Clinical subtyping using community detection: Limited utility?

ObjectivesTo discover psychiatric subtypes, researchers are adopting a method called community detection. This method was not subjected to the same scrutiny in the psychiatric literature as traditional clustering methods. Furthermore, many community detection algorithms have been developed without psychiatric sample sizes and variable numbers in mind. We aim to provide clarity to researchers on the utility of this method.MethodsWe provide an introduction to community detection algorithms, specifically describing the crucial differences between correlation-based and distance-based community detection. We compare community detection results to results of traditional methods in a simulation study representing typical psychiatry settings, using three conceptualizations of how subtypes might differ.ResultsWe discovered that the number of recovered subgroups was often incorrect with several community detection algorithms. Correlation-based community detection fared better than distance-based community detection, and performed relatively well with smaller sample sizes. Latent profile analysis was more consistent in recovering subtypes. Whether methods were successful depended on how differences were introduced.ConclusionsTraditional methods like latent profile analysis remain reasonable choices. Furthermore, results depend on assumptions and theoretical choices underlying subtyping analyses, which researchers need to consider before drawing conclusions on subtypes. Employing multiple subtyping methods to establish method dependency is recommended

Menstruation and menopause in autistic adults: Periods of importance?

Autism spectrum conditions were once seen as a predominantly male condition. This has caused a paucity of information on common events in the lives of women, such as menstruation and menopause. Some smaller studies indicate that autistic women might suffer from increased difficulties surrounding these events. This study aims to investigate whether autistic women experience more frequent premenstrual dysphoric disorder, and increased complaints surrounding menopause. In partly overlapping samples (premenstrual dysphoric disorder, n = 70, n(ASC) = 28, n(comparisons) = 42; menopause, n = 65, n(ASC) = 30, n(comparisons) = 35), we investigated premenstrual dysphoric disorder prevalence and menopausal complaints. In 70 individuals, we did not find an increased prevalence of premenstrual dysphoric disorder in autistic women (14.3%) compared with non-autistic women (9.5%). In 65 women aged 40 years and above, we found that autistic women did experience higher levels of menopausal complaints. In autistic women, higher menopausal complaints were associated with higher levels of depression and autistic traits. In non-autistic women, menopausal complaints were associated with increased inattention, hyperactivity/impulsivity (i.e. attention deficit hyperactivity disorder traits), and depression. With this work, we show the important role that major reproductive milestones can have in an autistic woman’s life. LAY ABSTRACT: Autism spectrum conditions were once seen as a predominantly male condition, but this has caused research to have little focus on women. Therefore, little is known about menstruation and menopause in autism spectrum conditions. Some smaller studies indicate that autistic individuals might suffer from increased difficulties surrounding these events. This study aimed to investigate whether autistic women experience more frequent premenstrual dysphoric disorder, causing extreme physical, emotional, and functional impairment. In a partly overlapping sample, we also examined whether women with autism spectrum condition experience increased complaints surrounding menopause. We did not find an increased prevalence of premenstrual dysphoric disorder in autism spectrum conditions (14.3%) compared with non-autistic women (9.5%). Those with autism spectrum conditions did experience increased menopausal complaints. These menopausal complaints were associated with higher levels of depression and autistic traits. In non-autistic women, menopausal complaints were associated with increased inattention, hyperactivity/impulsivity (i.e. attention deficit hyperactivity disorder traits), and depression. With this work, we show the important role that major reproductive milestones can have in an autistic woman’s life

One size does not fit all: An individualized approach to understand heterogeneous cognitive performance in autistic adults

Cognitive performances of autistic people vary widely. Therefore, previous group-based comparisons on cognitive aging in autistic adults might have overlooked those autistic adults that are particularly vulnerable for cognitive decline. Multivariate normative comparisons (MNC) statistically assess individual cognitive differences on the entire cognitive profile. Cognitive deviancy as indicated by MNC accurately predicts future cognitive decline, and is therefore sensitive in detecting meaningful cognitive differences. The current study aimed to (1) investigate the applicability of MNC to assess cognitive performance in autism individually, and (2) understand heterogeneous cognitive performance in autistic adults. As pre-registered, we performed MNC in a sample of 254 non-autistic adults, and two independent samples of respectively 118, and 86 autistic adults (20-85 years, mean: 50 years). Cognitive performance was measured on 11 outcomes in six domains (verbal/visual memory, working memory, verbal fluency, Theory of Mind, and psychomotor speed). Using MNC, about twice as many autistic individuals had a deviant cognitive profile (i.e., deviated statistically from the multivariate normspace) as compared to non-autistic individuals. Importantly, most autistic individuals (&gt;80%) did not have a deviant cognitive profile. Having a deviant profile was significantly associated with higher levels of psychological distress in autistic adults specifically, showing the clinical relevance of this method. Therefore, MNC seem a useful tool to individually detect meaningful cognitive differences in autism. These results are consistent with previous cognitive studies suggesting that most autistic adults show fairly similar cognitive profiles to non-autistic adults, yet highlight the necessity for approaches reflecting the heterogeneity observed in autistic people.</p