0 years]). A laboratory-wide association scan revealed a robust association between depression polygenic scores and white blood cell count (β, 0.03; SE, 0.004; P = 1.07 × 10−17), which was replicated in a meta-analysis across the 4 health care systems (β, 0.03; SE, 0.002; P = 1.03 × 10−136). Mediation analyses suggested a bidirectional association, with white blood cell count accounting for 2.5% of the association of depression polygenic score with depression diagnosis (95% CI, 2.2%-20.8%; P = 2.84 × 10−70) and depression diagnosis accounting for 9.8% of the association of depression polygenic score with white blood cell count (95% CI, 8.4%-11.1%; P = 1.78 × 10−44). Mendelian randomization provided additional support for an association between increased white blood count and depression risk, but depression modeled as the exposure showed no evidence of an influence on white blood cell counts.
Conclusions and Relevance This genetic association study found that increased depression polygenic scores were associated with increased white blood cell count, and suggests that this association may be bidirectional. These findings highlight the potential importance of the immune system in the etiology of depression and may motivate future development of clinical biomarkers and targeted treatment options for depression.
Introduction
Depression is a common psychiatric disorder estimated to affect 264 million individuals worldwide.1 Diagnostic criteria for Depression include clinical evaluation of self-reported psychiatric symptoms, such as depressed mood, irritability, anhedonia, or suicidal thoughts. In addition to psychiatric effects, depression is associated with increased risk for cardiovascular disease,2-4 autoimmune disease,5 and diabetes.6-9 The increased risk of peripheral diseases suggests the biology of depression is not limited to the brain; nevertheless, the causes and biological effects of depression in the brain and the periphery remain poorly understood.
In a health care setting, laboratory tests aid clinicians in diagnostic and treatment decision-making. Tests that can accurately and reproducibly indicate a medical state are generally referred to as biomarkers.10 To date, there are no biomarkers for depression; however, consistent with the high number of common comorbidities, depression is associated with changes in a wide range of clinical laboratory values, including increased proinflammatory cytokines,11-14 altered lipids,15-17 growth factors,18-20 and decreased brain-derived neurotrophic factor.21-24 For many of these physiological quantitative values, the underlying biological mechanisms are well understood. Further understanding of the biological link between clinical depression and these laboratory values can help identify the biological processes contributing to depression and could lead to the development of more informative biomarker panels to be used in risk assessment and treatment response.
Previous studies report a bidirectional association between depression and autoimmune disease.25 Several immune biomarkers are increased in patients with depression compared with controls, including monocytes,26-31 neutrophil-lymphocyte ratio,14,32,33 and C-reactive protein.14,31,34,35 However, most immune biomarker studies of depression are limited in sample size and scope and are often unable to control for potential confounders or determine the pathway between depression and biomarkers.
“…Although they are not currently recommended for clinical use, PGS do capture a significant proportion of the variance in depression diagnosis (1.5%-3.2%37), indicating that PGS[Polygenic Scores] represent a biologically relevant contribution to depression. In this work, we use recently developed methods38 to combine depression PGS with laboratory results stored in EHRs to robustly identify physiological processes affected by increased genetic liability to depression.”
Whereas independent biobanks can be used to discover associations, combining multiple health record systems through consortia can validate those discoveries in broader populations. The PsycheMERGE Network consists of investigators from institutions across the US with the common goal of using EHRs and biobanks to advance the identification, biology, and treatment of psychiatric disorders.39 Here, we investigate the effect of polygenic risk for depression on clinically measured laboratory values leveraging data from 4 health care systems participating in the PsycheMERGE Network.
“…Depression PGS were screened for associations with 315 clinical laboratory measurements using a LabWAS38 in VUMC’s biobank (N = 72 634). After multiple testing correction, the LabWAS of depression PGS revealed significant associations with A] 4 elevated immune markers:
- WBC (P = 1.07 × 10−17; β, 0.03; SE, 0.004),
- Urinary WBC (P = 1.45 × 10−5; β, 0.03; SE, 0.007),
- Absolute monocyte count (P = 2.54 × 10−5; β, 0.02; SE, 0.005), and
- Absolute neutrophil count (P = 5.91 × 10−5; β, 0.02; SE, 0.005).
