Reproduction and genetic causal attribution of epilepsy

Abstract

Objective:

This study addresses the contribution of genetics-related concerns to reduced childbearing among people with epilepsy.

Methods:

Surveys were completed by 606 adult patients with epilepsy of unknown cause at our medical center. Poisson regression analysis was used to assess the relations of number of offspring to: (1) genetic attribution (GA: participants’ belief that genetics was a cause of their epilepsy), assessed via a novel scale developed from four survey items (Cronbach’s alpha = .89), (2) participants’ estimates of epilepsy risk in the child of a parent with epilepsy (1%, 5%–10%, 25%, and 50%–100%), and (3) participants’ reports of the influence on their reproductive decisions of “the chance of having a child with epilepsy” (none/weak/moderate, strong/very strong). Analyses were adjusted for age, education, race/ethnicity, religion, type of epilepsy (generalized, focal, and both/unclassifiable), and age at epilepsy onset (<10, 10–19, and ≥20 years).

Results:

Among participants 18–45 years of age, the number of offspring decreased significantly with increasing GA (highest vs lowest GA quartile rate ratio [RR] = .5, p < .001), and increasing estimated epilepsy risk in offspring (with 5%–10% as referent because it is closest to the true value, RR for 25%: .7, p = .05; RR for 50%–100%: .6, p = .03). Number of offspring was not related to the reported influence of “the chance of having a child with epilepsy” on reproductive decisions. Among participants >45 years of age, the number of offspring did not differ significantly according to GA quartile or estimated offspring epilepsy risk. However, those reporting a strong/very strong influence on their reproductive decisions of “the chance of having a child with epilepsy” had only 60% as many offspring as others.

Significance:

These findings suggest that overestimating the risk of epilepsy in offspring can have important consequences for people with epilepsy. Patient and provider education about recurrence risks and genetic testing options to clarify risks are critical, given their potential influence on reproductive decisions.

1 |. INTRODUCTION

Strong evidence from both population-based^1–5 and other studies^6–9 shows that birth rates are lower among persons with epilepsy than in the general population. Possible reasons for this reduced reproduction include the biological effects of epilepsy or antiseizure medications (ASMs) on reproductive hormones and associated infertility or reduced fecundity,^10,11 as well as reduced marriage rates and decisions to limit or forego childbearing among persons with epilepsy. Such decisions may be related to concerns about the risk of epilepsy in offspring, ASM-related teratogenesis, or pregnancy-related health issues.^9,12

Misconceptions about the genetic causes of epilepsy can impact reproductive decision-making among people with epilepsy. In population-based studies, the risk of epilepsy in the offspring of parents with epilepsy is not greater than 10%, even in the highest risk subgroup.^13,14 However, many people with epilepsy overestimate the risk of epilepsy in offspring,^9,15,16 with one study reporting a mean estimated risk of 26%.¹⁵ Moreover, in previous studies, a substantial proportion of people with epilepsy (19%–34%) reported that they limited childbearing because of epilepsy,^9,15,16 and these decisions were associated with concerns about having a child with epilepsy.^9,15,16

We reported previously that among people with epilepsy who had multiple relatives with epilepsy, the influence on reproductive decisions of genetics-related concerns increased with higher estimates of the risk of epilepsy in offspring and the participants’ belief that their epilepsy had a genetic cause.⁹ However, the generalizability of these findings is limited because the sample consisted of members of unusual families containing multiple affected persons who had participated in genetic research. Here, we investigated these questions in a larger, more representative sample of patients with epilepsy. We hypothesized that reduced reproduction in persons with epilepsy is explained, in part, by concerns about having affected children. To address this hypothesis, we examined the relations of number of offspring to participants’ (1) belief that their epilepsy had a genetic cause (“genetic attribution” [GA], regardless of actual genetic cause), (2) estimates of the risk of epilepsy in the offspring of a parent with epilepsy, and (3) reported degree to which the “chance of having a child with epilepsy” influenced their reproductive decisions.

