Introduction

Over the last decades, several genes have been identified causing autosomal dominant adult-onset neurodegenerative disease, such as HTT in Huntington’s disease (HD), PSEN1, PSEN2 and APP in (early-onset) Alzheimer’s disease (AD) and MAPT, GRN and C9orf72 in frontotemporal dementia (FTD) (MacDonald et al. 1993; Sherrington et al. 1995; Clark et al. 1995; Goate et al. 1991; Hutton et al. 1998; Spillantini et al. 1998; Baker et al. 2006; Cruts et al. 2006; DeJesus-Hernandez et al. 2011; Renton et al. 2011). Therefore, predictive testing has become an option for an increasing number of unaffected at-risk relatives. While a majority of the relatives seemed to be interested in predictive testing before genetic testing was available, the uptake of predictive testing for adult-onset neurodegenerative diseases is in general less than 15% (Steinbart et al. 2001; Riedijk et al. 2009; Tibben 2007; Morrison et al. 2011).

Studies on the impact of predictive testing on neurodegenerative diseases mainly focussed on psychological aspects, such as anxiety and major depression and psychological adverse events (Almqvist et al. 2003), or on perception of genetic discrimination (Bombard et al. 2008; Penziner et al. 2008; Williams et al. 2010; Erwin et al. 2010). The authors of a review article on quality of life after predictive testing on neurodegenerative diseases published in 2013 concluded that (a) extreme or catastrophic outcomes are rare, (b) depression and anxiety are common but mainly transient, (c) most participants report no regret, (d) many tested individuals report extensive benefits of knowing their genetic status, and (e) there is a need for regulations regarding genetic discrimination (Paulsen et al. 2013). While these studies of people who have undergone testing have not shown increased harm, these studies reflect only those who considered predictive testing. Thus, even with untested participants included, these reports do not represent the entire population at (known) risk for inherited neurodegenerative disorders. Therefore, the sensitivity of measures used in these studies may not apply to the whole population. Besides the need to decrease uncertainty, life planning is one of the most cited reasons for predictive testing in the literature (Paulsen et al. 2013). This includes reproduction, work or retirement, finances and insurance. However, studies on the effect of predictive testing on adult-onset neurodegenerative diseases on these non-psychological aspects of life are scarce. It seems plausible that awareness of being a carrier of a neurodegenerative disease affects the course of life and decisions in a family—and future planning to a larger degree compared to being at 50% risk. Moreover, persons who know that they have not inherited the predisposition for the familial disease may benefit from the outcome of their genetic test. For example, in life planning and applying for insurances, there is no need to take into account a high risk of dementia. Therefore, carriers may experience more problems in several personal and social aspects of life, such as relationships and career, compared to both untested individuals at risk and non-carriers. It is important to have more information on the consequences of the test result in order to counsel and guide at-risk individuals requesting predictive testing properly.

The aim of the study is to investigate whether mutation carriers of adult-onset neurodegenerative diseases are more often unemployed, have a lower income, are refused to take out insurances or have to pay a higher premium, live less healthy and are more often single and childless compared to non-carriers and at-risk relatives who have not been tested. In this manuscript, we describe the outcome of the exploratory study aimed to identify trends for further investigation in a larger study, and to optimize the questions and possible answers of the questionnaire.

Subjects and Methods

Participants

We selected patients from four sources: I. patients who visited the Clinical Genetics Department of the Erasmus Medical Center (EMC) in Rotterdam from January 2003 to December 2012 at risk of familial HD, FTD or AD (n = 206); II. patients of the Clinical Genetics Department of the VU University Medical Center (VUmc) in Amsterdam from January 2003 to December 2012 at risk of AD or FTD (n = 9); III. participants of a genetic FTD research cohort on inherited FTD at the EMC (Dopper et al. 2014) (n = 31); and IV. family members of study participants, who gave consent to be informed about our research project (n = 37). Of the patients selected from the departments of clinical genetics, we checked in the national insurance database and hospital database whether they were alive and if they had changed addresses. Individuals of the FTD research cohort were asked permission to be contacted about this research project by their research physicians.

