Skip to main content
NCBI home page
The Journals of Gerontology Series B: Psychological Sciences and Social Sciences logoLink to The Journals of Gerontology Series B: Psychological Sciences and Social Sciences
. 2020 May 3;75(8):e189–e197. doi: 10.1093/geronb/gbaa061

Apolipoprotein ɛ4 Allele and Subjective Cognitive Functioning in Parents of Adults With Disabilities

Jieun Song 1,✉, Marsha R Mailick 1, Jan S Greenberg 1
Editor: Lynn Martire
PMCID: PMC7489093  PMID: 32361736

Abstract

Objectives

Parents of individuals with disabilities face ongoing responsibilities of providing care and support for their children, even during the child’s adulthood. Past research has shown that this caregiving role is linked to chronic stress and subsequent adverse health outcomes for parents, including impaired cognition. This study examines the impacts of genetic risk for cognitive impairment (apolipoprotein [APOE] ɛ4 allele) among parents of adults with disabilities and comparison parents whose adult children do not have disabilities.

Method

We performed rank order regression analysis of data from the Wisconsin Longitudinal Study (2004–2006 and 2010–2012 surveys and DNA samples). Participants included parents of adults with disabilities (247 mothers and 159 fathers) and comparison parents whose adult children were not disabled (1,482 mothers and 954 fathers).

Results

Mothers who had adult children with disabilities and who were APOE ɛ4 carriers reported significantly declining levels of subjective cognitive functioning over time, but mothers of adults with disabilities who did not have the APOE ɛ4 allele did not manifest this change. Among comparison group mothers, cognitive change over time was not a function of their APOE ɛ4 carrier status. Fathers’ cognitive function did not differ significantly by either parental status or APOE ɛ4 carrier status.

Discussion

The results show that older mothers of adults with disabilities are more susceptible to cognitive impairment than their age peers if they have the genetic risk factor of APOE ɛ4 allele.

Keywords: Caregiving, Cognition, Gender, Genetic risk, Stress

Individuals with developmental disabilities or serious mental illnesses are not rare in the United States—approximately one in six children have developmental disabilities (Boyle et al., 2011) and 4.6% of adults have serious mental health problems (Substance Abuse and Mental Health Services Administration [SAMHSA], 2014), often with lifelong disabling symptoms. Parents of individuals with such disabilities frequently provide care and support to their affected children even after those children have transitioned to adulthood. The prolonged responsibility of caring for and supporting their son or daughter may expose these parents to chronic stresses and subsequent cognitive impairment as well as health problems (Seltzer et al., 2009, 2011; Song, Mailick, Greenberg, Ryff, & Lachman, 2016). Prior research has found that stress associated with caregiving differs between women and men. A recent meta-analysis showed that, on average, female caregivers provide more hours of care for a longer duration than male caregivers. In addition, female caregivers experience higher levels of caregiver burden and subsequent depression as well as poorer health outcomes than male caregivers (Pinquart & Sorensen, 2006).

Studies have consistently found that stress has an adverse influence on cognitive functioning in adulthood. Chronic stress has been linked to cognitive impairments such as accelerated memory decline and reduced attention skills (Lee, Kawachi, & Grodstein, 2004; Lovell, Elliot, Liu, & Wetherell, 2014; Peavy et al., 2009; Romero-Martinez & Moya-Albiol, 2015; Sandi, 2013). A recent review of research on cognitive impairment in informal caregivers of individuals with chronic conditions (e.g., dementia, autism spectrum disorders, stroke) concluded that informal caregivers experienced cognitive decline on multiple dimensions (Romero-Martinez et al., 2018). However, a number of studies examined the adverse effects of chronic stress only among female caregivers (e.g., Lee et al., 2004; Romero-Martinez & Moya-Albiol, 2015) or did not examine gender differences due to the small number of male caregiving participants. The limited number of studies examining gender differences have found that the detrimental effects of caregiving to be more pronounced in women than in men (e.g., Norton et al., 2010; Seeman, McEwen, Albert, & Rowe, 1997; Song et al., 2016).

The risk factors for cognitive impairment include not only environmental factors such as chronic stress, but also genetic factors such as the APOE ɛ4 allele. In humans, the APOE protein is involved in the metabolism of lipids within cells. It is associated with two single-nucleotide polymorphisms (SNPs), rs429358 and rs7412, which genetically establish the three isoforms of the protein: the ɛ2, ɛ3, and ɛ4 alleles (Izaks et al., 2011). The prevalence of each allele in the overall population without dementia is estimated to be 8% (ɛ2), 78% (ɛ3), and 14% (ɛ4) (Belloy, Napolioni, & Greicius, 2019; Rawle et al., 2018). The APOE ɛ4 allele is a significant genetic risk factor for accelerated cognitive decline and development of Alzheimer’s disease from midlife to old age (Barnes et al., 2013; Packard et al., 2007; Rajan et al., 2019; Rawle et al., 2018). Individuals with the APOE ɛ4 allele have greater risks of cognitive decline, particularly in memory, and developing Alzheimer’s disease than those with low-risk APOE alleles (ɛ2 or ɛ3). A longitudinal follow-up of asymptomatic individuals with normal cognition, ranging in age from 21 to 97 years old, showed divergence in memory decline between ɛ4 carriers and non-carriers beginning before age 60 and subsequently accelerating (Caselli et al., 2009). Although both men and women who carry the ɛ4 allele show age-related cognitive decline, the risk appears greater in women than men. For example, women with the APOE ɛ3/ɛ4 genotype had an increased risk of developing mild cognitive impairment or Alzheimer’s disease compared to men with the same APOE genotype (Lehmann et al., 2006; Neu et al., 2017). Similarly, among older adults who had at least one APOE ɛ4 allele, women, but not men, experienced cognitive decline (Mortensen & Hogh, 2001).