2 |. METHODS

2.1 |. Study sample and recruitment

The study sample comprised adults treated for epilepsy at Columbia University Irving Medical Center. Eligibility required ages 18–79 at time of participation, an epilepsy diagnosis, and the ability to complete a self-administered survey in English or Spanish (i.e., no evidence of moderate to severe intellectual disability, dementia, or frequent instances of psychosis). In addition, their epilepsy must not have had an identified cause (e.g., stroke, severe traumatic brain injury).

To identify potentially eligible patients, we obtained patient lists through the Biomedical Informatics Resource Core of the Irving Institute for Clinical and Translational Research. The lists included demographic information for all adult patients (≥18 years) with a diagnosis of epilepsy (International Classification of Diseases, Tenth Revision [ICD-10] code G40.x) who had an outpatient visit during the preceding 1–3 months. Eligibility was determined by medical record review. For patients deemed eligible, we requested permission for contact from the epilepsy provider, and then mailed an invitation letter on behalf of the provider to those with permission. Subsequent recruitment contacts included phone calls, emails, and text messages, sent directly from the study team. Recruitment materials described study focus as “the experience of having epilepsy, and how people think about what caused them to have epilepsy.” Materials sent directly from the study team also included the study logo, with the name Epilepsy and Genetics Lived Experience (EAGLE). The current analysis includes participants who completed the survey between September 10, 2019, and January 22, 2022, either online (96%, Qualtrics, www.qualtrics.com) or on paper (4%).

At the end of the survey, participants were asked to provide consent for a more detailed review of their medical records. For those who consented, we abstracted epilepsy-related variables in detail, including age at epilepsy onset, epilepsy syndrome, seizure types, seizure frequency, medications, and findings on electroencephalography (EEG) and neuroimaging. The study was approved by the Columbia University Irving Medical Center Institutional Review Board.

2.2 |. Measures

Self-reported seizure-related variables. Survey items were used to assess the participants’ perceptions of their time since last seizure (<1 week, 1 week to 6 months, >6 months but <1 year, 1–5 years, >5 years; collapsed into <1 year ago vs ≥1 year ago for analysis) and number of lifetime seizures (1, 2–3, 4–20, 21–50, 51–100, >100; collapsed into ≤20 vs >20 for analysis).

Number of offspring.

Participants were asked, “How many biological children do you have?” Their numeric responses were recorded. They were also asked, “How many (or how many more) biological children would you like to have in the future?” Numeric responses were recorded.

Family history of epilepsy.

The survey asked, “Have any of your relatives ever had epilepsy or a seizure disorder? Please include your close relatives (parents, brothers and sisters, and offspring), as well as other relatives such as cousins, aunts and uncles, nieces and nephews, and grandparents. Include only relatives related to you by blood, rather than by marriage or adoption.” Possible answers were “yes,” “no,” and “don’t know.” Those who answered “yes” were asked to specify how many relatives and what their relationship to each of them was.

Estimate of epilepsy risk in offspring.

The survey asked, “If a child has a mother or father with epilepsy, which of the following comes closest to the chance the child will eventually develop epilepsy?” Choices were 1%, 5%, 10%, 25%, 50%, and 100%. Each possible answer was represented in a 10 × 10 icon array graphic, demonstrating the number out of 100. Risks were shown in text below each graphic in two formats: N in 100, N%. For analysis, we collapsed these choices into 1%, 5%–10%, 25%, and 50%–100%.

2.2.1 |. Reproductive concerns

The survey asked, “How much has each of the following factors influenced your decisions about having children or your plans to have children?” Eight factors were listed, each with possible answers “no influence,” “weak influence,” “moderate influence,” “strong influence,” and “very strong influence.” The primary factor for our current analysis was “the chance of having a child with epilepsy.” The seven other factors were “advice from your doctor,” “the effect of having epilepsy on your ability to care for a child,” and (for women only) “an effect of pregnancy on how well your seizure medicine works to control your seizures,” “a possible need to stop or change your seizure medicine during pregnancy,” “an effect of seizures during pregnancy on a developing baby,” “possible difficulties during labor/delivery,” and “an effect of seizure medicine during pregnancy on a developing baby.” Responses were collapsed into no/weak/moderate vs strong/very strong influence.