B] Significant associations also included several metabolic markers, including
1. Increased triglycerides (P = 3.14 × 10−18; β, 0.05; SE, 0.006),
2. Decreased high-density lipoprotein cholesterol (P = 1.23 × 10−11; β, −0.04; SE, 0.005),
3. Decreased Calcitriol (P = 2.83 × 10−8; β, –0.04; SE, 0.007),
4. Increased Glucose (P = 2.84 × 10−7; β, 0.02; SE, 0.004),
5. Decreased Blood Urea Nitrogen (P = 5.19 × 10−7; β, –0.02; SE, 0.004),
6. Decreased Calcium (P = 9.74 × 10−7; β, –0.02; SE, 0.004), and
7. Decreased Calcidiol (P = 7.03 × 10−5; β, –0.04; SE, 0.01).
C. Depression PGS were also associated with
1. Decreased Troponin I (P = 1.09 × 10−6; β, −0.05; SE, 0.009),
2.Decreased Urinary Red Blood Cells (P = 1.37 × 10−5; β, −0.03; SE, 0.006),
3.Decreased Thyroxine (P = 1.72 × 10−5; β, −0.03; SE, 0.006), and
4. Decreased Blood Carbon Dioxide (P = 4.06 × 10−6; β, −0.02; SE, 0.003) (Figure 1A; eTable 1 in Supplement 2).”
In a conditional analysis, we sequentially controlled for diagnoses for depression, anxiety, adjustment reaction, and tobacco use disorder and for median body mass index across the EHR. In the analysis with all covariates, the most significant association remained WBC count (P = 1.11 × 10−10; β, 0.03; SE, 0.005), followed by triglycerides (P = 1.91 × 10−5; β, 0.04; SE, 0.008) (Figure 1B; eTables 2-6 in Supplements 3-7, respectively, and eFigures 1-2 in Supplement 1).
Although depression PGS remained robustly associated with WBC across all analyses, the magnitude of the association was modest (β, 0.03; SE, 0.004). Stratification of individuals in the discovery cohort (VUMC) showed that even at the highest decile of depression PGS, WBC measurements were elevated but remained within the clinical reference range (ie, 4-11 thousand cells/μL) (eFigur
However, the association with WBC count was in the same direction as in the European sample (P = .06; β, 0.02; SE, 0.01) (eFigure 4 in Supplement 1; eTable 8 in Supplement 9).No laboratory results were significantly associated in the LabWAS of depression PGS in individuals of African descent, likely owing to the smaller sample size of the African ancestry sample (n = 12 383) and the low generalizability of PGS built using European summary statistics in African populations.48 However, the association with WBC count was in the same direction as in the European sample.
“…The association between depression PGS and WBC count remained significant after controlling for each group separately and controlling for all phenotype groups together (P = 4.19 × 10−3; β, 0.02; SE, 0.008) with effect estimates similar to the original association despite the reduced sample size (N = 13 269).”
Discussion
Depression is consistently associated with increased proinflammatory biomarkers; however, the mechanisms underlying these associations remain unclear. In this genetic association study, analysis of EHR-linked biobanks within the PsycheMERGE Network were used to examine the association between depression PGS and a variety of clinical laboratory traits, revealing a robustly replicated association with increased WBC count. Notably, several other laboratory traits were associated with depression PGS, including Lipids, Blood glucose, and Blood urea nitrogen. The variety of associations with Depression PGS suggest that multiple areas of biology are affected by depression genetics, including Metabolism49,50 and Inflammation.50-52 We chose to further investigate the association with WBC count given the existing literature and the robustness of the observed association with clinical confounders.
In a laboratory-wide screen, increased polygenic depression risk was associated with increased inflammatory markers, including WBC count, even after controlling for depression, anxiety, multiple comorbid phenotypes, body mass index, and smoking, thus suggesting that depression PGS was an important risk factor for the proinflammatory state observed in depression. These results suggested that genetic risk for depression, independent of depressive symptoms, was linked to a proinflammatory biomarker. The association of the depression PGS with WBC was modest across all biobanks, suggesting that individuals with high depression genetic liability may have an activated but not abnormal immune system. Nonetheless, sustained activation of the immune system could have important implications for the risk of developing depression.
There are 2 main models that connect Depression to a Proinflammatory state: the Neuroinflammation model and the Stress Response model.
The Neuroinflammation model hypothesizes that an activated immune system contributes to risk of developing depression.53,54
The Stress Response model proposes the stress of Depression symptoms leads to a proinflammatory state.55,56
Importantly, these 2 models are not mutually exclusive, and some have suggested they form a feedback loop.57,58 In support of this hypothesis, our mediation results do not distinguish either the Neuroinflammation model or the Stress Response model as the exclusive pathway between depression and WBC count.
However, Mendelian randomization results supported a potential causal path from increased WBC levels to increased depression risk, consistent with the Neuroinflammation model; BUT DID NOT SUPPORT A MODEL OF DEPRESSION LEADING TO INCREASED WBC LEVELS. It is important to note that only 47 SNVs met criteria to be included as depression instrument variables, limiting the statistical power of the analysis.