In sum, there is empirical evidence of a greater risk of cognitive decline among (a) informal caregivers who are often exposed to chronic stress, such as parents of individuals with disabilities and (b) those who have a genetic risk factor, such as the APOE ɛ4 allele are at greater risk for experiencing cognitive decline, with female carriers at greater risk than male carriers. However, there is no empirical research on the dual impacts of having both an adult child with disabilities and this genetic risk of cognitive impairment.

The current study was designed to fill this gap by examining whether a genetic risk for cognitive impairment, APOE ɛ4 carrier status, moderates the association between long-term parenting of children with disabilities and subjective cognitive functioning in older mothers and fathers using survey and genetic data from the Wisconsin Longitudinal Study (WLS). Specifically, we hypothesize that the adverse impact of the APOE ɛ4 allele on cognitive functioning will be more pronounced among parents whose children have disabilities than among parents whose children do not have disabilities, and that this difference by parenting status will be greater among mothers than among fathers.

Method

Data

The WLS is a long-term study of a random sample of 10,317 women and men who graduated from Wisconsin high schools in 1957; the sample also includes 5,823 randomly selected siblings of the graduates. The original sample members were surveyed in 1957, 1975, 1992, 2004, and 2010–2012, and their siblings were surveyed in 1977, 1994, 2006, and 2010–2012 (Herd, Carr, and Roan, 2014). Most respondents were White, which reflects Wisconsin’s population in the mid-20th century. The WLS also collected saliva samples from survey participants to obtain DNA information, using Oragene kits and a mailback protocol. Saliva samples were first collected in 2007–2008 and again during in-person interviews in 2010–2012 for the subgroup of respondents who had not returned saliva samples in response to the 2007–2008 mailing. A total of 9,606 saliva samples were collected from graduates and sibling panel members. Of them, 9,472 were successfully genotyped and passed the quality control process. The samples that had questionable identity or withdrew consent to provide genetic information were additionally excluded. As the result, 9,012 graduates and sibling panel members were successfully genotyped, passed the quality control process and were available for analysis (see Quality Control Report for Genotypic Data, 2016, for details). The current study used data from survey participants (both graduates and siblings) who completed the 2004–2006 and 2010–2012 survey waves and provided saliva for genetic analysis in either 2007–2008 or 2010–2012. Of the original combined sample of panel members, 8,706 participated in both the 2004–2006 and the 2010–2012 surveys (5,609 graduates and 3,097 siblings). Of this group, 7,152 (4,613 graduates and 2,539 siblings) also provided saliva samples that were suitable for genetic analysis (82.2% of the participants in the two surveys). These panel members form the sample pool for the current study. Figure 1 contains a flow chart of the WLS sample selection.

Figure 1.

Figure 1.

Open in a new tab

Flowchart: WLS analytic sample selection.

The analytic sample consists of two groups. The first group includes respondents who (a) completed both the 2004–2006 and the 2010–2012 surveys and DNA collection and (b) had adult children with developmental disabilities or long-term serious mental health problems. Children’s conditions were initially identified via a review of an array of variables based on survey items related to caregiving and children’s education and disabilities in the 1975–1977 and 1992–1994 WLS surveys. The resulting sample was then confirmed and expanded through a series of direct screener questions asked of all parents in the 2004–2006 and 2010–2012 surveys. The screener consisted of a maximum of 31 questions that began by asking parents if any of their children (living or deceased) had a developmental disability or long-term serious mental health problem, and (if so) the specific diagnosis. We exclude cases from the analytic sample if the child with disabilities was not the biological or adoptive child of the WLS respondent. Using this procedure, we identified 772 parents (452 mothers and 320 fathers) who had a child with a developmental disability or a serious mental health problem that was identified before the 2004–2006 survey. Of these parents, 470 (277 mothers and 193 fathers) participated in both the 2004–2006 and the 2010–2012 surveys and had a valid DNA sample analyzed in the study. Within this group, 39 parents reported that their children with disabilities were deceased. To avoid potential interdependency between graduate and sibling participants from the same family, we randomly selected one participant from each graduate-sibling pair for inclusion in the analytic sample. This resulted in 406 participants (247 mothers and 159 fathers) who had adult children with disabilities. The adult children’s specific diagnoses and frequencies are presented in Table 1.

Table 1.

Diagnoses of Adult Children With Disabilities

Adult child’s conditions n
Intellectual disability 47
Autism spectrum disorder 20
Cerebral palsy 16
Down syndrome 17
Specific developmental disabilities diagnosis (e.g., FAS, epilepsy with below average intelligence) 14
Other developmental disabilities 13
Brain injury 4
Bipolar disorder 181
Schizophrenia 47
Major depression 47
Total N 406
Open in a new tab

Note: FAS = fetal alcohol syndrome.

The second group was a comparison group of WLS respondents who (a) completed both the 2004–2006 and the 2010–2012 surveys and DNA data collection and (b) had at least one child and did not have any children with developmental disabilities or serious mental health problems. We identified 5,695 parents as fulfilling these conditions. Stratified random sampling was used to select a comparison group matched to the parents of adult children with disabilities on age and gender. To increase statistical power, rather than matching one comparison group case to each case with an adult child with a disability (which would have resulted in statistical power = .60), we selected at a ratio of 6:1 that maximized the number of the matched comparison cases, resulting in a comparison group of 2,448 parents (1,482 mothers and 966 fathers) (resulting in statistical power = .83, given alpha, sample size, and effect size).