2.2.2 |. Genetic Attribution Score

A genetic attribution (or GA) score was computed as the mean of responses to four survey items. The first two items, each rated on a scale from 0 (lowest) to 10 (highest), asked, “What is the chance that one of your genes was a big part of the reason you have epilepsy?” and “How big a role did your genes play in causing you to have epilepsy?” The other two items came from the Illness Perception Questionnaire-Revised,¹⁷ in which participants rated the likelihood that each of 17 factors “caused you to have epilepsy” (very unlikely, somewhat unlikely, somewhat likely, very likely). For the GA score, we used responses for “genes or inheritance” and “something in my DNA,” with responses scaled to be parallel to those scaled 0–10 (very unlikely = 0, somewhat unlikely = 3.33, somewhat likely = 6.67, very likely = 10). Cronbach’s alpha = .89 for the four items. GA scores ranged from 0–10, with a mean of 4.6 (standard error of the mean [SEM] .13).

2.3 |. Statistical analysis

We used Poisson regression models to assess associations of number of offspring (dependent variable) with three independent variables of interest: GA score quartile, estimated risk of epilepsy in the offspring of a person with epilepsy, and influence of the chance having a child with epilepsy on reproductive decisions. To assess potential confounding, we examined the associations of potential confounders (age, sex, education, race/ethnicity, religion, self-reported time since last seizure, self-reported number of lifetime seizures, age at epilepsy onset, and epilepsy classification) with our dependent and independent variables. Age at epilepsy onset and epilepsy classification were obtained from medical record abstraction, and all other variables were obtained from the survey. Potential confounders associated with both number of offspring and one or more independent variables at a “liberal” p-value of .2 were included in the adjusted models. Six potential confounders met this criterion: age, education (college graduate vs other), race/ethnicity (White non-Latinx, Black/African American non-Latinx, Latinx, Other non-Latinx), religion (Catholic, Protestant/Other Christian, Jewish, other/none/prefer not to say), epilepsy classification (generalized, focal, both/unclassifiable), and age at epilepsy onset (0–9, 10–19, ≥20 years). In separate analyses, we assessed the association of number of offspring with each independent variable, adjusting only for age. Then we repeated the analysis adjusting for all six potential confounders. Preliminary analyses indicated that the results differed by age; hence, we carried out all analyses separately within two broad age groups (18–45 years, 46–79 years). All analyses were conducted using IBM SPSS Statistics (Version 27; Chicago, IL).

3 |. RESULTS

3.1 |. Participants

Among 1515 patients invited to participate, 606 (40%) completed the survey (587 in English, 19 in Spanish). Participation rates were higher among women (44%) than men (34%, p < .001) and among those 18–45 years of age (42%) vs 46 or older (36%, p < .05). Participation rates according to race and ethnicity could only be evaluated from limited information in the medical records (42% missing for race, 43% missing for Latino ethnicity); based on these limited data, participation rates appeared to be higher among Whites (44%) vs non-Whites (34%, p < .05) and among non-Latinos (45%) vs Latinos (25%, p < .001).

Participants averaged age 41 years (SEM .62); 64% were women, 64% had ever lived with a partner, and 67% were college graduates (Table 1). Self-reported race/ethnicity was 66% White non-Latinx, 7% Black non-Latinx, 18% Latinx, and 9% other non-Latinx. Religion was reported as Catholic (27%), Jewish (16%), Protestant/other Christian (14%), or other, none, or prefer not to say (42%). Epilepsy was generalized in 31%, focal in 60%, both focal and generalized in .7%, and unclassifiable in 8%. A first-degree family history of epilepsy was reported by 83 participants (14%). Ninety-two percent of participants gave permission for medical record abstraction.

TABLE 1.