The inclusion criteria of this exploratory study were (a) age ≥ 35 years; (b) tested while asymptomatic for HD, FTD or AD at least 2 years before the start of the study or at (presumed) 50% risk for one of these diseases and (c) sufficient knowledge of the Dutch language to understand the instructions and questionnaires. We chose the age cut-off age because many important decisions and life events, such as building a career, having long-lasting relationships and reproduction are fulfilled at that age. We chose a minimum period since testing of 2 years to avoid including persons for whom the test had been carried out too recently to result in any changes in their course of life. When we set up the study project, we decided to include affected individuals who were able to fill in and return the questionnaire. However, since responses of participants diagnosed with the disease showed a few inconsistencies, we decided to exclude them from the analysis to avoid involvement of the disease on the results and we therefore did not send them the additional questionnaire. Following completion of the inclusion, we also decided to exclude the results of participants from AD families from the analysis, because their small number would not allow sub-analysis of this group and would only increase the heterogeneity of the cohort.

The medical ethics committees of the Erasmus MC and VU University Medical Center approved the study.

Data Collection

To eligible persons selected from the clinical genetics departments, we sent a package containing 1. a personal letter signed by the executive researcher and their own physician, 2. general information on the study, 3. an informed consent form, 4. a form to inform us about the contact details of relatives who gave them their consent to be contacted about this study and 5. a return envelope. Participants gave their permission to be contacted soon after the return of their questionnaire with additional questions, consented to being contacted at a later date for follow-up and optioned whether they wanted to be informed on the general results of the study. Persons who agreed to participate were sent a copy of the signed informed consent form and the questionnaire. Participants were reminded by phone or email if the questionnaire was not returned within 6 weeks. Within a year of sending the first questionnaires, we sent the additional questionnaire.

Questionnaires

The primary questionnaire was developed and contained items selected and based on experience of the researchers and literature studies. For the formulation of the questions and answering options, we consulted a survey expert. The questionnaire comprised 70 questions on employment, financial issues, lifestyle, relations and family life, clustered in eight sections: I. general information on sex and date of completing the questionnaire, II. family history, III. health and lifestyle, IV. family and relations, V. education, employment and finance, VI, perception of the impact of the disease in the family, VII. perception of the impact of the personal risk and VIII. the DNA test (to be filled in only by tested participants). The validated Dutch version of the 12-Item Short Form Health Survey (SF-12) (Gandek et al. 1998) was embedded in the section on health and lifestyle. The SF-12 measures physical and mental health. Scores of the SF-12 are normed to a mean of 50 and a standard deviation of 10. Higher scores equal better health status and lower scores equal poorer health status based on US population norms. The scoring system is influenced by age and other factors and therefore especially useful to compare results between or within groups. Most questions in our questionnaire were multiple choice items, with the option to elaborate or to choose not to answer the question or ‘not applicable’.

Based on preliminary analysis of the results and comments made by the participants, an additional questionnaire was developed by the authors. The 47 items were either questions from the first questionnaire though slightly differently worded or with adjusted answer options, or additional questions on items that seemed to be missing based on the given answers of the primary questionnaire. The additional questionnaire was structured in the following sections: I. general information on age and the date, II. family and relations, III well-being, IV. education, employment and finance, V. perception of the impact of the personal risk, and VI. the DNA test. This questionnaire also encompassed the validated Hospital Anxiety and Depression Scale (HADS) questionnaire (Zigmond and Snaith 1983; Spinhoven et al. 1997; Bjelland et al. 2002), which is a screening tool containing 7 items on depression and 7 on anxiety. A score of 8 to 10 on one of the subscales may reflect anxiety or a depressive state, a score of 11 or above is indicative of a clinically relevant level of distress.

Data Analyses

Since the additional questionnaire also included rephrased questions of the first questionnaire, we only analysed the data of participants who returned both questionnaires. Of the overlapping items present in both questionnaires, only the answers of the second questionnaire were used in the analysis. Survey data entry and analyses were conducted using the Statistical Package for the Social Sciences (SPSS) version 22 (Chicago, IL, USA). Pearson chi-squared tests with asymptotic probability values were used for categorical association testing, and Kruskal-Wallis tests to compare medians. A significance level of P < 0.05 was used.