Measures

Parenting status

Parenting status was coded as a dichotomous variable depending on whether the respondent had any children with a disability (developmental disability or serious mental health problem) (1 = parent of an adult child with a disability, 0 = comparison parent).

Subjective cognitive functioning

Subjective cognitive functioning was assessed by the cognition module of the Health Utilities Index Mark 3 (HUI-3). The HUI-3 consists of eight attributes—vision, hearing, speech, ambulation, dexterity, emotion, cognition, and pain—and it has been widely used to evaluate the outcomes of clinical interventions as well as population health quality (Kaplan et al., 2008; Robert et al., 2009). Results from a broad range of studies have supported both the predictive and construct validity and the test-retest reliability of the HUI-3 (e.g., Feeny et al., 2002). Subjective evaluation of cognitive functioning, especially subjective cognitive decline, is a significant predictor of the development of cognitive impairment and Alzheimer’s disease ( Center for Disease Control and Prevention [CDC], 2019).

To assess subjective cognitive functioning level, the survey included items about two topics: memory and thinking. The memory item asked, “How would you describe your ability to remember things, during the past four weeks? Were you able to remember most things, somewhat forgetful, very forgetful, or unable to remember anything at all?” (1 = able to remember most things, 2 = somewhat forgetful, 3 = very forgetful, 4 = unable to remember anything at all). The thinking item asked, “How would you describe your ability to think and solve day-to-day problems during the past four weeks? Were you able to think clearly and solve problems, had a little difficulty, had a great deal of difficulty, or unable to think or solve problems?” (1 = able to think clearly and solve problems, 2 = had a little difficulty, 3 = had some difficulty, 4 = had a great deal of difficulty, 5 = or unable to think or solve problems). Previous studies utilized the two items to assess subjective cognitive function in population data (e.g., Wong, Smith, Ibrahim, Mustard, & Gignac, 2016). Respondents’ subjective evaluations of the two cognition items were combined and categorized into six levels, as indicated in the current study: level 1 = able to remember most things, think clearly and solve day-to-day problems; level 2 = able to remember most things, but have a little difficulty when trying to think and solve day-to-day problems; level 3 = somewhat forgetful, but able to think clearly and solve day-to-day problems; level 4 = somewhat forgetful, and have a little difficulty when trying to think or solve day-to-day problems; level 5 = very forgetful, and have great difficulty when trying to think or solve day-to-day problems; level 6 = unable to remember anything at all, and unable to think or solve day-to-day problems. Weights are then assigned to each level to represent the population value of cognitive status. The weights in the HUI-3 scoring system were determined by surveying a representative sample’s ratings of selected sets of unique health domains and then estimating the mean ratings of the respondents via econometric approaches (Feeny et al., 2002; Fryback et al., 2007; Robert et al., 2009). The following corresponding weights were assigned by Feeny and coworkers and Fryback and coworkers to each level with a “1” represents the highest level of cognitive functioning and a “0” represents the lowest level of cognitive functioning: level 1 (1.0), level 2 (0.92), level 3 (0.86), level 4 (0.70), level 5 (0.32), and level 6 (0.0).

APOE genotype

The APOE genotype of each respondent was identified by the combined value of alleles in rs7412 and rs429358 SNPs. Those who had any APOE ɛ4 alleles, either homozygous (ɛ4/ɛ4) or heterozygous (ɛ2/ɛ4, ɛ3/ɛ4), were identified as APOE ɛ4 carriers (APOE ɛ4 carrier = 1). Parents who did not have any APOE ɛ4 alleles (i.e., ɛ2/ɛ2, ɛ2/ɛ3, ɛ3/ɛ3) were identified as APOE ɛ4 non-carriers (APOE ɛ4 carrier = 0).

Covariates

We controlled age, education, and physical health in all analyses. Education was measured as years of educational attainment. Physical health was assessed via an item that asked respondents to rate their physical health on a 5-point scale (1 = poor to 5 = excellent). Its validity and predictive power as a health measure have been evidenced in multiple studies (Idler & Benyamini, 1997). Research has shown that older age, lower levels of education, and poorer physical health are associated with poorer cognitive functioning (Alley, Suthers, & Crimmins, 2007; Karlamangla et al., 2014; Salthouse, 2009).

Data Analysis

We estimated rank order regression models to examine the effects of genetic risk for cognitive decline (APOE ɛ4 allele) and parenting status (having an adult child with disabilities) on subjective cognitive functioning, controlling for age, education, and self-rated health. In all analyses, we included rank of cognitive functioning at baseline (2004–2006) and modeled the effects of the independent variables on cognitive functioning at follow-up (2010–2012) to focus on change in rank of cognitive functioning over time. Model 1 examines the main effects of APOE ɛ4 carrier status, parenting status, and gender of parents as well as control variables (age, education, self-rated health). In Model 2, two-way interactions of APOE ɛ4 carrier status, parenting status, and gender of parents were added (APOE ɛ4 carrier × parenting status, APOE ɛ4 carrier × gender, parenting status × parent gender). In Model 3, the three-way interaction of genetic risk (i.e., APOE ɛ4 carrier) × parenting status × parent gender was included to examine potential differences between mothers and fathers in the interaction of genetic risk and parenting status.

