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Anticholinergic Medications And Cognitive Outcomes In Autistic Adults

Anticholinergic Medications And Cognitive Outcomes In Autistic Adults


This study investigates the impact of anticholinergic (AC) medications on cognitive outcomes in autistic adults, an area that has not been extensively researched. AC medications, known for their potential to cause cognitive impairment, are commonly used for various medical and psychiatric conditions. In older adults, exposure to AC medications has been associated with cognitive disorders, including Alzheimer’s disease, collectively referred to as anticholinergic cognitive burden (ACB).

A cohort of autistic adults aged 40–83, recruited through Simons Powering Autism Research’s Research Match service, participated in this research. Medication use and memory complaints were self-reported at Time 1 (T1), with a subset of participants providing follow-up information 2 years later at Time 2 (T2). The study utilized two scales to assess the potency of AC medications.

Findings revealed a significant proportion (48.2%–62.9%) of autistic adults reported using at least one medication with AC effects. Moreover, 20.5% to 26.5% reported clinically relevant levels of AC medication (potency ≥3). After adjusting for birth-sex and age, hierarchical linear regression models demonstrated that higher total ACB scores and AC potency values of ≥3 were predictive of increased memory complaints. Logistic regression models further indicated that AC medications at T1 were associated with self-reported cognitive decline at the 2-year follow-up.

This study underscores the prevalence of AC medication use among autistic adults and suggests a link between AC exposure and cognitive outcomes, including memory complaints and declines in thinking abilities. The findings emphasize the importance of understanding the potential cognitive impact of AC medications, including the risk of conditions such as dementia, in the context of autistic adults.


This text discusses the crucial role of acetylcholine in cognition, particularly in learning and memory processes. Cholinergic neurons originating from the basal forebrain project widely to the cerebral cortex, with the hippocampus, a key structure for memory, receiving inputs from this cholinergic system. Dysfunction in the cholinergic system is linked to cognitive decline associated with aging and disorders such as Alzheimer’s disease.

The cholinergic hypothesis of Alzheimer’s disease suggests that medications targeting the cholinergic system, such as cholinesterase inhibitors, can be used for symptomatic management. In contrast, anticholinergic (AC) medications, commonly prescribed for various medical and psychiatric conditions, block the action of acetylcholine at receptors in the nervous system.

Aging individuals using AC medications are associated with cognitive impairments, and a higher AC exposure is linked to an elevated risk of delirium, dementia, mild cognitive impairment, and Alzheimer’s disease. Given the high prevalence of medical and psychiatric conditions in autistic individuals, they are likely to have increased AC exposure throughout their lifespan. Older autistic adults, in particular, exhibit a higher prevalence of cognitive disorders.

While cognitive aging trajectories in autistic adults compared to non-autistic adults present varying results in cross-sectional and longitudinal studies, the text highlights the need for further research. The study under discussion aims to fill this gap by characterizing AC medication usage in middle-aged and older autistic adults, exploring associations with self-reported memory problems, and examining the correlation with self-reported cognitive decline over a 2-year period. The hypotheses suggest that AC medication use is common among this population and may be associated with memory problems and cognitive decline.


This passage outlines the recruitment and characterization of a sample of autistic middle-aged and older adults aged 40 and above for a research study. The participants were recruited through Simons Powering Autism Research’s (SPARK) Research Match service, and the study aimed to investigate various aspects of autistic adult outcomes.

The research included two main studies, referred to as Study 1 and Study 2, each involving a distinct survey battery. The initial survey was conducted in December 2019 and January 2020, and a follow-up survey took place 2 years later in December 2021 and January 2022. The text provides detailed information about the recruitment process, inclusion criteria, and the specific measures used in the studies. Participants designated as “independent” adults were those capable of self-consent and unlikely to have co-occurring intellectual disabilities.

To ensure the validity of reported autism diagnoses, electronic medical records from SPARK participants were examined, confirming a high accuracy rate of 98.8% in an independent study. The participants self-disclosed a community-based professional autism spectrum diagnosis, and autistic traits were assessed using the Autism-Spectrum Quotient (AQ-28). The majority of participants scored at or above the cutoff indicating significant autistic traits.

The final samples for the studies included 415, 382, and 197 autistic adults, respectively, and age ranges varied across the studies. Given the prevalence of co-occurring medical and psychiatric conditions in autistic individuals, as well as high rates of polypharmacy, the researchers anticipated a high likelihood of anticholinergic (AC) medication use in this population. The rationale for not excluding participants with neurological or neurodegenerative conditions is explained, and the studies received approval from The George Washington University Institutional Review Board, adhering to ethical procedures and informed consent in line with the Declaration of Helsinki.

The passage describes the methodology employed in a study focused on assessing anticholinergic (AC) medication usage and its association with cognitive outcomes in middle-aged and older autistic adults. The research involved demographic information collection, medication reporting, coding based on two AC scales (CRIDECO Anticholinergic Load Scale – CALS, and Anticholinergic Cognitive Burden/ACB Scale), and analysis of self-reported memory complaints and cognitive decline.

Demographic information, including age, gender identity, sex assigned at birth, ethno-racial identity, and educational level, was collected. Participants reported their current medication usage in a detailed health questionnaire at Time 1, specifying prescription and over-the-counter medications, as well as vitamins and supplements. Only participants with complete and unambiguous medication information were included in the analyses.

Medications were coded using the CALS and ACB Scale, both assessing AC potency on a scale from 1 to 3. The CALS was developed to provide a comprehensive scale of ACB, incorporating findings from seven existing AC scales. ACB was characterized in three ways for each scale: dichotomous coding for AC medication use, total ACB score, and dichotomous coding for clinically meaningful ACB score (≥3).