Participant characteristics and number of offspring^a

	N (%)	Mean N offspring (SEM)	p-value
Age (years)
18–45	409 (67.5)	.5 (.05)	<.001
>45	197 (32.5)	1.4 (.11)
Sex
Female	385 (63.5)	.8 (.06)	.25
Male	221 (36.5)	.9 (.10)
Race/ethnicity
Non-Latinx White	396 (65.9)	.8 (.07)	.01
Non-Latinx Black	41 (6.8)	.9 (.18)
Latinx	111 (18.5)	1.0 (.13)
Non-Latinx other	53 (8.8)	.5 (.13)
Religion
Catholic	164 (27.5)	.9 (.09)	<.001
Jewish	96 (16.1)	1.4 (.20)
Protestant or other Christian	86 (14.4)	.8 (.12)
Other, none, or prefer not to say	251 (42.0)	.5 (.06)
Education
Less than college graduate	196 (32.6)	1.2 (.12)	<.001
College graduate	406 (67.4)	.6 (.05)
Marital status
Never lived with partner	219 (36.4)	.1 (.03)	<.001
Ever lived with partner	382 (63.6)	1.2 (.07)
Family history of epilepsy
None	411 (68.0)	.9 (.07)	.05
Not first-degree	110 (18.2)	.6 (.10)
First-degree	83 (13.7)	.8 (.13)
Number of lifetime seizures
≤20	316 (52.3)	.9 (.08)	.24
>20	288 (47.7)	.8 (.07)
Time since last seizure
≥1 year	324 (53.6)	.9 (.07)	.04
<1 year	280 (46.4)	.7 (.08)
Epilepsy type
Generalized	173 (31.3)	.5 (.08)	<.001
Focal	330 (59.7)	.9 (.07)
Both or unclassifiable	90 (9.0)	.9 (.22)
Epilepsy age at onset
0–9 years	78 (14.2)	.5 (.10)	<.001
10–19 years	244 (44.4)	.5 (.06)
20+ years	227 (41.3)	1.2 (.10)

^ap-values were computed by Poisson regression analysis. Epilepsy type and age at onset are based on medical record abstraction; all other variables are based on survey responses. Total N’s vary for different variables because of missing data.

3.2 |. Reproductive concerns

Overall, 16% of participants (women 19%, men 11%) responded that the “chance of having a child with epilepsy” had a strong/very strong influence on their reproductive decisions (Figure 1). For each of the three factors asked of all participants, women were more likely than men to report a strong/very strong influence. The proportion of women who reported a strong/very strong influence was greatest for factors related to their health during pregnancy (30%–38%) and the effects of seizures (42%) or ASMs (46%) on a developing child.

FIGURE 1.

Proportion of participants who responded that each factor had a strong/very strong influence on their decisions about having children or their plans to have children.

3.3 |. Relations among the three main predictors

Mean GA scores were significantly higher among participants with vs without a family history of epilepsy, and highest in those who reported a first-degree relative with epilepsy, supporting the construct validity of the measure (p < .001, Kruskal-Wallis H test) (Figure 2). In addition, mean GA scores increased with increasing estimates of epilepsy risk in the offspring of a parent with epilepsy (Spearman’s rho = .243, p < .001), and were significantly higher among participants who responded that “the chance of having a child with epilepsy” had a strong/very strong influence on their reproductive decisions than among others (p = .002, Mann-Whitney U test) (Figure 2).

FIGURE 2.

Mean genetic attribution score according to family history of epilepsy (none, other than first-degree, first-degree), estimated risk of epilepsy in offspring of a parent with epilepsy, and influence on reproductive decisions of “the chance of having a child with epilepsy.” bars indicate 95% confidence intervals.

The proportion of participants who responded that the chance of having a child with epilepsy had a strong/very strong influence on their reproductive decisions also increased significantly with increasing estimates of epilepsy risk in offspring (p < .001, chi-square test of linear relationship), and with increasing GA quartile (p = .002, chi-square test of linear relationship) (Figure 3).

FIGURE 3.

Percent of participants who responded the influence on their reproductive decisions of “the chance of having a child with epilepsy” was “strong/very strong,” according to estimated epilepsy risk in offspring of a parent with epilepsy and genetic attribution score quartile.