Results

Table 2 presents descriptive statistics for the parents whose adult children had disabilities and the comparison parents whose children did not have any known disabilities, for mothers and fathers separately. As indicated above, the two groups were matched on age and gender. Parents’ average age was approximately 64 years old at the first point of data in the present study (the 2004–2006 survey) and about 61% of parents were mothers.

Table 2.

Descriptive Statistics of the Mothers and Fathers of Individuals With Disabilities or Comparison Parents: WLS (2004–2006, 2010–2012)

Mothers of individuals with disabilities Comparison mothers Fathers of individuals with disabilities Comparison fathers
Mean (SD) Mean (SD) Mean (SD) Mean (SD)
Age 64.0 (4.1) 64.1 (4.0) ns 64.5 (4.1) 64.3 (3.9) ns
% APOE ɛ4 carrier 29.2 27.6 ns 23.3 28.0 ns
Education (years) 13.6 (2.2) 13.4 (2.1) ns 15.0 (2.8) 14.2 (2.6) ***
Self-rated health 3.6 (1.0) 3.8 (0.9) *** 3.7 (1.0) 3.8 (0.9) ns
Cognition 2004–2006 0.96 (0.11) 0.97 (0.08) ns 0.95 (0.09) 0.96 (0.10) ns
Cognition 2010–2012 0.93 (0.14) 0.94 (0.11) + 0.93 (0.14) 0.94 (0.12) ns
N 247 1,482 159 954
Open in a new tab

Notes: Comparison parents were matched on age and gender of parents of children with disabilities (1:6 ratio).

ns = nonsignificant. +p ≤ .10, ***p ≤ .001.

The prevalence of the indicator of genetic risk for increased vulnerability to cognitive decline, APOE ɛ4, was comparable for both mothers and fathers whose children had disabilities and their peers who did not have any children with disabilities. The prevalence of each allele in the current analytic sample was 7.8% (ɛ2), 77.3% (ɛ3), and 14.9% (ɛ4), which is in Hardy–Weinberg equilibrium and congruent with the prevalence in overall population without dementia (Belloy et al., 2019; Rawle et al., 2018). Slightly over one-quarter of mothers and fathers carried at least one high-risk allele, ɛ4, in APOE genotype (i.e., ɛ4ɛ4 or ɛ2ɛ4 or ɛ3ɛ4). Among mothers, educational attainment was 13 years, on average, and was comparable for those who had children with disabilities and their peers who did not have children with disabilities. Among fathers, in contrast, those who had children with disabilities reported a higher level of education than those without children with disabilities. Self-rated health differed between the two mother groups; mothers who had adult children with disabilities reported poorer health than their peers who did not have any adult children with disabilities. In contrast, self-rated health did not differ between fathers whose adult children had disabilities and their peers whose adult children did not have such conditions.

Subjective cognitive function did not differ significantly between the two groups of mothers at both points of data collection of the present study: 2004–2006 and 2010–2012. Subjective cognitive function of fathers was also comparable at both points of data collection, regardless of the disability status of their adult children. In 2010–2012, approximately 64% of the mothers and fathers reported their cognition as “able to remember most things, think clearly and solve day-to-day problems” (level 1). However, 22% of mothers and fathers rated their cognition as “somewhat forgetful, but able to think clearly and solve day-to-day problems” (level 2) and approximately 4% of the mothers and fathers reported their cognition as “able to remember most things, but have a little difficulty when trying to think and solve day-to-day problems” (level 3). Overall, 9% of the mothers and fathers reported their cognition as “somewhat forgetful, and have a little difficulty when trying to think or solve day-to-day problems” (level 4) and 1.3% of mothers and 1.8% of the fathers indicated their cognition as “very forgetful, and have great difficulty when trying to think or solve day-to-day problems, or worse” (level 5 and 6).

Table 3 presents the results of rank order regression analyses examining the effects of parenting status and the APOE ɛ4 allele on change in parents’ subjective cognitive function over time, with the moderating effect of gender. By controlling for cognition in 2004–2006, the model estimate change in cognition between that time and 2010–2012 (from age 64–71, on average). Model 1 examines the main effects of having adult children with disabilities and the APOE ɛ4 allele on the subjective cognitive function of parents. In Model 1, parenting status was not predictive of change in subjective cognitive function. However, APOE ɛ4 carrier status was significantly associated with subjective cognition; parents who had the APOE ɛ4 allele reported a greater decline in subjective cognitive function than APOE ɛ4 non-carriers (b = −50.876, p ≤ .05).

Table 3.

Rank Order Regression Predicting Subjective Cognitive Functioning of Parents of Individuals With Disabilities and Comparison Parents: WLS (2004–2006, 2010–2012)

Cognition (2010–2012)
Model 1 Model 2 Model 3
b SE b SE b SE
Cognition (2004–2006) 0.438*** 0.019 0.438*** 0.019 0.438*** 0.019
Age −9.318** 2.987 −9.394** 2.988 −9.521*** 2.986
Parent gender (1 = mother) 2.236 24.536 −1.078 30.360 −14.452 30.931
Education 13.068** 5.175 12.717** 5.181 12.467* 5.179
Self-rated health 85.118*** 12.869 84.844*** 12.874 85.177*** 12.866
APOE ɛ4 carrier (1 = carrier) −50.876* 26.376 −84.975* 43.554 −1143.837** 45.424
Parent status −6.083 33.842 41.667 56.807 −10.842 61.498
Mothers × APOE ɛ4 carrier — — 54.750 54.192 102.262+ 58.230
Mothers × children had disabilities — — −84.693 69.231 4.987 80.113
APOE ɛ4 carrier × children had disabilities — — 10.268 76.025 235.484+ 126.741
Mothers × APOE ɛ4 × children had disabilities — — — — −351.617* 158.385
Constant 906.908 920.122 938.524
R 2 .202 .203 .205
Open in a new tab

Notes: Parent status: 1 = having adult children with disabilities, 0 = not having adult children with disabilities. Parent gender: 1 = mother, 0 = father. APOE ɛ4 carrier: 1 = carrier, 0 = non-carrier. Comparison parents were matched on age and gender of parents of children with disabilities (1:6 ratio).

