H.H. Stassen, J. Katsanis, S. Malone, W.G. Iacono
Human brain wave patterns (EEG) represent complex traits as is illustrated by the fact that the inheritance does not follow simple mendelian modes in the great majority of parameters used to quantify EEG characteristics. The only exception might be the low-voltage EEG that is characterized by the absence of an alpha rhythm in the resting EEG and that is hypothesized to be an autosomal-dominant trait (Vogel 1986; Anokhin et al. 1992; Steinlein et al. 1992a, b). Although single parameter models do not readily yield insights into the mode of inheritance of EEG characteristics, there is convincing evidence from studies on monozygotic (MZ) and dizygotic (DZ) twins, that the inter-individual variability of the human EEG under "normal" conditions is largely genetically determined (e.g. Young et al. 1972; Propping et al. 1980; Stassen 1980; Lykken et al. 1982; Stassen 1985; Vogel 1986; Baier and Dose 1987; Christian et al. 1988; Stassen et al. 1988a; Linkowski et al. 1989; Fujiwara et al. 1990; Meshkova 1992; Beijsterveldt and Boomsma 1994). In fact, quantitative analysis of the static component of the human EEG on the basis of twins brought up together and reared apart (Stassen et al. 1988b) yielded conclusive proof that the variance in individual resting EEG patterns is predominantly determined by hereditary factors: we found a heritability coefficient h2=0.825 for adolescents ranging in age from 9 to 12 years (reared together), a heritability coefficient h2=0.761 for adults between 20 and 35 years old (reared together), and a heritability coefficient h2=0.719 for adults aged 21 to 65 years (reared apart). The corresponding quotients rDZ/rMZ of within-pair DZ and within-pair MZ similarities were with 0.499, 0.452 and 0.598 not too far from the theoretical value of 0.5 of the polygenic-additive model (Stassen et al. 1993). Regrettably, the number of twin pairs available in these studies was far too small to allow for sufficiently narrow confidence intervals for conclusive inference about the underlying population parameters and related genetic models. The much larger sample size of the MTFS project will allow us to get estimates at a much higher accuracy and consequently, will allow us to check the validity of the additive model.
Our interest in the present twin/family study has a psychiatric background. That is, we think that investigations into the heritability of brain wave patterns might contribute to a better understanding of the complex familial aggregations of psychic illnesses. Indeed, methods of quantitative genetics applied in a large number of empirical studies have demonstrated that psychiatric diagnoses (used to define phenotypes) are not "elementary" but "emergenic" traits, i.e. traits that do not "run" in families. And at present it is still an unresolved issue of how to break down the phenotypic heterogeneity of psychiatric disease entities, and of how to tease apart the underlying multifactorial causes.
Both psychic illnesses and brain wave patterns exhibit a similar complexity on the trait level. However, unlike psychic illnesses, brain wave patterns are "objectively" assessable, i.e. in a rater-independent way and in a standardized experimental setting.
Our sample consists of >50 MZ, >150 DZ same sex twin pairs together with their parents. Of these probands 5 minutes of resting EEG derived from 3/5 parallel channels will be transferred to Zurich, re-calibrated, plotted, and inspected visually for artifacts (e.g. body movements, eye blinks, muscle potentials, loose electrodes) taking advantage of the many years of the Zurich laboratory expertise. Finally, time-series will be Fourier-transformed, stored in a data bank and re-transferred to Minneapolis. Subsequent analyses are based on the frequency bands 0-3.75 Hz, 3.75-7.5 Hz, 7.5-15 Hz, 15-30 Hz and include the single-valued parameters Absolute power, Relative power, Centroid, Symmetry, Peak amplitude, Peak frequency as well as multivariate spectral patterns which have proven to measure the fine graduations of inter-individual EEG differences together with the intra-individual stability of brain wave patterns over time.
The large number of DZ pairs are required in order to get reliable estimates of within-pair correlations which are expected to lie somewhere between 0.3 and 0.4 (e.g. 40 DZ pairs are required to confirm that an observed within-pair correlation of r=0.35 is significantly greater than zero at the 5% level). In other words, sufficiently large samples are required if within-pair DZ correlations are to be computed with sufficient precision.
A study of 24 families comprising index cases, siblings, parents and grandparents will serve as control group in order to verify intra- familial correlations, and a study of 90 healthy volunteers (ages 20-35) with repeated assessments at 14- day intervals will serve as control group with respect to the stability of EEG parameters over time.
In this project we aim to quantify the intra-familial phenotypic heterogeneity of EEG characteristics. In particular, we aim to ascertain the nature of single-valued or multivariate phenotypes:
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