Polygenic risk for immuno-metabolic markers and specific depressive symptoms: A multi-sample network analysis study

Abstract

BackgroundAbout every fourth patient with major depressive disorder (MDD) shows evidence of systemic inflammation. Previous studies have shown inflammation-depression associations of multiple serum inflammatory markers and multiple specific depressive symptoms. It remains unclear, however, if these associations extend to genetic/lifetime predisposition to higher inflammatory marker levels and what role metabolic factors such as Body Mass Index (BMI) play. It is also unclear whether inflammation-symptom associations reflect direct or indirect associations, which can be disentangled using network analysis.MethodsThis study examined associations of polygenic risk scores (PRSs) for immuno-metabolic markers (C-reactive protein [CRP], interleukin [IL]-6, IL-10, tumour necrosis factor [TNF]-α, BMI) with seven depressive symptoms in one general population sample, the UK Biobank study (n=110,010), and two patient samples, the Munich Antidepressant Response Signature (MARS, n=1,058) and Sequenced Treatment Alternatives to Relieve Depression (STAR*D, n=1,143) studies. Network analysis was applied jointly for these samples using fused graphical least absolute shrinkage and selection operator (FGL) estimation as primary analysis and, individually, using unregularized model search estimation. Stability of results was assessed using bootstrapping and three quality criteria were defined to appraise consistency of results across estimation methods, network bootstrapping, and samples.ResultsNetwork analysis results displayed to-be-expected PRS-PRS and symptom-symptom associations (termed edges), respectively, that were mostly positive. Using FGL estimation, results further suggested 28, 29, and six PRS-symptom edges in MARS, STAR*D, and UK Biobank samples, respectively. Unregularized model search estimation suggested three PRS-symptom edges in the UK Biobank sample. Applying our quality criteria to these associations indicated that only the association of higher CRP PRS with greater changes in appetite fulfilled all three criteria. Four additional associations fulfilled at least two quality criteria; specifically, higher CRP PRS was associated with greater fatigue and reduced anhedonia, higher TNF-α PRS was associated with greater fatigue, and higher BMI PRS with greater changes in appetite and anhedonia. Associations of the BMI PRS with anhedonia, however, showed an inconsistent valence across estimation methods.ConclusionsOur findings align with previous studies suggesting that systemic inflammatory markers are primarily associated with somatic/neurovegetative symptoms of depression such as changes in appetite and fatigue. We extend these findings by providing evidence that associations are direct (using network analysis) and extend to genetic predisposition to immuno-metabolic markers (using PRSs). Our findings can inform selection of patients with inflammation-related symptoms into clinical trials of immune-modulating drugs for MDD.

Circulating Inflammation Markers Partly Explain the Link Between the Dietary Inflammatory Index and Depressive Symptoms

“… 41 In keeping with these findings, polygenic scores influencing higher CRP levels were positively associated with increasing altered appetite and fatigue (along with TNF-α), suggesting that genetic predisposition to higher systemic inflammatory markers are primarily associated with somatic/neurovegetative symptoms of depression. 42 This evidence was supported by a multi-sample network analysis in depressed and general population cohorts, and is also consistent with previous observational studies on circulating inflammation markers in population cohorts. 7 , 43 Moreover, Mendelian randomization analyses suggested a causal effect of increased CRP on somatic symptoms (appetite alterations, tiredness/fatigue and psychomotor changes), and of IL-6 on cognitive symptoms (suicidality).…”

Network analysis of psychological distress, posttraumatic stress and fear symptoms by COVID-19 in Peruvian adults

“…Estas condiciones pueden generar un aumento de los componentes del sistema inmunitario como las citoquinas proinflamatorias que afianzan una mayor angustia psicológica, especialmente una mayor concurrencia de depresión como el presente estudio. Por lo tanto, la inclusión de modelos de red compuestos por síntomas con medidas bioquímicas permite ampliar otras (34) rutas de investigación ante el contexto de COVID-19 , siendo recomendable considerar estudios (35,36,37) recientes de red para futuras investigaciones.…”

Network analysis in clinical research

“…Fried et al 13 publicaron otro estudio que evaluó redes simultaneas antes y después del control de covariables; allí se incluyeron medidas bioquímicas (marcadores inflamatorios), antropométricas y psicológicas para precisar aquellas variables de mayor influencia causal en la red. Asimismo, en los análisis de redes se ha reportado el uso de otras medidas clínicas como las neuropsiquiátricas, 14 las neuroanatómicas 15 y las genómicas, 16,17 así como la inclusión de factores de riesgo y protección. 18 En la actualidad se viene impulsando el estudio de múltiples entidades clínicas relacionadas con el impacto negativo de la pandemia por COVID-19, tales como miedo, angustia y estrés, 12,19 y en 2021 ya se han publicado dos artículos que emplean el análisis de redes en Sudamérica en este contexto; 19,20 sin embargo, aún urge una mayor divulgación y capacitación sobre este enfoque para fomentar su uso general en la investigación de las ciencias de la salud.…”