+ p ≤ .10, *p ≤ .05, **p ≤ .01, ***p ≤ .001.

Model 2 assessed two-way interaction effects (gender × APOE ɛ4 carrier, gender × parenting status, APOE ɛ4 carrier × parenting status) on parents’ subjective cognitive function. The results show that none of these two-way interactions was significant. The results for Model 3, which included the three-way interaction (gender × APOE ɛ4 carrier × parenting status), revealed that parent’s gender had a significant moderating effect on the interaction of parenting status and genetic risk on subjective cognitive decline (b = −351.617, p ≤ .05). Among mothers, genetic vulnerability (i.e., APOE ɛ4 carrier status) was significantly associated with a decline in subjective cognitive function among mothers who had adult children with disabilities compared to mothers who did not have any children with disabilities. However, this pattern was not evident among fathers. Figure 2 illustrates predicted rank of subjective cognition scores of mothers and fathers contingent on their APOE ɛ4 carrier status and adult children’s disabilities.

Figure 2.

Figure 2.

Open in a new tab

Predicted level of subjective cognitive function in mothers and fathers by parenting status and APOE ɛ4 carrier status. NN = parents of individuals with disabilities. Comparison = parents of individuals who did not have disabilities.

Regarding the control variables, the results indicated that, in general, parents who were older, had less education, and had poorer health at baseline experienced a greater decline in subjective cognitive function over time during older age than their counterparts.

Discussion

The findings of the current study show that the impact of the APOE ɛ4 allele on subjective cognitive functioning is contingent on both parenting status and gender of parents, which supports our hypothesis. Specifically, older mothers who had adult children with disabilities and were carriers of the APOE ɛ4 allele experienced greater subjective cognitive decline between the two study points (on average, between age 64 and 71) than mothers who had children with disabilities but did not have the APOE ɛ4 allele. Among comparison group mothers, change in subjective cognitive function over time was not a function of their APOE ɛ4 carrier status. Fathers’ subjective cognitive change over time did not differ by either their APOE ɛ4 carrier status or their children’s disability status.

The gender effect in the expression of genetic risk for subjective cognitive decline in parents whose adult children have disabilities is consistent with prior research. For example, past research reported age-related memory problems among mothers who had a child with a disability but not in fathers (Song et al., 2016). In addition, given the evidence that women are generally more vulnerable than men to the detrimental impacts of stress on cognition (e.g., Sandi, 2013), it might be that the chronic stress of parenting children with disabilities has a more substantial impact on cognition during the life course in mothers relative to fathers. Because mothers are, on average, more involved in care and support of their children with disabilities than fathers over the life course (e.g., Bogossian et al., 2019), mothers are more likely than fathers to experience chronic stress and, in turn, may be at a greater risk of cognitive decline. In addition, our finding on gender difference in susceptibility to the impact of the APOE ɛ4 allele on cognitive decline is consistent with other studies showing that carrying the risky allele has a more pronounced detrimental impact on women than men, particularly at older age (e.g., Neu et al., 2017).

The possible mechanisms through which the chronic stress resulting from providing care and support to adult children with disabilities for a prolonged period accelerates cognitive decline include hypothalamic-pituitary-adrenal (HPA) axis dysregulation and an elevated risk of cardiovascular disease. First, chronic stress has been linked to chronic elevation of glucocorticoids and consequent neurotoxic effects on the brain, which can impact cognitive functioning, in the general population (e.g., Lupien et al., 1998). Higher levels of cortisol during the night were associated with age-related cognitive decline in caregivers (Palma et al., 2011). The empirical evidence of irregular cortisol patterns due to HPA axis dysregulation in parents of individuals with disabilities (e.g., Seltzer et al., 2010) indicates that cognitive decline in this population may be at least partially attributable to HPA dysfunction. Second, chronic stress has been consistently linked to an elevated risk of the development and progression of cardiovascular disease through acute stress responses and long-term pathophysiological changes (e.g., Aalbaek, Graff, & Vestergaard, 2017; Kivimäki & Steptoe, 2018). In addition, the vascular hypothesis of Alzheimer’s disease posits that cardiovascular disease, as well as dozens of other known vascular risk factors for Alzheimer’s disease, may chronically lower blood flow to the brain and accelerate cognitive decline and the development of Alzheimer’s disease over time (de la Torre, 2010). Thus, prolonged exposure to stress might result in cognitive decline via an increased risk of vascular disease. As for the genetic risks of cognitive decline, recent studies have found that the APOE ɛ4 allele is associated with not only cognition but also a certain type of heart disease (Rasmussen, 2016); meta-analyses have shown that APOE ɛ4 is associated with an increased risk of ischemic heart disease (e.g., Bennet et al., 2007). Thus, future studies examining the complex associations between chronic stress, cardiovascular/heart disease or vascular risk factors, and genetic risk could provide a deeper understanding of the mechanisms through which parenting sons or daughters with disabilities for a prolonged period has adverse impacts on parents’ cognition, especially in middle- and old age. Further research on the effects of these two biomarkers on the cognitive aging of parents whose adult children have disabilities would improve the understanding of these important mechanisms.

