The New Zealand minds for minds autism spectrum disorder self-reported cohort

Virués‐Ortega, Javier; Lehnert, Klaus; Swan, Brendan; Taylor, Michael W.; Southee, Adrienne; Dougan, Dane; Taylor, Juliet; Hill, Rosamund; Snell, Russell G.; Jacobsen, Jessie C.

doi:10.1016/j.rasd.2016.12.003

Cited by 5 publications

(5 citation statements)

References 8 publications

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“…Our estimated male to female ratio of 3.6:1 lies between widely cited 4:1 estimates ( American Psychiatric Association, 2013a ; Baio et al, 2018 ) and the 3:1 estimate of Loomes et al (2017) that they determine to be the ‘true’ ratio in a recent meta-analysis ( Loomes et al, 2017 ). Patterns across ethnic groups are consistent with those seen in previous New Zealand studies ( Eggleston et al, 2019 ; Virues-Ortega et al, 2017 ) and the results of the NZHS ( MoH, 2019a ). They also reflect previous US studies in which rates for minority ethnic groups (Hispanic and African American) were lower than European-American rates ( Baio et al, 2018 ; Kogan et al, 2008 ).…”

Section: Discussionsupporting

confidence: 90%

“…Rates of specific co-occurring conditions are consistent with, although often at the lower end of, epidemiological literature (Leyfer et al, 2006;Mattila et al, 2010;Salazar et al, 2015;Simonoff et al, 2008;Van Steensel et al, 2013;Virues-Ortega et al, 2017). Our estimated rate of co-occurring intellectual disability (30%) is in line with the recent CDC estimate of 31% and comfortably in the range of estimates in the wider literature of 16.7% to 84% (Postorino et al, 2016).…”

Section: Asd Overallsupporting

confidence: 87%

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Autism spectrum disorder/Takiwātanga: An Integrated Data Infrastructure-based approach to autism spectrum disorder research in New Zealand

Bowden

Thabrew

Kokaua

et al. 2020

Autism

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New Zealand has few estimates of the prevalence of autism spectrum disorder and no national registry. The use of administrative data sources is expanding and could be useful in autism spectrum disorder research. However, the extent to which autism spectrum disorder can be captured in these data sources is unknown. In this study, we utilised three linked administrative health data sources from the Integrated Data Infrastructure to identify cases of autism spectrum disorder among New Zealand children and young people. We then investigated the extent to which a range of mental health, neurodevelopmental and related problems co-occur with autism spectrum disorder. In total, 9555 unique individuals aged 0–24 with autism spectrum disorder were identified. The identification rate for 8-year-olds was 1 in 102. Co-occurring mental health or related problems were noted in 68% of the autism spectrum disorder group. The most common co-occurring conditions were intellectual disability, disruptive behaviours and emotional problems. Although data from the Integrated Data Infrastructure may currently undercount cases of autism spectrum disorder, they could be useful for monitoring service and treatment-related trends, types of co-occurring conditions and for examining social outcomes. With further refinement, the Integrated Data Infrastructure could prove valuable for informing the national incidence and prevalence of autism spectrum disorder and the long-term effectiveness of clinical guidelines and interventions for this group. Lay abstract New Zealand has few estimates of the prevalence autism spectrum disorder and no national registry or data set to identify and track cases. This hinders the ability to make informed, evidence-based decisions relating to autism spectrum disorder. In this study, we utilised linked health and non-health data to develop a method for identifying cases of autism spectrum disorder among children and young people in New Zealand. In addition, we examined rates of co-occurring mental health, neurodevelopmental and related conditions among this cohort and compared these to the general population. The method identified almost 10,000 children and young people with autism spectrum disorder in New Zealand. Co-occurring mental health or related problems were found in over 68% of this group (nearly seven times higher than the general population), and around half were identified with multiple co-occurring conditions. The most frequently identified conditions were intellectual disability, disruptive behaviours and emotional problems. We have developed a useful method for monitoring service and treatment-related trends, number and types of co-occurring conditions and examining social outcomes among individuals with autism spectrum disorder. While the method may underestimate the prevalence of autism spectrum disorder in New Zealand, it provides a significant step towards establishing a more comprehensive evidence base to inform autism spectrum disorder–related policy.

