A polygenic predictor of treatment-resistant depression using whole exome sequencing and genome-wide genotyping

Abstract

Treatment-resistant depression (TRD) occurs in~30% of patients with major depressive disorder (MDD) but the genetics of TRD was previously poorly investigated. Whole exome sequencing and genome-wide genotyping were available in 1209 MDD patients after quality control. Antidepressant response was compared to non-response to one treatment and non-response to two or more treatments (TRD). Differences in the risk of carrying damaging variants were tested. A score expressing the burden of variants in genes and pathways was calculated weighting each variant for its functional (Eigen) score and frequency. Gene-based and pathway-based scores were used to develop predictive models of TRD and non-response using gradient boosting in 70% of the sample (training) which were tested in the remaining 30% (testing), evaluating also the addition of clinical predictors. Independent replication was tested in STAR*D and GENDEP using exome array-based data. TRD and non-responders did not show higher risk to carry damaging variants compared to responders. Genes/pathways associated with TRD included those modulating cell survival and proliferation, neurodegeneration, and immune response. Genetic models showed significant prediction of TRD vs. response and they were improved by the addition of clinical predictors, but they were not significantly better than clinical predictors alone. Replication results were driven by clinical factors, except for a model developed in subjects treated with serotonergic antidepressants, which showed a clear improvement in prediction at the extremes of the genetic score distribution in STAR*D. These results suggested relevant biological mechanisms implicated in TRD and a new methodological approach to the prediction of TRD.

Genetics and major depressive disorder: clinical implications for disease risk, prognosis and treatment

“…Pathway analysis led to the identification of several biological mechanisms that mediate depression and antidepressant action. These can be grouped in some main clusters: axonal development, neuron differentiation and morphogenesis, neural-plasticity, excitatory neurotransmission, cytokines, immune response and regulation of gene expression ( Zeng et al , 2017 ; Wray et al , 2018 ; Howard et al , 2018 ; Fabbri et al , 2019a ).…”

“…Despite a probable neurodevelopmental component in a subgroup of cases, genetic studies provided quite convincing evidence that MDD pathogenesis and antidepressant action mostly involve modifications of neural-plasticity and neurotransmission, which are controlled by changes in gene expression patterns and influenced by the activity of the immune system ( Calabrese et al , 2014 ). In terms of specific pathways, association signals came from those modulating long-term potentiation, a persistent increase in synaptic strength following high-frequency synaptic stimulation, and second messengers mediating the cellular events activated by neurotrophins such as brain-derived neurotrophic factor ( BDNF ) ( Hunter et al , 2013 ; Fabbri et al , 2019a ). Excitatory neurotransmission is a key regulator of neural plasticity and neural survival, and in the central nervous system, the most common excitatory neurotransmitter is glutamate.…”

“…the structure formed by DNA and proteins that constitutes chromosomes) has a tridimensional structure that varies over time in response to a variety of stimuli, such as neurotransmitters, growth factors, neuropeptides ( Ou et al , 2017 ), which can be modulated by antidepressant treatments. Pathways modulating chromatin structure have been associated with depression, antidepressant response and animal models showed that downregulation of histone deacetylase (an enzyme modulating chromatin structure) in the hippocampus has antidepressant-like effect ( Tsankova et al , 2006 ; Network and Pathway Analysis Subgroup of Psychiatric Genomics Consortium, 2015 ; Fabbri et al , 2019a ).…”

“…Few studies used WES in MDD, in relatively small samples (e.g. Tombácz et al , 2017 ; Zhang et al , 2019 ), and only two studies are available for antidepressant response, of which one was performed on 10 subjects ( Tammiste et al , 2013 ), while the other on ~1200 subjects ( Fabbri et al , 2019b ). Thus, the contribution of rare variants to these traits is largely unknown and difficult to explore since the relatively smaller samples analyzed compared to other psychiatric traits.…”

Pharmacogenetics in Psychiatry: An Update on Clinical Usability

“…Of course this poses another challenge, as to assign a clinical relevance to rare variants identified that have not previously been characterized. Recent evidence suggests that bioinformatic tools may successfully be applied to NGS (Fabbri et al, 2020a). Specific programs that can be used for this are Aldy, Astrolable, and Stargazer.…”