3.4 |. Differences between participants ages 18–45 and >45 years

Average age was 31 (SEM .33) among participants 18–45 years of age, and 59 (SEM .68) among those >45. As expected due to their younger age, participants in the younger group had significantly fewer offspring than those in the older group (mean .5 vs 1.4, p < .001, Table 1). The two age groups also differed significantly in the three main predictors in our analysis. Compared with participants >45 years of age, younger participants had significantly higher mean GA scores (4.9 vs 3.9, p < .001, Mann-Whitney U test) and were more likely to respond that the chance of having a child with epilepsy had a strong/very strong influence on their reproductive decisions (19.7 vs 9.3%, p = .001, chi-square test). Estimates of epilepsy risk in the offspring of a parent with epilepsy also differed between the two groups (p < .001, chi-square test), with higher risk estimates in younger participants. Compared with older participants, those 18–45 years of age were less likely to estimate risk of 1% (10.7 vs 28.3%) and more likely to estimate risk of 25% or greater (25% risk: 26.4% vs 18.3%; 50%–100% risk: 19.2% vs 13.1%).

3.5 |. Associations with number of offspring

Among participants 18–45 years of age, number of offspring decreased significantly with increasing GA score (Figure 4 and Table 2). Participants in the two highest GA quartiles had only about half as many offspring as those in the lowest quartile (fully adjusted analysis, Table 2: rate ratio [RR] = .6 for GA quartile 3; .5 for GA quartile 4). Compared with participants who estimated 5%–10% risk, number of offspring was significantly decreased among those who estimated 25% risk (fully adjusted analysis, RR = .7, p = .05) or 50%–100% risk RR = .6, p = . 03). Among participants who estimated 1% risk, number of offspring was significantly increased in the age-adjusted analysis (RR = 1.6, Table 2), but this estimate was attenuated (closer to the null hypothesis) and no longer significant in the fully adjusted analysis (RR = 1.3, p = .26, Table 2). Among participants 18–45 years of age, number of offspring was not associated with a response that the chance of having a child with epilepsy had a strong/very strong influence on their reproductive decisions (Figure 4 and Table 2).

FIGURE 4.

Mean number of offspring by genetic attribution score quartile, estimated risk of epilepsy in offspring of a parent with epilepsy, and influence on reproductive decisions of “the chance of having a child with epilepsy” among participants ages 18–45 (top) and >45 years (bottom). Bars indicate 95% confidence intervals.

TABLE 2.

Associations of reported number of offspring with genetic attribution, influence on reproductive decisions of “the chance of having a child with epilepsy,” and estimated risk of epilepsy in offspring of affected parent

Age 18–45	N	Mean N offspring (SEM)	Age-adjusted		Fully adjusted
			RR (95% CI)	p-value	RR (95% CI)	p-value
Genetic attribution scorea
1st (lowest) quartile	88	.8 (.16)	1.0 (referent)		1.0 (referent)
2nd quartile	91	.6 (.10)	.8 (.55–1.14)	.21	.9 (.61–1.42)	.74
3rd quartile	113	.5 (.10)	.6 (.42–.87)	.01	.6 (.41–.91)	.02
4th (highest) quartile	114	.3 (.07)	.4 (.28–.63)	<.001	.5 (.34–.81)	<.001
Estimated risk in offspring of parent with epilepsyb
1%	43	1.0 (.24)	1.6 (1.08–2.23)	.02	1.3 (.83–1.96)	.26
5%–10%	176	.5 (.08)	1.0 (referent)		1.0 (referent)
25%	106	.4 (.07)	.7 (.48–1.03)	.07	.7 (.45–1.01)	.05
50%–100%	77	.3 (.09)	.6 (.40–1.00)	.05	.6 (.33–.93)	.03
Influence of “the chance of having a child with epilepsy”c
None/weak/moderate	327	.5 (.06)	1.0 (referent)		1.0 (referent)
Strong/very strong	80	.4 (.09)	.9 (.60–1.24)	.43	.9 (.62–1.38)	.70
Age >45
Genetic attribution scorea
1st (lowest) quartile	63	1.3 (.20)	1.0 (referent)		1.0 (referent)
2nd quartile	57	1.7 (.19)	1.3 (.94–1.69)	.12	1.1 (.79–1.52)	.57
3rd quartile	32	1.2 (.23)	.9 (.61–1.30)	.54	.8 (.54–1.34)	.48
4th (highest) quartile	39	1.6 (.24)	1.2 (.88–1.71)	.24	1.2 (.80–1.74)	.40
Estimated risk in child of parent with epilepsyb
1%	54	1.8 (.18)	1.3 (.98–1.72)	.06	1.1 (.82–1.55)	.45
5%–10%	77	1.4 (.18)	1.0 (referent)		1.0 (referent)
25%	35	1.4 (.26)	1.0 (.72–1.42)	.97	.7 (.49–1.10)	.13
50%–100%	25	1.1 (.27)	.8 (.54–1.25)	.36	.9 (.52–1.39)	.52
Influence of “the chance of having a child with epilepsy”c
None/weak/moderate	175	1.5 (.11)	1.0 (referent)		1.0 (referent)
Strong/very strong	18	.8 (.34)	.6 (.33–.94)	.03	.6 (.32–1.07)	.08