Some limitations of this study should be acknowledged. First, because we analyzed secondary data, we did not have measures of parents’ stress level specifically due to the conditions of their children with disabilities for the whole sample. Future studies that directly assess parenting stress would provide additional information that would help researchers identify pathways through which the parenting experience impacts cognitive change of parents of children with disabilities. Second, the current study measured parents’ cognition by self-assessment (the HUI-3 scale). Subjective assessment can be affected by several factors unrelated to cognitive impairment or Alzheimer’s disease (AD), such as psychiatric/neurological disease and medications (Jessen et al., 2014). Thus, future studies that seek to replicate the current findings using objective scales of cognitive function would strengthen the findings. Third, the effect size for the three-way interaction (gender × APOE ɛ4 carrier × parenting status) is small (Cohen’s d = .23) and suggests the being the carrier of the APOE risk allele is one of many factors that helps explain cognitive decline in mothers caring for a son or daughter with disabilities.

The current study also has unique strengths including its longitudinal design that allowed us to trace cognitive change among parents over time. In addition, unlike much of the prior research, in which parents volunteered to participate in studies of parenting effects, the current analysis focused on a sample of parents drawn from a population sample who were recruited to the study long before becoming parents; thus, the results are less vulnerable to self-selection bias. Long-term parenting for an adult child with a disability is one example of chronic stress exposure, and the results reported here likely would also be indicative of other sources of stress interacting with genetic risk. Both replication of the current results and extension to studies of other sources of stress exposure are warranted.

In conclusion, the results show that mothers who have children with disabilities as well as genetic risk for Alzheimer’s disease experience greater self-reported cognitive decline in older age than their counterparts. The findings warrant future studies to examine both the pathways through which the two risk factors (gene and environment) have adverse influences on these vulnerable mothers’ subjective cognitive function and the protective resources that can mitigate the adverse influences.

Acknowledgments

We are grateful to Murray Brilliant, PhD, for the Hardy–Weinberg calculations. Data is available at https://ssc.wisc.edu/wlsresearch/data/. This study was not preregistered.

Funding

This work was supported by National Institute on Aging (P01-AG021079); and the Waisman Center at the University of Wisconsin-Madison (U54 HD090256).

Conflict of Interest

None.