Results

Response and Eligibility

A total of 283 individuals received the information package (Fig. 1). Of these, 193 were from HD families, 81 from FTD families and 9 from AD families. A positive informed consent form was returned by 115, an overall response rate of 39.5% (HD 33.2%, FTD 55.6% and AD 33.3%) Of the 171 non-participants, 17 returned a negative consent form or informed us about their decision by email, of whom 9 explained why they did not agree to participate. Reasons given for a negative consent were the current state of health (n = 3), not wanting to be confronted with the disease (n = 2), being too young to participate (n = 1), not being at risk of the disease (n = 1), believing to be ineligible because being a non-carrier (n = 1) and privacy or personal circumstances (n = 1).

Fig. 1
figure 1

Selection and inclusion of the participants

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Non-responders had a median age of 46.2 years (range 35–80), slightly though significantly younger than the positive responders (p = 0.02), who had a median age of 49.4 years (range 29–75). No significant differences were detected between responders and non-responders in sex, disease, or carrier status (Table 1, P values > 0.05). Of note, of a few individuals, we had no prior information on age, carrier status or date of testing. Some of the responders turned out to be ineligible: seven individuals had had predictive testing performed less than 2 years before the start of our study, and one person had a less than 50% risk on the predisposition.

Table 1 Characteristics of responders and non-responders
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Characteristics of the Participants

The characteristics of the participants are described in Table 2. Carriers were the youngest and untested individuals the eldest group. The majority of the participants were female (68.9%). The majority of carriers and non-carriers were from HD families (77.0%), while most untested individuals were at risk of FTD (74.1%). A relatively high proportion (40.5%) of the participants were highly educated compared to 26.8% of the general population (Statistics Netherlands 2016). The average age of onset of the disease within the family was, as far as known by the participants, comparable between carriers, non-carriers and untested individuals at risk.

Table 2 Characteristics of the participants
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Most participants did not have an affected parent when they were minors. None of the untested individuals but 15% of the tested participants were regular caregivers for affected relatives. The carriers and non-carriers were comparable in age at testing and the time since receiving the test result.

Outcome

The main outcomes of our study are described in Table 3. None of the differences were significant.

Table 3 Results of the study
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In all groups, a small majority had a paid job for at least 20 hours a week. The proportion of participants that were retired was highest in the untested group (22.2%) and lowest in the non-carrier group (3.3%). Two carriers and one non-carrier had been declared unfit for work. Untested individuals more often had an income of over € 66.000 than carriers (20.0 vs 0%). Life, disability or additional health insurances were rarely refused or offered at a higher premium in all groups. Two carriers and no non-carriers or untested participants had severe debts requiring professional help.

There were no differences in drinking and smoking habits between carriers, non-carriers and untested at-risk participants. None of the participants declared to use any drugs. We found no difference in mental or physical health, although we found a wider range of the SF-12 scores in tested compared to untested individuals. Indications for depression or anxiety were slightly more often present in carriers.

Although not significantly different, carriers lived slightly less often with a partner, were more often divorced and more often childless. A wish to have children at the moment of testing was reported by 8 carriers and 14 non-carriers. Of the carriers, 4 refrained from having any (more) children, 4 had prenatal testing or preimplantation genetic diagnostics performed and one decided to accept the risk to pass the mutation to a future child. None of the carriers adopted a child or chose for a donor parent. Six of the carriers and ten of the 14 non-carriers who wanted to have a or another child had a child after the test result.

A mainly negative influence of their personal risk of the disease on their marital state was reported by 5.6% of the carriers and none of the non-carriers, and a mainly positive effect by 2.8% of the carriers and 5.6% of the non-carriers. Furthermore, 8.1% of the carriers and 5.5% of the non-carriers reported to have once ended a relationship (partly) because of their personal risk of the disease. None of the untested participants reported any influence of their personal disease risk on these items.