Note: Age-adjusted model includes only age as a continuous variable. Fully adjusted model includes age as a continuous variable, college graduation, race/ethnicity (white non-Hispanic, Black/African American, Hispanic, Other), religion (Catholic, Protestant/Other Christian, Jewish, Other/none/prefer not to say), epilepsy type (generalized, focal, both/unclassifiable), and epilepsy age at onset (0–9, 10–19, ≥20 years). Total N’s vary across different analyses because of missing data.

Abbreviations: CI, confidence interval; RRs, rate ratios computed by Poisson regression analysis.

^aGenetic attribution (GA) score. Mean value of responses to likelihood that factor “caused you to have epilepsy” for “genes or inheritance” and “something in my DNA” (very unlikely = 0, somewhat unlikely = 3.33, somewhat likely = 6.67, very likely = 10.0) and responses to “What is the chance that one of your genes was a big part of the reason you have epilepsy?” and “How big a role did your genes play in causing you to have epilepsy?” (each rated 0 to 10). Cronbach’s alpha = .89 for the four items.

^bResponse to “If a child has a mother or father with epilepsy, which of the following comes closest to the chance the child will eventually develop epilepsy?” with possible choices: 1 in 100 (1%), 5 in 100 (5%), 10 in 100 (10%), 25 in 100 (25%), 50 in 100 (50%), 100 in 100 (100%).

^cResponse to the degree of influence of “the chance of having a child with epilepsy” on decisions about having children or plans to have children (none/weak/moderate, strong/very strong).

Among participants >45 years, number of offspring was not associated with GA quartile or estimated risk of epilepsy in offspring (Figure 4 and Table 2). Participants who responded that the chance of having a child with epilepsy had a strong/very strong influence on their reproductive decisions had significantly fewer offspring than others in the age-adjusted analysis (Table 2: RR = .6, p = .03); the RR estimate remained the same after full adjustment, although the p-value increased to .08.

To explore the extent to which the findings were mediated by reduced marriage rates, we repeated the analysis after restricting to participants who had ever lived with a partner. Although statistical power was reduced, the results were very similar to those in Table 2 (Table S1). Finally, we repeated the analysis with a more extreme outcome—the decision not to have children (Table S2). Overall, 23% of participants responded that they had not had any offspring and were not planning to have any in the future. This proportion was lower (but still substantial) among those 18–45 years of age (18%) than among those >45 years (33%) (p < .001, chi-square analysis). Analysis in relation to our three main predictors revealed a significantly increased odds of deciding to remain childless among participants 18–45 years of age who overestimated the risk of epilepsy in the offspring of a parent with epilepsy (25%: odds ratio [OR] = 2.5, p = .01, 50%–100%: OR = 3.6, p ≤ .001).