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Section: Discussionsupporting

confidence: 90%

Section: Asd Overallsupporting

confidence: 87%

Autism spectrum disorder/Takiwātanga: An Integrated Data Infrastructure-based approach to autism spectrum disorder research in New Zealand

Bowden

Thabrew

Kokaua

et al. 2020

Autism

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“…Within the fetal PPIN, a common group of genes (i.e., KANSL1 , LINC02210 , RP11-259G18.3 , MAPT-AS1 , RP11-259G18.1 , and MAPT ) were associated with most of the mood/brain-related phenotypes (e.g., neuroticism, Parkinson’s disease, depression, mood swings, and white matter microstructure). Many of these phenotypes, particularly depression and mood traits ( Croen et al, 2015 ; Virues-Ortega et al, 2017 ; Chien et al, 2021 ), are known to co-occur with autism. Consistent with this, depression and mood disorders were observed to have an increased prevalence in autistic New Zealanders.…”

Section: Discussionmentioning

confidence: 99%

De novo network analysis reveals autism causal genes and developmental links to co-occurring traits

et al. 2023

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Autism is a complex neurodevelopmental condition that manifests in various ways. Autism is often accompanied by other conditions, such as attention-deficit/hyperactivity disorder and schizophrenia, which can complicate diagnosis and management. Although research has investigated the role of specific genes in autism, their relationship with co-occurring traits is not fully understood. To address this, we conducted a two-sample Mendelian randomisation analysis and identified four genes located at the 17q21.31 locus that are putatively causal for autism in fetal cortical tissue (LINC02210,LRRC37A4P,RP11-259G18.1, andRP11-798G7.6).LINC02210was also identified as putatively causal for autism in adult cortical tissue. By integrating data from expression quantitative trait loci, genes and protein interactions, we identified that the 17q21.31 locus contributes to the intersection between autism and other neurological traits in fetal cortical tissue. We also identified a distinct cluster of co-occurring traits, including cognition and worry, linked to the genetic loci at 3p21.1. Our findings provide insights into the relationship between autism and co-occurring traits, which could be used to develop predictive models for more accurate diagnosis and better clinical management.

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“…The copyright holder for this preprint this version posted April 26, 2023. ; https://doi.org/10.1101/2023.04.24.23289060 doi: medRxiv preprint traits (Chien et al 2021;Virues-Ortega et al 2017;Croen et al 2015), are known to co-occur with autism. Consistent with this, depression and mood disorders were observed to have an increased prevalence in autistic New Zealanders.…”

Section: (Which Was Not Certified By Peer Review)mentioning

confidence: 99%

An unbiasedde novonetwork analysis uncovering causal genes and the developmental intersection between autism and co-occurring traits

Miller

Golovina

Wicker

et al. 2023

Preprint

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Autism is a complex neurodevelopmental condition that manifests in various ways. Autism is often accompanied by other neurological disorders, such as ADHD, anxiety, and schizophrenia, which can complicate diagnosis and management. While research has investigated the role of specific genes in autism, their relationship with co-occurring traits is not fully understood. To address this gap, we conducted a two-sample Mendelian Randomisation analysis and identified four genes located at the 17q21.31 locus that are causally linked to autism in fetal cortical tissue (i.e. LINC02210, LRRC37A4P, RP11-259G18.1, RP11-798G7.6). LINC02210 was also identified as being causally related to autism in adult cortical tissue. By integrating data from expression quantitative trait loci [eQTLs], genes, and protein interactions we identified that the 17q21.31 locus contributes to the intersection between autism and other neurological traits and conditions in fetal cortical tissue. We also identified an additional distinct cluster of co-occurring traits, including cognition and worry, linked to genetic loci at 3p21.1. Our results support the hypothesis that an individual's autism phenotype is partially determined by their genetic risk for co-occurring conditions. Overall, our findings provide insights into the complex relationship between autism and co-occurring conditions, which could be used to develop predictive models for more accurate diagnosis and better clinical management.

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The New Zealand minds for minds autism spectrum disorder self-reported cohort

Cited by 5 publications

References 8 publications

Autism spectrum disorder/Takiwātanga: An Integrated Data Infrastructure-based approach to autism spectrum disorder research in New Zealand

Autism spectrum disorder/Takiwātanga: An Integrated Data Infrastructure-based approach to autism spectrum disorder research in New Zealand

De novo network analysis reveals autism causal genes and developmental links to co-occurring traits

An unbiasedde novonetwork analysis uncovering causal genes and the developmental intersection between autism and co-occurring traits

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