References

  1. Aalbaek F. S., Graff S., & Vestergaard M (2017). Risk of stroke after bereavement: A systematic literature review. ACTA Neurologica Scandinavica, 136(4),293–297. doi: 10.1111/ane.12736 [DOI] [PubMed] [Google Scholar]
  2. Alley D., Suthers K., & Crimmins E (2007). Education and cognitive decline in older Americans: Results from the AHEAD sample. Research on Aging, 29(1), 73–94. doi: 10.1177/0164027506294245 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Barnes L. L., Arvanitakis Z., Yu L., Kelly J., De Jager P. L., & Bennett D. A (2013). APOE and change in episodic memory in blacks and whites. Neuroepidemiology, 40, 211–219. doi: 10.1159/000342778 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Belloy M. E., Napolioni V., & Greicius M. D (2019). A quarter century of APOE and Alzheimer’s disease: Progress to date and the path forward. Neuron, 101(5), 820–838. doi: 10.1016/j.neuron.2019.01.056 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Bennet A. M., Di Angelantonio E., Ye Z., Wensley F., Dahlin A., Ahlbom A., … Danesh J (2007). Association of apolipoprotein E genotypes with lipid levels and coronary risk. Journal of the American Medical Association, 298(11), 1300–1311. doi: 10.1001/jama.298.11.1300 [DOI] [PubMed] [Google Scholar]
  6. Bogossian A., King G., Lach L. M., Currie M., Nicholas D., McNeill T., & Saini M (2019). (Unpacking) father involvement in the context of childhood neurodisability research: a scoping review. Disability and Rehabilitation, 41(1), 110–124. doi: 10.1080/09638288.2017.1370497 [DOI] [PubMed] [Google Scholar]
  7. Boyle C. A., Boulet S., Schieve L. A., Cohen R. A., Blumberg S. J., Yeargin-Allsopp M., … Kogan M. D (2011). Trends in the prevalence of developmental disabilities in US children, 1997-2008. Pediatrics, 127(6), 1034–1042. doi: 10.1542/peds.2010-2989 [DOI] [PubMed] [Google Scholar]
  8. Caselli R. J., Dueck A. C., Osborne D., Sabbagh M. N., Connor D. J., Ahern G. L., … Reiman E. M (2009). Longitudinal modeling of age-related memory decline and the APOE epsilon4 effect. The New England Journal of Medicine, 361(3), 255–263. doi: 10.1056/NEJMoa0809437 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Centers for Disease Control and Prevention (CDC). (2019). Subjective cognitive decline—a public health issue. Retrieved from https://www.cdc.gov/aging/aginginfo/subjective-cognitive-decline-brief.html
  10. de la Torr J. C. (2010). The vascular hypothesis of Alzheimer’s disease: Bench to bedside and beyond. Neurodegenerative Disease, 7, 116–121. doi: 10.1159/000285520 [DOI] [PubMed] [Google Scholar]
  11. Feeny D., Furlong W., Torrance G. W., Goldsmith C. H., Zhu Z., DePauw S., … Boyle M (2002). Multiattribute and single-attribute utility functions for the Health Utilities Index Mark 3 system. Medical Care, 40(2), 113–128. doi: 10.1097/00005650-200202000-00006 [DOI] [PubMed] [Google Scholar]
  12. Fryback D. G., Cross Dunham N., Palta M., Hanmer J., Buechner J., Cherepanov, … Kind P (2007). U.S. norms for six generic health-related quality-of-life indexes from the National Health Measurement Study. Medical Care, 45, 1162–1170. doi: 10.1093/ije/dys194 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Herd P., Carr D., & Roan C (2014). Cohort profile: Wisconsin Longitudinal Study (WLS). International Journal of Epidemiology, 43(1), 34–41. doi: 10.1093/ije/dys194 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Idler E. L., & Benyamini Y (1997). Self-rated health and mortality: a review of twenty-seven community studies. Journal of Health and Social Behavior, 38(1), 21–37. [PubMed] [Google Scholar]
  15. Izaks G. J., Gansevoort R. T., van der Knaap A. M., Navis G., Dullaart R. P., & Slaets J. P (2011). The association of APOE genotype with cognitive function in persons aged 35 years or older. PLOS ONE, 6(11), e27415. doi: 10.1371/journal.pone.0027415 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Jessen F., Amariglio R. E., van Boxtel M., Breteler M., Ceccaldi M., Chételat G., … Wagner M.; Subjective Cognitive Decline Initiative (SCD-I) Working Group (2014). A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer’s disease. Alzheimer’s & Dementia, 10(6), 844–852. doi: 10.1016/j.jalz.2014.01.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Kaplan M. S., Huguet N., Orpana H., Feeny D., McFarland B. H., & Ross N (2008). Prevalence and factors associated with thriving in older adulthood: A 10-year population-based study. The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences, 63(10), 1097–1104. doi: 10.1093/gerona/63.10.1097 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Karlamangla A. S., Miller-Martinez D., Lachman M. E., Tun P. A., Koretz B. K., & Seeman T. E (2014). Biological correlates of adult cognition: Midlife in the United States (MIDUS). Neurobiology of Aging, 35(2), 387–394. doi: 10.1016/j.neurobiolaging.2013.07.028 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Kivimäki M., & Steptoe A (2018). Effects of stress on the development and progression of cardiovascular disease. Nature Reviews. Cardiology, 15(4), 215–229. doi: 10.1038/nrcardio.2017.189 [DOI] [PubMed] [Google Scholar]
  20. Lee S., Kawachi I., & Grodstein F (2004). Does caregiving stress affect cognitive function in older women? The Journal of Nervous and Mental Disease, 192(1), 51–57. doi: 10.1097/01.nmd.0000106000.02232.30 [DOI] [PubMed] [Google Scholar]
  21. Lehmann D. J., Refsum H., Nurk E., Warden D. R., Tell G. S., Vollset S. E., … Smith A. D (2006). Apolipoprotein E e3 and impaired episodic memory in community-dwelling elderly people: A marked sex difference. The Hordaland Health Study. Journal of Neurology, Neurosurgery, and Psychiatry, 77(8),902–908. doi: 10.1136/jnnp.2005.077818 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Lovell B., Elliot H., Liu C. C., & Wetherell M. A (2014). Memory failures for everyday tasks in caregivers of children with autism. Research in Developmental Disabilities, 35(11), 3057–3061. doi: 10.1016/j.ridd.2014.07.019 [DOI] [PubMed] [Google Scholar]
  23. Lupien S. J., de Leon M., de Santi S., Convit A., Tarshish C., Nair N. P., … Meaney M. J (1998). Cortisol levels during human aging predict hippocampal atrophy and memory deficits. Nature Neuroscience, 1(1), 69–73. doi: 10.1038/271 [DOI] [PubMed] [Google Scholar]
  24. Mortensen E. L., & Høgh P (2001). A gender difference in the association between APOE genotype and age-related cognitive decline. Neurology, 57(1), 89–95. doi: 10.1212/wnl.57.1.89 [DOI] [PubMed] [Google Scholar]