4 |. DISCUSSION

In this study, we examined the relations of number of offspring among people with epilepsy to three interrelated measures of their beliefs and concerns about the genetic influences on their disorder. We predicted that these measures would capture concerns that might influence reproductive choices contributing to the reduced reproduction observed in many studies of people with epilepsy. The first measure, genetic attribution (or GA), assessed the degree to which participants believed their epilepsy had a genetic cause; the second, their estimate of the chance that the child of a parent with epilepsy would develop epilepsy; and the third, the degree to which concerns about the chance of having a child with epilepsy influenced their reproductive decisions. As expected, the three measures were strongly correlated with each other; however, they are not equivalent. For example, a participant’s belief in a high risk of epilepsy in the offspring of a person with epilepsy does not necessarily correspond to a belief in a genetic cause of his/her epilepsy, and a high level of GA does not necessarily correspond to a strong influence on reproductive decisions of the chance of having a child with epilepsy.

Among people 45 years of age or younger, the number of offspring was strongly associated with both GA and estimated offspring risk. Those in the highest GA quartile had only about half as many offspring as those in the lowest quartile. For analyses of estimated offspring risk, we used 5%–10% risk as the referent because it is closest to the true risk in offspring of people with epilepsy.^13,14 Offspring risks vary by gender and epilepsy type of the affected parent. In population-based data from the Rochester Epidemiology Project,¹³ cumulative incidence of epilepsy to age 40 was 5% (95% confidence interval [CI] 3%–8%) among offspring of women with epilepsy and 2% (95% CI. 1%–4%) among those of men with epilepsy. Risks were higher in the offspring of parents with generalized epilepsy but were not higher than 10% in any subgroup. In a large population-based study from Denmark,¹⁴ the cumulative incidence to age 30 was 8% (95% CI 7%–9%) among the offspring of women with epilepsy and 5% (95% CI 5%–6%) among the offspring of men with epilepsy. In the current study, nearly half of participants 18–45 years of age overestimated risk, responding that it was either 25% (26% of participants) or 50%–100% (19%). Moreover, as predicted, those who overestimated risk in offspring had significantly fewer offspring than those who estimated 5%–10% risk. Furthermore, about 25% of the younger participants who overestimated risk indicated that they had decided not to have any children, compared with 14% of those who estimated 5%–10% risk. Although a substantial proportion (20%) of younger participants responded that that the chance of having a child with epilepsy had a strong/very strong influence on their reproductive plans, the number of offspring was not related to this variable.

Older participants had lower levels of GA than younger participants. Although the estimates of risk of epilepsy in offspring were lower than those of younger participants, a significant proportion in this group also overestimated risk at either 25% (18% of participants) or 50%–100% (13% of participants). Among older participants, however, the number of offspring was not related to either GA or estimated risk in offspring. Participants who responded that the chance of having a child with epilepsy had a strong/very strong influence on their reproductive decisions had only 60% as many offspring as others, and this estimate was unchanged after adjustment for potential confounders. A third of participants >45 years of age had not had any offspring and were not planning to have any in the future; the extent and ways in which this is related to having epilepsy would be important to explore.

Age, period, or cohort effects likely contribute to the differences in the results between the two age groups. Participants 18–45 years of age were responding about their current or future reproductive decisions, whereas those >45 years of age were responding about their past decisions, reflecting on the degree to which past reproductive choices might have been influenced by concerns about having a child with epilepsy. The emphasis on genetic causes of epilepsy has increased exponentially in recent decades, and younger participants are likely to be more aware of genetic risks, and possibly more concerned about them. The younger participants may also reflect the concerns of future people with epilepsy reaching adulthood during the era of strong emphasis on genetics and precision medicine in the epilepsies. Older participants whose responses indicated high levels of GA now may not have held the same beliefs or had the same concerns when deciding to have offspring. In addition, the number of our participants >45 years of age was only about half that of those younger, limiting our statistical power in the older group.