Self-reported memory complaints were assessed using the Prospective and Retrospective Memory Questionnaire (PRMQ) at Time 1. The questionnaire included 16 items, and participants responded on a 6-point Likert scale. Memory failures were categorized into retrospective and prospective, probing issues related to past events and future actions.

At Time 2, a subset of participants completed the self-report version of the Eight-item Interview to Differentiate Aging and Dementia (AD8). The AD8 assessed changes in thinking and memory over the last several years, with participants responding to three options: “YES, a change,” “NO, no change,” or “N/A, don’t know.” The AD8 total score was generated, and two dichotomous scores (cut-offs of 1 and 2) were evaluated for associations with self-reported cognitive decline.

Statistical Analysis

Statistical analyses included descriptive characterizations of AC medication use and ACB (Study 1A), examination of associations between ACB and self-reported memory complaints (Study 1B), and exploration of associations between ACB at Time 1 and self-reported cognitive decline at Time 2 (Study 2). Logistic regression models were employed for the analyses, with age and sex assigned at birth as control variables. The study prioritized specificity and sensitivity, considering both “traditional” and “conservative” cut-off scores in the AD8 analysis. All statistical analyses were conducted using R (v.4.2.0).


In Study 1A, which aimed to characterize anticholinergic (AC) medication use and its cognitive burden (ACB) in middle-aged and older autistic adults, the results revealed a substantial prevalence of AC medication usage. Specifically, 62.9% of participants reported using at least one AC medication according to the CRIDECO Anticholinergic Load Scale (CALS), and 48.2% according to the Anticholinergic Cognitive Burden/ACB Scale. The range of ACB scores varied, with a mean of 1.8 (SD = 2.1) on the CALS and 1.2 (SD = 1.8) on the ACB Scale. About 26.5% and 20.5% of autistic adults reported ACB scores ≥3 on the CALS and ACB Scale, respectively.

The study illustrated the most common types of AC medications reported by participants, as indicated by the CALS and ACB Scale. Psychotropic medications, including antidepressants, antipsychotics, and benzodiazepines, along with antihistamines, were prevalent in the sample. Common antidepressants included SSRIs, TCAs, and SNRIs, while antipsychotics encompassed both atypical and conventional variants. Reported antihistamines comprised medications such as diphenhydramine, hydroxyzine, and loratadine, and benzodiazepines included clonazepam, diazepam, and lorazepam. Additionally, biguanides, beta-blockers, opioids, H2-blockers, and skeletal muscle relaxants were frequently reported.

In Study 1B, investigating associations between ACB and self-reported memory “failures” at Time 1 (T1), hierarchical regression models using both CALS and ACB Scale results indicated that, after accounting for age and sex assigned at birth, higher total ACB and ACB scores ≥3 predicted greater concurrent self-reported memory complaints.

In Study 2, focusing on associations between ACB at T1 and self-reported cognitive decline at Time 2 (T2), logistic regression models were applied. For the CALS, after controlling for age at T2 and sex assigned at birth, ACB total score predicted the AD8 ≥1 cut-off at T2. However, no other logistic regression model was significant. For the ACB Scale, after controlling for age at T2 and sex assigned at birth, neither the logistic regression model with the ACB total score nor ACB ≥3 significantly predicted the AD8 ≥1 cut-off at T2. Nevertheless, the model with ACB total score approached significance. ACB did not significantly predict AD8 ≥2 at T2 for both CALS and ACB Scale.


The study addresses a significant gap in autism research, which has primarily focused on children and adolescents, leaving a dearth of knowledge about aging and cognition in autistic adults. Specifically, it explores the impact of anticholinergic (AC) medication exposure on cognition and aging-related cognitive trajectories in middle-aged and older autistic adults.

The research confirms a high prevalence of AC medication use in this population, with 62.9% and 48.2% of participants reporting usage according to the CRIDECO Anticholinergic Load Scale (CALS) and Anticholinergic Cognitive Burden/ACB Scale, respectively. Notably, 20.5%-26.5% of autistic adults reported clinically meaningful levels of AC medication use (ACB score ≥3). Comparisons with broader aging literature reveal variations in AC medication prevalence, emphasizing the need to consider specific factors such as geographical location, sample characteristics, and evolving medication trends.

The study uniquely associates AC medication use with self-reported cognitive complaints, indicating that higher AC medication levels are linked to concurrent prospective and retrospective memory problems. This finding aligns with broader research associating AC medication use with subjective cognitive decline in various populations, emphasizing the importance of considering AC medication effects on cognitive outcomes.

Despite the study’s strengths, such as a large sample size and robust AC medication characterization, there are limitations. The absence of autistic individuals with co-occurring intellectual disabilities raises questions about the generalizability of findings. Additionally, reliance on self-reported data, including cognitive decline and memory issues, introduces potential biases. Future research should incorporate medical record reviews and objective cognitive measures.

The study underscores the need for further investigation into AC medication effects on cognitive functioning in autistic adults. Given the elevated risk of cognitive challenges reported in this population, understanding and mitigating the impact of AC medication use on aging-related outcomes become crucial. The study encourages healthcare providers to exercise caution in prescribing AC medications to autistic adults, particularly considering potential risks and exploring alternative interventions. The findings prompt a comprehensive exploration of adverse effects beyond cognitive outcomes, such as falls and mortality, to enhance the overall well-being of autistic individuals in their aging journey.

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