  25. Neu S. C., Pa J., Kukull W., Beekly D., Kuzman A. Grangadhara P., … Toga A. W (2017). Apolipoprotein E genotype and sex risk factors for Alzheimer disease. JAMA Neurology, 74(10),1178–1189. doi: 10.1001/jamaneurol.2017.2188 [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Norton M. C., Smith K. R., Østbye T., Tschanz J. T., Corcoran C., Schwartz S., … Welsh-Bohmer K. A.; Cache County Investigators (2010). Greater risk of dementia when spouse has dementia? The Cache County study. Journal of the American Geriatrics Society, 58(5), 895–900. doi: 10.1111/j.1532-5415.2010.02806.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Packard C., Westendorp R., Stott D., Caslake M. J., Murray H. M., Shepherd J., … Twomey C.; Prospective Study of Pravastatin in the Elderly at Risk Group. (2007). Association between apolipoprotein E4 and cognitive decline in elderly adults . Journal of American Geriatric Society, 55, 1777–1785. doi: 10.1111/j.1532-5415.2007.01415.x [DOI] [PubMed] [Google Scholar]
  28. Palma K. A., Balardin J. B., Vedana G., de Lima Argimon I. I., Luz C., Schröder N., … Bromberg E (2011). Emotional memory deficit and its psychophysiological correlate in family caregivers of patients with dementia. Alzheimer Disease and Associated Disorders, 25(3), 262–268. doi: 10.1097/WAD.0b013e318209e453 [DOI] [PubMed] [Google Scholar]
  29. Peavy G. M., Salmon D. P., Jacobson M. W., Hervey A., Gamst A. C., Wolfson T., … Galasko D (2009). Effects of chronic stress on memory decline in cognitively normal and mildly impaired older adults. The American Journal of Psychiatry, 166(12), 1384–1391. doi: 10.1176/appi.ajp.2009.09040461 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Pinquart M., & Sorensen S (2006). Gender differences in caregiver stressors, social resources, and health: An updated meta-analysis. Journal of Gerontology: Psychological Sciences, 61B(1), 33–45. doi: 10.1093/geronb/61.1.p33 [DOI] [PubMed] [Google Scholar]
  31. Quality Control Report for Genotypic Data (2016). University of Washington. Retrieved from https://ssc.wisc.edu/wlsresearch/documentation/GWAS/Herd_QC_report.pdf
  32. Rajan K. B., Barnes L. L., Wilson R. S., Weuve J., McAninch E. A., & Evans D. A (2019). Apolipoprotein E genotypes, age, race, and cognitive decline in a population sample. Journal of the American Geriatrics Society, 67(4), 734–740. doi: 10.1111/jgs.15727 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Rasmussen K. L. (2016). Plasma levels of apolipoprotein E, APOE genotype and risk of dementia and ischemic heart disease: A review. Atherosclerosis, 255, 145–155. doi: 10.1016/j.atherosclerosis.2016.10.037 [DOI] [PubMed] [Google Scholar]
  34. Rawle M. J., Davis D., Bendayan R., Wong A., Kuh D., & Richards M (2018). Apolipoprotein-E (Apoe) ε4 and cognitive decline over the adult life course. Translational Psychiatry, 8(1), 18. doi: 10.1038/s41398-017-0064-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Robert S. A., Cherepanov D., Palta M., Dunham N. C., Feeny D., & Fryback D. G (2009). Socioeconomic status and age variations in health-related quality of life: Results from the National Health Measurement Study. The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 64(3), 378–389. doi: 10.1093/geronb/gbp012 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Romero-Martinez A., & Moya-Albiol L (2015). An autistic endophenotype and testosterone are involved in an atypical decline in selective attention and visuospatial processing in middle-aged women. International Journal of Environmental Research and Public Health, 12(12), 15960–15966. doi: 10.3390/ijerph121215033 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Romero-Martínez Á., Hidalgo-Moreno G., & Moya-Albiol L (2018). Neuropsychological consequences of chronic stress: The case of informal caregivers. Aging & Mental Health, 24(2), 259–271. doi: 10.1080/13607863.2018.1537360 [DOI] [PubMed] [Google Scholar]
  38. Salthouse T. A. (2009). When does age-related cognitive decline begin? Neurobiology of Aging, 30(4), 507–514. doi: 10.1016/j.neurobiolaging.2008.09.023 [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Sandi C. (2013). Stress and cognition. WIREs Cognitive Science, 4, 245–261. doi: 10.1002/wcs.1222 [DOI] [PubMed] [Google Scholar]
  40. Seeman T. E., McEwen B. S., Albert M. S., & Rowe J. W (1997). Increase in urinary cortisol excretion and memory decline: MacArthur studies of successful aging. Journal of Clinical Endocrinology & Metabolism, 82, 2458–2465. doi: 10.1210/jcem.82.8.4173 [DOI] [PubMed] [Google Scholar]
  41. Seltzer M. M., Almeida D. M., Greenberg J. S., Savla J., Stawski R. S., Hong J., & Taylor J. L (2009). Psychosocial and biological markers of daily lives of midlife parents of children with disabilities. Journal of Health and Social Behavior, 50(1), 1–15. doi: 10.1177/002214650905000101 [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Seltzer, M. M., Greenberg, J. S., Hong, J., Smith, L. E., Almeida, D. M., Coe, C., & Stawski, R. S. (2010). Maternal cortisol levels and behavior problems in adolescents and adults with ASD. Journal of Autism and Developmental Disorders, 40(4), 457–469. doi: 10.1007/s10803-009-0887-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Seltzer M. M., Floyd F., Song J., Greenberg J., & Hong J (2011). Midlife and aging parents of adults with intellectual and developmental disabilities: Impacts of lifelong parenting. American Journal on Intellectual and Developmental Disabilities, 116(6), 479–499. doi: 10.1352/1944-7558-116.6.479 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Song J., Mailick M. R., Greenberg J. S., Ryff C. D., & Lachman M. E (2016). Cognitive aging in parents of children with disabilities. The Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 71(5), 821–830. doi: 10.1093/geronb/gbv015 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Substance Abuse and Mental Health Services Administration (SAMHSA) (2014). Center for Behavioral Health Statistics and Quality. The NSDUH Report: State Estimates of Adult Mental Illness from the 2011 and 2012 National Surveys on Drug Use and Health. Rockville, MD: Substance Abuse and Mental Health Services Administration. [Google Scholar]
  46. Wong I. S., Smith P. M., Ibrahim S., Mustard C. A., & Gignac M. A (2016). Mediating pathways and gender differences between shift work and subjective cognitive function. Occupational and Environmental Medicine, 73(11), 753–760. doi: 10.1136/oemed-2016-103774 [DOI] [PubMed] [Google Scholar]

Articles from The Journals of Gerontology Series B: Psychological Sciences and Social Sciences are provided here courtesy of Oxford University Press

RESOURCES