These findings are similar to those from our previous study on this topic,⁹ but we note important differences. Although the previous study was restricted to members of unusual families containing multiple people with epilepsy (average four with epilepsy per family) who had participated in genetic research, our current findings are from a study of adult epilepsy patients unselected by family history. We also made two changes in the design of the survey used for data collection. First, to obtain participant estimates of offspring epilepsy risk, we used discrete categories rather than the open-ended question we used before and included visual icon arrays to help clarify the meaning of the risks. Second, we changed the response categories for the questions about influences of different factors on reproductive decisions. In the earlier study, possible responses ranged from “made me much less likely to want to have a child” to “made me much more likely to want to have a child.” Because most of the factors listed were expected to lead to reduced rather than increased reproduction, we simplified the response categories to reflect the degree of influence (none, weak, moderate, strong, very strong), rather than specifying the direction. The single item in which this change affects comparability of the results is “advice from your doctor,” which could influence decisions about reproduction in either direction. For the other items, our current results replicate those of our previous analysis: the influence of genetics-related concerns on reproductive decisions increased with increasing genetic attribution and estimated offspring risk (here, a “strong/very strong” influence of the “chance of having a child with epilepsy,” [Figure 2], and in our previous analysis, a response of “less likely/much less likely to want to have a child” for “chance of having a child with epilepsy” and “having epilepsy in your family”).

In our current analysis, we used an improved measure of GA based on four survey items, with better reliability (Cronbach’s alpha = .89 vs .77 for our previous measure¹⁸) and a wider scale (0–10 vs 1–3 for our previous measure). In addition, rather than focusing primarily on the impacts of GA on genetics-related concerns, our current analysis goes farther and assesses the impacts on number of offspring. Other strengths of our current study include greater generalizability to people with epilepsy without a family history, large sample size, more ethnic diversity (87% White non-Latinx in our previous study vs 66% in our current study), and better information on the clinical aspects of epilepsy (based on medical record review).

Weaknesses include sampling from a tertiary referral center and a participation rate of only 40%, with evidence for selection bias by sex, age, and race/ethnicity and an overrepresentation of people with high education (68%), which limits generalizability to all patients with epilepsy. Our study was restricted to people with epilepsy in whom a cause had not been identified, and the number of participants >45 years of age was relatively small, thereby limiting the statistical power in this subgroup.

Although our recruitment materials described the study focus in general terms (“the experience of having epilepsy, and how people think about what caused them to have epilepsy”), they also included our study name, “Epilepsy and Genetics Lived Experience,” which may have led to a bias in participation favoring patients with a family history or genetics-related concerns. We believe this bias is likely relatively small given the modest level of GA in the sample (average score of 4.6 on a scale of 0–10). The proportion of participants with a first-degree family history of epilepsy (14%) was higher than the 9%–10% reported in some other large studies.^19–21 Given that familial risks are known to be higher among patients without vs with an identified cause of their epilepsy,¹³ this higher rate may have been partly explained by our restriction to patients without identified causes. Levels of GA, estimated risk in offspring, and their impacts on reproduction would be important to explore in a population-based series.

5 |. CONCLUSIONS

These findings provide strong evidence that misunderstandings related to genetic influences on epilepsy can have important real-life consequences for people with epilepsy. More studies are needed of the risks of epilepsy in offspring, based on large, population-based data sets with sufficient power to determine the range of risks in offspring of women and men with specific clinically defined subcategories of epilepsy (epilepsy syndrome, age at onset, and so on). Patient and provider education about recurrence risks and genetic testing options to clarify risks would be beneficial to correct misconceptions, given the important influence they can have reproductive decisions. Future studies should also explore the most effective ways of disseminating and imparting this information.

Key Points.

• Some people with epilepsy may choose to limit or forego childbearing due to concerns about genetic risks.

• Epilepsy patients 18–45 years of age who strongly believed genetics was a cause of their epilepsy had only about half as many offspring as others.

• Many patients overestimated the risk of epilepsy in offspring, and those18–45 years of age who did so had only 60%–70% as many offspring as others.

• Patients >45 years of age less strongly endorsed a genetic cause of their epilepsy, but those influenced by concern about having an affected child had fewer offspring than others.