In the clinic, WBC measurements can be broken down into measurements of each WBC subtype. Abnormal levels of different WBC subtypes can index different immune processes. Understanding which cell types underlie the relationship between depression PGS and Depression diagnosis through WBC can help narrow a specific immune process involved in depression.
Neutrophil counts explained 1.9% of the association between Depression PGS and Depression diagnosis, and no other subtypes contributed to the association. Neutrophils are well known as responders to acute bacterial infection59 and are the most abundant WBC subtype in circulation (40%-60%).59 Recent evidence demonstrates that neutrophils have essential roles in innate and adaptive immunity,60 are implicated in diseases of chronic inflammation,61 and are experimentally shown to transmigrate into intact mouse brain to deliver interleukin 1β, resulting in depressive behavioral change.62
“…Therefore, we emphasize that the PGS approach is still fundamentally an association. Third, results are based on genetic studies of primarily European ancestry populations and may not generalize across diverse ancestries. Fourth, while pleiotropy was assessed in the mendelian randomization analyses, possible unknown sources of confounding (such as those mentioned in the description of “phenotypic hitchhiking”) were not assessed.
Finally, even though the association between depression PGS and WBC count was robust, the effect sizes were small, making WBC count an unlikely candidate for use as a diagnostic biomarker of depression.”
References
1.
James SL, et al; GBD 2017 Disease and Injury Incidence and Prevalence Collaborators. 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. Lancet. 2018;392(10159):1789-1858. doi:10.1016/S0140-6736(18)32279-7PubMedGoogle ScholarCrossref
2.
Brown DW, Giles WH, Croft JB. White blood cell count: an independent predictor of coronary heart disease mortality among a national cohort. J Clin Epidemiol. 2001;54(3):316-322. doi:10.1016/S0895-4356(00)00296-1PubMedGoogle ScholarCrossref
3.
Hare DL, Toukhsati SR, Johansson P, Jaarsma T. Depression and cardiovascular disease: a clinical review. Eur Heart J. 2014;35(21):1365-1372. doi:10.1093/eurheartj/eht462PubMedGoogle ScholarCrossref
4.
Musselman DL, Evans DL, Nemeroff CB. The relationship of depression to cardiovascular disease: epidemiology, biology, and treatment. Arch Gen Psychiatry. 1998;55(7):580-592. doi:10.1001/archpsyc.55.7.580
ArticlePubMedGoogle ScholarCrossref
5.
Benros ME, Waltoft BL, Nordentoft M, et al. Autoimmune diseases and severe infections as risk factors for mood disorders: a nationwide study. JAMA Psychiatry. 2013;70(8):812-820. doi:10.1001/jamapsychiatry.2013.1111
ArticlePubMedGoogle ScholarCrossref
6.
Anderson RJ, Freedland KE, Clouse RE, Lustman PJ. The prevalence of comorbid depression in adults with diabetes: a meta-analysis. Diabetes Care. 2001;24(6):1069-1078. doi:10.2337/diacare.24.6.1069PubMedGoogle Scholar
7.
Gkrania-Klotsas E, Ye Z, Cooper AJ, et al. Differential white blood cell count and type 2 diabetes: systematic review and meta-analysis of cross-sectional and prospective studies. PLoS One. 2010;5(10):e13405. doi:10.1371/journal.pone.0013405PubMedGoogle Scholar
8.
Mezuk B, Eaton WW, Albrecht S, Golden SH. Depression and type 2 diabetes over the lifespan: a meta-analysis. Diabetes Care. 2008;31(12):2383-2390. doi:10.2337/dc08-0985PubMedGoogle ScholarCrossref
9.
Shim WS, Kim HJ, Kang ES, et al. The association of total and differential white blood cell count with metabolic syndrome in type 2 diabetic patients. Diabetes Res Clin Pract. 2006;73(3):284-291. doi:10.1016/j.diabres.2006.02.001PubMedGoogle ScholarCrossref
11. Dowlati Y, Herrmann N, Swardfager W, et al. A meta-analysis of cytokines in major depression. Biol Psychiatry. 2010;67(5):446-457. doi:10.1016/j.biopsych.2009.09.033PubMedGoogle ScholarCrossref
12.
Dinan TG. Inflammatory markers in depression. Curr Opin Psychiatry. 2009;22(1):32-36. doi:10.1097/YCO.0b013e328315a561PubMedGoogle ScholarCrossref
13.
Howren MB, Lamkin DM, Suls J. Associations of depression with C-reactive protein, IL-1, and IL-6: a meta-analysis. Psychosom Med. 2009;71(2):171-186. doi:10.1097/PSY.0b013e3181907c1bPubMedGoogle ScholarCrossref
21.
