Auli Suominen

Risk of Autism Spectrum Disorders in Low Birth Weight and Small for Gestational Age Infants

OBJECTIVE To examine the relationship between birth weight, gestational age, small for gestational age (SGA), and 3 of the most common autism spectrum disorder (ASD) subtypes. STUDY DESIGN In this population-based case-control study conducted in Finland, 4713 cases born between 1987 and 2005 with International Classification of Diseases-diagnoses of childhood autism, Asperger syndrome, or pervasive developmental disorder (PDD), were ascertained from the Finnish Hospital Discharge Register. Four controls, individually matched on sex, date of birth, and place of birth, were selected from the Finnish Medical Birth Register for each case. Conditional logistic regression models were used to assess whether birth weight and gestational age information predicted ASD after controlling for maternal age, parity, smoking during pregnancy, and psychiatric history, as well as for infants major congenital anomalies. RESULTS Very low (<1500 g) and moderately low (<2500 g) birth weight, very low gestational age (less than 32 weeks), and SGA increased risk of childhood autism (adjusted OR 3.05, 95% CI 1.4-6.5; 1.57, 1.1-2.3; 2.51, 1.3-5.0; and 1.72, 1.1-2.6, respectively). Very low and moderately low birth weight, very low gestational age, and SGA were also associated with increase in PDD risk (OR 3.44, 95% CI 1.9-6.3; 1.81, 1.4-2.4; 2.46, 1.4-2.3; and 2.24, 1.7-3.0, respectively). No associations were found between the perinatal characteristics and Asperger syndrome. The increased risks persisted after controlling for selected potential confounders. CONCLUSIONS The finding that low birth weight, prematurity, and SGA were related to childhood autism and PDD but not to Asperger syndrome suggests that prenatal factors related to these exposures may differ for these ASD subtypes, which may have preventive implications.

Preterm Birth and Poor Fetal Growth as Risk Factors of Attention-Deficit/Hyperactivity Disorder

BACKGROUND: Previous studies have shown an association between prematurity and attention-deficit/hyperactivity disorder (ADHD). Results concerning late preterm infants are controversial, and studies examining fetal growth represented by weight for gestational age are scarce. Our objective was to examine the association between gestational age by each week of fetal maturity, weight for gestational age, and ADHD. METHODS: In this population-based study, 10 321 patients with ADHD, diagnosed according to the International Classification of Diseases and 38 355 controls individually matched for gender, date and place of birth, were identified from Finnish nationwide registers. Perinatal data were obtained from the Finnish Medical Birth Register. Conditional logistic regression was used to examine the association between gestational age, weight for gestational age, and ADHD after controlling for confounding factors. RESULTS: The risk of ADHD increased by each declining week of gestation. The associations were robust after adjusting for confounders. An elevated risk also was seen among late preterm and early term infants. As for fetal growth, the odds ratio showed a U-shaped curve with an increased risk seen when the weight for gestational age was 1 SD below and 2 SD above the mean. CONCLUSIONS: Our findings suggest that each gestational week has significance for child’s subsequent neurodevelopment and risk for ADHD. We also showed that poor fetal growth increased the risk of ADHD. This highlights the importance of taking into account both prematurity and poor fetal growth when planning the timing of birth as well as later follow-up and support policies.

Smoking during Pregnancy and Risk of Autism Spectrum Disorder in a Finnish National Birth Cohort

BACKGROUND Results of previous population-based studies examining associations between smoking during pregnancy and autism spectrum disorders (ASD) are contradictory. Furthermore, there is a lack of population-based studies examining the relationship between smoking during pregnancy and the main diagnostic subtypes of ASD. METHODS We conducted a population-based nested case-control study based on the Finnish Prenatal Study of Autism (FIPS-A) among liveborn infants delivered in Finland between 1987 and 2005. Data on maternal smoking during pregnancy were available from the Finnish Medical Birth Register (FMBR) since October 1990. Data on ASD in the offspring were obtained from the Finnish Hospital Discharge Register (FHDR). RESULTS Among the three subtypes of ASD, maternal smoking during the whole pregnancy was associated with an increased risk of pervasive developmental disorder (PDD) (odds ratio 1.2, 95% confidence interval 1.0, 1.5). The increase in odds persisted after controlling for maternal age, mothers socio-economic and psychiatric status, and infants weight for gestational age. However, smoking exposure limited to the first trimester was not associated with PDD or any of the other ASD subtypes. CONCLUSIONS Maternal smoking is related to a modest increase in risk of PDD, while no associations were observed for childhood autism and Aspergers syndrome.

