A review of selected candidate endophenotypes for depression

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Highlights

  • Gottesman and Gould's (2003) criteria were used to review depression endophenotypes.

  • Neuroticism, morning cortisol, CAR, and EEG frontal asymmetry had the most support.

  • Cognitive tasks lacked substantial support or necessary studies for many criteria.

  • In particular, heritability and cosegregation studies are lacking.

  • Studies of shared genetics among endophenotypes and with depression are needed.

Abstract

Endophenotypes are proposed to occupy an intermediate position in the pathway between genotype and phenotype in genetically complex disorders such as depression. To be considered an endophenotype, a construct must meet a set of criteria proposed by Gottesman and Gould (2003). In this qualitative review, we summarize evidence for each criterion for several putative endophenotypes for depression: neuroticism, morning cortisol, frontal asymmetry of cortical electrical activity, reward learning, and biases of attention and memory. Our review indicates that while there is strong support for some depression endophenotypes, other putative endophenotypes lack data or have inconsistent findings for core criteria.

Section snippets

Gottesman and Gould's criteria: a guide for empirical scrutiny

Several requirements must be met for a construct to be considered an endophenotype. Gottesman and Gould (Gottesman and Gould, 2003, Chan and Gottesman, 2008, Gould and Gottesman, 2006) originally proposed five, and later added a sixth, criteria. An endophenotype must: (1) be associated with the target illness; (2) be heritable; (3) be detectable independent of the disorder's current manifestation (however, challenges can be used to unmask the endophenotype if necessary); (4) cosegregate within

Endophenotypes and the research domain criteria

The endophenotype concept fits comfortably with the research domain criteria (RDoC; see Miller & Rockstroh, 2013). The RDoC has recently been proposed as a framework to integrate genetic and neuroscience findings to develop a pathophysiology-based classification system that is hoped to improve prevention, early intervention, and treatment outcomes (Insel et al., 2010). To this end, RDoC largely abandons the current diagnostic system and favors dimensionally measured constructs, and neural

Neuroticism

Neuroticism is characterized by a disposition to report and experience negative emotions (Eysenck, 1967). Among personality traits, neuroticism has consistently distinguished depressed and non-depressed individuals (Klein, Kotov, & Bufferd, 2011). Furthermore, depressed individuals with higher levels of neuroticism have a more chronic course, poorer treatment outcome, increased likelihood of recurrent episodes, and more frequent hospitalizations compared to depressed individuals with lower

Cortisol

Cortisol, a stress hormone that is frequently used as a marker of HPA-axis functioning, has received substantial attention in the depression literature for decades. Cortisol is relevant to depression since it is linked to lab-induced acute and chronic stress (e.g. Burke et al., 2005, Stetler and Miller, 2011) and may be a pathway for depression transmission (Halligan, Herbert, Goodyer, & Murray, 2007). Cortisol activity is appealing because it can be assessed in naturalistic contexts (e.g.

Frontal asymmetry

Another putative endophenotype is asymmetry in electrical activity in frontal regions of the scalp as measured by electroencephalography (EEG). In most studies, frontal asymmetry (FA) is assessed while participants are at rest; however some studies have examined FA in response to specific tasks. FA profiles are relevant to depression since activity in the right frontal region is thought to reflect withdrawal behavior and negative affect whereas activity in the left frontal region is

Reward learning

There is growing interest in deficits in reward processing as a putative endophenotype for depression (Bogdan, Nikolova, & Pizzagalli, 2013). Several behavioral tasks have been developed that tap into various aspects of reward (e.g. reward valuation, effort valuation/willingness to work, preference-based decision making, reward learning) and are commonly used in conjunction with imaging techniques. However, these tasks reflect very different processes, and therefore cannot be lumped together.

Cognitive endophenotypes

There are studies addressing most of the Gottesman and Gould's criteria for the depression endophenotypes reviewed thus far. The next section will focus on endophenotypes with fewer studies for many criteria. Of the many putative endophenotypes with a more limited evidence base, we chose to include attention and memory biases because of their prominent role in cognitive models of the etiology of depression (e.g. Gotlib & Joormann, 2010). Furthermore, these putative cognitive endophenotypes have

Attention biases

Attentional biases can be studied using numerous paradigms that typically involve measuring reaction time to, or time spent looking at, an emotional stimulus. Specific methodological features, such as the length of exposure to the stimuli or the use of a negative mood induction prior to the task may be important influences on the results (Gibb et al., 2009, Kujawa et al., 2011). Some might consider mood inductions as violating the state independence criteria. However, they can also be viewed as

Memory biases

Biased recall for negative material is consistently found in individuals with depression (Gotlib & Joormann, 2010). We will focus on biases in self-referential recall and overgeneral autobiographical memory, which appear to have the most relevant evidence regarding endophenotype status.

Self-referential recall is typically assessed with the self-referent encoding task (SRET), in which participants are read a list of negative and positive adjectives and asked to indicate whether or not each word

Genetic associations between endophenotypes

We have suggested that the degree of genetic overlap between a putative endophenotype and depression is a crucial consideration. However, it is also informative to explore the genetic relatedness among different endophenotypes. We would expect endophenotypes that share a large proportion of genes to implicate the same set of risk genes for depression, and endophenotypes that do not overlap would implicate different sets of risk genes. If several putative endophenotypes share significant genetic

Conclusion

We evaluated whether putative depression endophenotypes meet the required benchmarks for endophenotype status. We used Gottesman and Gould's (2003, 2006) definition of an endophenotype, which is distinct from related concepts such as biomarkers (Lenzenweger, 2013), and expanded it to include shared heritability between the endophenotype and the clinical phenotype. Hasler et al. (2004) review of putative depression endophenotypes highlighted the lack of evidence bearing on many of Gottesman and

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    This work was supported by National Institute of Mental Health grant, R01 MH069942 (Klein).

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