Discussion

In this exploratory study, we found no large negative effects of predictive testing for FTD or HD on employment, salary, financial issues or health and well-being between carriers and non-carriers and untested individuals at risk.

The only differences we found, although not significant, were in family life: carriers lived more often without a partner, were more often divorced despites their younger age and were more often childless. According to the national registration in The Netherlands in 2014, 40.1% of the marriages end in a divorce16. Therefore, it is not that carriers necessarily have a higher divorce rate, rather the at-risk untested participants have a lower divorce rate. Also according to this national database, 78% of the Dutch persons have one or more children (Statistics Netherlands 2016). The carriers in our study are more often childless than the other participants, but the non-carriers and untested at risks are less often childless than the general population. However, only tested individuals reported an influence of their personal risk of the disease on relationships.

Although caution is required when interpreting results of a study with small numbers of participants, the absence of differences in our study in most social aspect in life is encouraging. The outcome of our exploratory study suggest that if a positive predictive test result has a significant impact on personal and social life, the impact may be limited to a minority, or be relatively small or only temporary.

One possible explanation for the lack of significant differences between carriers and non-carriers or untested individuals at risk may be that all individuals are unaware of their genetic status for a certain period of time. Of those participants who underwent testing, the median age was 35 years; therefore, half of them lived at least the first 35 years of their lives without knowing their genotype. These first decades may be crucial in developing a personality, but also in building a career and having a family. It would be interesting to analyse whether the outcome is different in patients who were tested at a young age.

Because of the small numbers in our study and exclusion of individuals aged younger than 35 years, such a sub-analysis was not possible in this exploratory study. Another explanation is self-selection of participants who consented to participate and who remained in the study. Timman et al. reported on a long-term follow-up study of individuals tested for HD and found that identified carriers who were lost to follow-up after disclosure of test results, reported significantly more pre-test distress than did those carriers who attended for follow-up (Timman et al. 2004). They speculated that studies that report few harmful effects may have underestimated the real impact.

In general, we found fewer differences in outcomes between carriers and non-carriers, than between tested and untested individuals. Carriers and non-carriers seem more alike. The decision to undergo predictive testing is probably influenced by many factors, including personality traits, the perception of the severity of the disease, the risk perception and the degree of involvement with affected relatives. We did not find a difference between tested and untested individuals in age of onset of the disease within the family or in having an affected parent during their childhood. However, only tested individuals had been involved in regularly care of an affected relative, and only tested individuals reported influence (negative or positive) of their disease risk on marital status and relationships.

Study Limitations

The numbers of this study are small and we should be cautious when interpreting the outcomes. Furthermore, the response rate was low and a significant influence of a selection bias is likely. The response rate may have been influenced negatively by the length of the surveys, although only 19 of the 199 sent questionnaires were not returned. Especially individuals who experienced less favorable life changes might be less inclined to respond to this survey. Indeed, carriers less often participated; however, this may also be due to a larger proportion already being affected. The response rate was higher in individuals of FTD families than in AD and HD families. This difference is probably caused by our methods of selecting patients: most individuals from FTD families were selected from the FTD research cohort and were requested permission to be informed in this study beforehand.

Practice Implications

The absence of differences in our study in most social aspects in life between carriers and non-carriers and untested individuals at risk for adult-onset neurodegenerative diseases is encouraging. This information, after validation in a larger cohort, is important for genetic counselling individuals considering predictive testing.

Research Recommendations

Further studies are necessary to confirm our findings before our results can be implemented in clinical genetic care. Performing this study in a larger cohort would also enable subgroup analysis, for example in carriers tested at a young age. A prospective study should be conducted, because information on both pre- and post-test status would give more background information on the non-responders.

Conclusion

Our hypothesis that mutation carriers of adult-onset neurodegenerative diseases are more often unemployed, have a lower income, experience more problems with insurances, live less healthy and are more often single and childless compared to non-carriers and at-risk relatives who have not been tested was not confirmed in our study. Although these observations should be interpreted with caution because of the small number of participants and low response rate, these findings suggest that, in general, predictive testing on these diseases do not largely influence the course of life. However, further (larger) studies are necessary before the results can be used in clinical genetic counselling.