Endophenotype best practices

Abstract

This review examines the current state of electrophysiological endophenotype research and recommends best practices that are based on knowledge gleaned from the last decade of molecular genetic research with complex traits. Endophenotype research is being oversold for its potential to help discover psychopathology relevant genes using the types of small samples feasible for electrophysiological research. This is largely because the genetic architecture of endophenotypes appears to be very much like that of behavioral traits and disorders: they are complex, influenced by many variants (e.g., tens of thousands) within many genes, each contributing a very small effect. Out of over 40 electrophysiological endophenotypes covered by our review, only resting heart, a measure that has received scant advocacy as an endophenotype, emerges as an electrophysiological variable with verified associations with molecular genetic variants. To move the field forward, investigations designed to discover novel variants associated with endophenotypes will need extremely large samples best obtained by forming consortia and sharing data obtained from genome wide arrays. In addition, endophenotype research can benefit from successful molecular genetic studies of psychopathology by examining the degree to which these verified psychopathology-relevant variants are also associated with an endophenotype, and by using knowledge about the functional significance of these variants to generate new endophenotypes. Even without molecular genetic associations, endophenotypes still have value in studying the development of disorders in unaffected individuals at high genetic risk, constructing animal models, and gaining insight into neural mechanisms that are relevant to clinical disorder.

Psychophysiological endophenotypes to characterize mechanisms of known schizophrenia genetic loci

“…While antisaccade and P300 are convincing putative endophenotypes in schizophrenia and EEG and electrodermal measures have also received significant support, multiple promising putative endophenotypes for schizophrenia were not available in the present research (Allen et al 2009). Some of these endophenotypes may be associated with genetic loci of substantially larger effect sizes than any of our 17, although there is little evidence that psychophysiological or imaging-based endophenotypes are associated with larger effects than other complex traits and diseases (Iacono et al 2016). Despite the fact that our study could not definitively test all candidate endophenotypes in schizophrenia, we suggest that our findings indicate that mechanism studies of the present kind will not be effective in community samples of the size investigated here, because none of the variants known to be associated with clinical outcome has any appreciable association with any of the endophenotypes.…”

“…We have also argued previously that to qualify as an endophenotype, v . a putative endophenotype, the laboratory-based measure should also show robust and reliable associations with genetic variants through genetic association studies (Iacono et al 2016). Endophenotypes are also thought to be more genetically homogeneous than their associated clinical outcomes (Cannon & Keller, 2006), and so effects of individual genetic variants on endophenotypes are suspected to be larger and possibly easier to detect than the effect of those variants on the clinical outcome.…”

“…To answer this question, we took the results from a recent schizophrenia genetic association meta-analysis by the Psychiatric Genomics Consortium (PGC), which discovered 128 independent genetic variants in 108 genomic loci associated with schizophrenia (Schizophrenia Working Group of the Psychiatric Genomics Consortium, 2014), and tested them for association with the same 17 endophenotypes described above. Many of these endophenotypes have demonstrated substantial construct validity as endophenotypes for schizophrenia (Iacono et al 2016); others less so, but nevertheless have been associated with schizophrenia, found to be heritable in twin studies, and show deviation in schizophrenia patient first-degree relatives (Fukushima et al 1988; Braff et al 1992; Iacono et al 1999; Hong et al 2012; Kam et al 2013; Chen et al 2014; Narayanan et al 2014; Qiu et al 2014). The only two endophenotypes that have not been linked to schizophrenia are our measures of affectively modulated startle (Iacono et al 2016).…”

Testing the effects of adolescent alcohol use on adult conflict-related theta dynamics

“…The current report provides, to the best of our knowledge, the first evidence that adolescent drinking is related to reduced adult theta-band processes during demands of cognitive control, and that a premorbid genetic risk towards early alcohol use, and not the direct causal effect of alcohol exposure, likely underlies the relationship between adolescent drinking and diminished adult theta dynamics. As such, deviations in theta dynamics appear to possess key characteristics required of an endophenotype for AAU (Iacono et al, 2016). Should genetic variants associated with theta dynamics be identified, our findings have the potential to provide insights into how these variants are related to brain function associated with AAU liability.…”

A genome wide association study of fast beta EEG in families of European ancestry

“…Given these associations, and the high degree of genetic influence observed (Malone et al, 2014; van Beijsterveldt et al, 1996), beta EEG has been proposed as a useful endo-phenotype (Gottesman and Gould, 2003) for identifying genetic risk factors for disorders characterized by disinhibitory traits (Edenberg et al, 2004; Porjesz et al, 2002). Despite the promise of the endo-phenotype concept however, the genetic complexity of resting-state EEG (Malone et al, 2014), coupled with the scant number of replicable and/or clinically useful genetic variants uncovered by this approach (Iacono et al, 2016), has necessitated large scale genetic association studies of beta EEG, utilizing best-practices in genetic epidemiology.…”