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Seasonality of births in horizontal strabismus: comparison with birth seasonality in schizophrenia and other disease conditions

Published online by Cambridge University Press:  22 March 2019

A. B. Agarwal
Affiliation:
Department of Physiology & Cell Biology, University of Nevada, Reno School of Medicine, Reno, NV, USA
K. Cassinelli
Affiliation:
Sierra Eye Associates, Reno, NV, USA
L. A. Johnson
Affiliation:
Department of Physiology & Cell Biology, University of Nevada, Reno School of Medicine, Reno, NV, USA Sierra Eye Associates, Reno, NV, USA
K. Matsuda
Affiliation:
Matsuda Eye Clinic, Sennan, Osaka, Japan
B. Kirkpatrick
Affiliation:
Department of Psychiatry & Behavioral Sciences, University of Nevada, Reno School of Medicine, Reno, NV, USA
W. Yang
Affiliation:
School of Community Health Sciences, Nevada Center for Health Statistics and Informatics, University of Nevada, Reno, NV, USA
C. S. von Bartheld*
Affiliation:
Department of Physiology & Cell Biology, University of Nevada, Reno School of Medicine, Reno, NV, USA
*
Address for correspondence: C. S. von Bartheld, Department of Physiology & Cell Biology, University of Nevada, Reno School of Medicine, Reno, NV, USA. E-mail: cvonbartheld@med.unr.edu
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Abstract

Recent work has implicated one type of horizontal strabismus (exotropia) as a risk factor for schizophrenia. This new insight raises questions about a potential common developmental origin of the two diseases. Seasonality of births is well established for schizophrenia. Seasonal factors such as light exposure affect eye growth and can cause vision abnormalities, but little is known about seasonality of births in strabismus. We examined birth seasonality in people with horizontal strabismus in a retrospective study in Washoe County, Nevada, and re-examined similar previously obtained data from Osaka, Japan. We then compared seasonal patterns of births between strabismus, refractive error, schizophrenia and congenital toxoplasmosis. Patients with esotropia had a significant seasonality of births, with a deficit in March, then increasing to an excess in September, while patients with exotropia had a distinctly different pattern, with an excess of births in July, gradually decreasing to a deficit in November. These seasonalities were statistically significant with either χ2 or Kolmogorov–Smirnov-type statistics. The birth seasonality of esotropia resembled that for hyperopia, with an increase in amplitude, while the seasonality for myopia involved a phase-shift. There was no correlation between seasonality of births between strabismus and congenital toxoplasmosis. The pattern of an excess of summer births for people with exotropia was remarkably similar to the well-established birth seasonality of one schizophrenia subtype, the deficit syndrome, but not schizophrenia as a whole. This suggests a testable hypothesis: that exotropia may be a risk factor primarily for the deficit type of schizophrenia.

Information

Type
Original Article
Copyright
© Cambridge University Press and the International Society for Developmental Origins of Health and Disease 2019 
Figure 0

Fig. 1 Comparison of seasonality of births for horizontal strabismus from two different sites: data from Washoe County, Nevada (a, b), and Osaka, Japan (c, d), as previously reported,18 but without normalization to the local population. Esotropia (a, c, e); Exotropia (b, d, f). Note the similarities in the timings of peaks and troughs between the two sites. (Panel a) Esotropia births (n=2513, red squares) are shown relative to normal Washoe County births (blue dots). (Panel b) Exotropia births (n=2332, red squares) are shown relative to births in the normal Washoe County population (blue dots). (Panel c) Esotropia births from the Osaka cohort (n=3507, orange dots)18 are shown relative to the normal local birth seasonality (blue dots).35 (Panel d) Exotropia births from the Osaka cohort (n=3188, orange dots)18 are shown relative to the normal local birth seasonality (blue dots).35 Note the similarity of patterns in seasonality of births between cohorts. (Panel e) The distribution of births from the combined esotropia cohorts (Nevada and Osaka, n=6020, orange dots) are shown relative to the combined normal local variation (blue dots). The black arrow denotes the gradually increasing number of esotropia births from a trough in March to the peak in September. (Panel f) The distribution of births from the combined exotropia cohorts (Nevada and Osaka, n=5520, orange dots) are shown relative to the combined normal local variation (blue dots). The black arrow denotes the gradually decreasing number of exotropia births from a peak in July to the trough in November. Note the ‘reverse’ or ‘mirror image’ seasonality pattern between esotropia (e) and exotropia (f).

Figure 1

Fig. 2 Comparison of seasonality of births in horizontal strabismus and refractive errors: esotropia (a), exotropia (b), hyperopia (c, e), myopia (d, f). (Panels a–d) Data from subjects with strabismus or with refractive errors are shown in orange, relative to the normal local population (blue). Data for esotropia and exotropia are the combined cohorts from Nevada and Osaka.18 Data for hyperopia are from Osaka,17,35 and data for myopia are from Israel.16,45 Note that the birth distribution for esotropia (a) and hyperopia (c) is very similar, while the birth distribution for exotropia (b) and myopia (d) is not. Hyperopia and myopia birth distributions form amplitude- or phase-altered sine waves, with hyperopia increasing the amplitude of the normal seasonal variation (c, e), while myopia has the same amplitude, but is phase-shifted (precocious) by about 1 month compared with the normal seasonal variation (d, f). Hyperopia births have the minimum in spring (c, e), while myopia has the minimum in winter (d, f). The seasonality curves were modeled as sine waves in panels e (hyperopia) and f (myopia). A, amplitude; Ah, amplitude for hyperopia; An, Amplitude for normal population; αm, phase shift for myopia; αn, phase shift for normal population; P, period (=wavelength); 1/2 P, one half period. Note that a sine wave’s amplitude is defined differently than a birth seasonality’s amplitude.33

Figure 2

Fig. 3 Comparison of seasonality of births for exotropia, two types of schizophrenia, and congenital toxoplasmosis. (Panel a) Exotropia births (orange squares) compared with schizophrenia births (blue diamonds) for similar latitudes (30–39°).5 (Panel b) Comparison of births for deficit schizophrenia and non-deficit schizophrenia, compiled from four data sets.21,46 Data from Messias et al., 200421 were redrawn with permission. Note that the summer peak extends into August in at least four of the nine studies showing an excess of summer births (Table 1). Note also that the period of excess births in schizophrenia as a whole extends between December and May, with some variation, but always occurs in winter/spring. Error bars = SEM. *, data points are significantly different, P<0.01, t-test. (Panel c) Comparison of the birth seasonalities of people with exotropia (combined cohorts from Nevada and Osaka) and people with deficit schizophrenia (combined cohorts from UK, Ireland, Spain, New York and Tunisia). The graph for deficit schizophrenia was plotted as percent births per month (purple scale on left side, as in the original studies), while the exotropia graph was plotted as deviation from the mean (orange scale on right side). Note the similarities between the two seasonality graphs, and thus between the two disease conditions: exotropia and deficit schizophrenia. (Panel d) Comparison of seasonality of toxoplasmosis births22 (purple dots) and the current study’s data on exotropia (orange dots). A similar seasonality was reported in two other studies for toxoplasmosis, supporting maternal infection in winter, and an increased number of affected offspring born in spring.41,42 Note that there is no similarity between the timing of toxoplasmosis infection and exotropia births (r-value=0.0556, Pearson’s r correlation test).

Figure 3

Table 1 Studies on seasonality of births comparing deficit and non-deficit schizophrenia (SZ) in the Northern hemisphere