Aydemir C, Yalcin ES, Aksaray S, et al. Brain-derived neurotrophic factor (BDNF) changes in the serum of depressed women. Prog Neuropsychopharmacol Biol Psychiatry. 2006;30(7):1256-1260. doi:10.1016/j.pnpbp.2006.03.025PubMedGoogle ScholarCrossref
2.
Molendijk ML, Bus BA, Spinhoven P, et al. Serum levels of brain-derived neurotrophic factor in major depressive disorder: state-trait issues, clinical features and pharmacological treatment. Mol Psychiatry. 2011;16(11):1088-1095. doi:10.1038/mp.2010.98PubMedGoogle ScholarCrossref
23.
Dwivedi Y. Brain-derived neurotrophic factor: role in depression and suicide. Neuropsychiatr Dis Treat. 2009;5:433-449. doi:10.2147/NDT.S5700PubMedGoogle Scholar
24.
Castrén E, Rantamäki T. The role of BDNF and its receptors in depression and antidepressant drug action: reactivation of developmental plasticity. Dev Neurobiol. 2010;70(5):289-297. doi:10.1002/dneu.20758PubMedGoogle ScholarCrossref
25.
Euesden J, Danese A, Lewis CM, Maughan B. A bidirectional relationship between depression and the autoimmune disorders—new perspectives from the National Child Development Study. PLoS One. 2017;12(3):e0173015. doi:10.1371/journal.pone.0173015PubMedGoogle Scholar
Kayhan F, Gündüz Ş, Ersoy SA, Kandeğer A, Annagür BB. Relationships of neutrophil-lymphocyte and platelet-lymphocyte ratios with the severity of major depression. Psychiatry Res. 2017;247:332-335. doi:10.1016/j.psychres.2016.11.016PubMedGoogle ScholarCrossref
33.
Demir S, Atli A, Bulut M, et al. Neutrophil-lymphocyte ratio in patients with major depressive disorder undergoing no pharmacological therapy. Neuropsychiatr Dis Treat. 2015;11:2253-2258.PubMedGoogle Scholar
34.
De Berardis D, Campanella D, Gambi F, et al. The role of C-reactive protein in mood disorders. Int J Immunopathol Pharmacol. 2006;19(4):721-725. doi:10.1177/039463200601900402PubMedGoogle ScholarCrossref
35.
Kappelmann N, Arloth J, Georgakis MK, et al. Dissecting the association between inflammation, metabolic dysregulation, and specific depressive symptoms: a genetic correlation and 2-sample mendelian randomization study. JAMA Psychiatry. 2021;78(2):161-170. doi:10.1001/jamapsychiatry.2020.3436
Troubat R, Barone P, Leman S, et al. Neuroinflammation and depression: a review. Eur J Neurosci. 2021;53(1):151-171. doi:10.1111/ejn.14720PubMedGoogle Scholar
54.
Raison CL, Capuron L, Miller AH. Cytokines sing the blues: inflammation and the pathogenesis of depression. Trends Immunol. 2006;27(1):24-31. doi:10.1016/j.it.2005.11.006PubMedGoogle ScholarCrossref
55.
Olff M. Stress, depression and immunity: the role of defense and coping styles. Psychiatry Res. 1999;85(1):7-15. doi:10.1016/S0165-1781(98)00139-5PubMedGoogle ScholarCrossref
Bao AM, Swaab DF. The human hypothalamus in mood disorders: the HPA axis in the center. IBRO Rep. 2018;6:45-53. doi:10.1016/j.ibror.2018.11.008PubMedGoogle ScholarCrossref
57.
Finnell JE, Wood SK. Neuroinflammation at the interface of depression and cardiovascular disease: evidence from rodent models of social stress. Neurobiol Stress. 2016;4:1-14. doi:10.1016/j.ynstr.2016.04.001PubMedGoogle ScholarCrossref
58.
Hurley LL, Tizabi Y. Neuroinflammation, neurodegeneration, and depression. Neurotox Res. 2013;23(2):131-144. doi:10.1007/s12640-012-9348-1PubMedGoogle ScholarCrossref
Soehnlein O, Steffens S, Hidalgo A, Weber C. Neutrophils as protagonists and targets in chronic inflammation. Nat Rev Immunol. 2017;17(4):248-261. doi:10.1038/nri.2017.10PubMedGoogle ScholarCrossref
62.
Aguilar-Valles A, Kim J, Jung S, Woodside B, Luheshi GN. Role of brain transmigrating neutrophils in depression-like behavior during systemic infection. Mol Psychiatry. 2014;19(5):599-606. doi:10.1038/mp.2013.137PubMedGoogle ScholarCrossref