Epilepsy Among Children and Adolescents with Autism Spectrum Disorders: A Population-Based Study

The present population-based study examines associations between epilepsy and autism spectrum disorders (ASD). The cohort includes register data of 4,705 children born between 1987 and 2005 and diagnosed as cases of childhood autism, Asperger’s syndrome or pervasive developmental disorders—not otherwise specified. Each case was matched to four controls by gender, date of birth, place of birth, and residence in Finland. Epilepsy was associated with ASD regardless of the subgroup after adjusting for covariates. The associations were stronger among cases with intellectual disability, especially among females. Epilepsy’s age at onset was similar between the cases and controls regardless of the ASD subgroup. These findings emphasize the importance to examine the neurodevelopmental pathways in ASD, epilepsy and intellectual disability.

Risk of Psychiatric and Neurodevelopmental Disorders Among Siblings of Probands With Autism Spectrum Disorders

IMPORTANCE Previous research has focused on examining the familial clustering of schizophrenia, bipolar disorder, and autism spectrum disorders (ASD). Little is known about the clustering of other psychiatric and neurodevelopmental disorders among siblings of persons with ASD. OBJECTIVE To examine the risk for psychiatric and neurodevelopmental disorders among full siblings of probands with ASD. DESIGN, SETTING, AND PARTICIPANTS The Finnish Prenatal Study of Autism and Autism Spectrum Disorders used a population-based cohort that included children born from January 1, 1987, to December 31, 2005, who received a diagnosis of ASD by December 31, 2007. Each case was individually matched to 4 control participants by sex and date and place of birth. The siblings of the cases and controls were born from January 1, 1977, to December 31, 2005, and received a diagnosis from January 1, 1987, to December 31, 2009. This nested case-control study included 3578 cases with ASD with 6022 full siblings and 11 775 controls with 22 127 siblings from Finnish national registers. Data were analyzed from March 6, 2014, to February 12, 2016. MAIN OUTCOMES AND MEASURES The adjusted risk ratio (RR) for psychiatric and neurodevelopmental disorders among siblings of probands with ASD vs siblings of matched controls. Additional analyses were conducted separately for ASD subgroups, including childhood autism, Asperger syndrome, and pervasive developmental disorders not otherwise specified. Analyses were further stratified by sex and intellectual disability among the probands. RESULTS Among the 3578 cases with ASD (2841 boys [79.4%]) and 11 775 controls (9345 boys [79.4%]), 1319 cases (36.9%) and 2052 controls (17.4%) had at least 1 sibling diagnosed with any psychiatric or neurodevelopmental disorder (adjusted RR, 2.5; 95% CI, 2.3-2.6). The largest associations were observed for childhood-onset disorders (1061 cases [29.7%] vs 1362 controls [11.6%]; adjusted RR, 3.0; 95% CI, 2.8-3.3), including ASD (374 cases [10.5%] vs 125 controls [1.1%]; adjusted RR, 11.8; 95% CI, 9.4-14.7), tic disorders (28 cases [0.8%] vs 24 controls [0.2%]; adjusted RR, 4.3; 95% CI, 2.3-8.2), attention-deficit/hyperactivity disorder (189 cases [5.3%] vs 180 controls [1.5%]; adjusted RR, 3.7; 95% CI, 2.9-4.7), learning and coordination disorders (563 cases [15.7%] vs 697 controls [5.9%]; adjusted RR, 3.2; 95% CI, 2.8-3.6), intellectual disability (104 cases [2.9%] vs 137 controls [1.2%]; adjusted RR, 3.1; 95% CI, 2.3-4.2), conduct and oppositional disorders (180 cases [5.0%] vs 221 controls [1.9%]; adjusted RR, 2.8; 95% CI, 2.2-3.5), and emotional disorders with onset specific to childhood (126 cases [3.5%] vs 157 controls [1.3%]; adjusted RR, 2.6; 95% CI, 1.9-3.4). Autism spectrum disorders were also associated with schizophrenia spectrum disorders, affective disorders, anxiety disorders, and other neurotic and personality disorders among siblings. CONCLUSIONS AND RELEVANCE Psychiatric and neurodevelopmental disorders cluster among siblings of probands with ASD. For etiologic research, these findings provide further evidence that several psychiatric and neurodevelopmental disorders have common risk factors.

The International Collaboration for Autism Registry Epidemiology (iCARE): Multinational Registry-Based Investigations of Autism Risk Factors and Trends

The International Collaboration for Autism Registry Epidemiology (iCARE) is the first multinational research consortium (Australia, Denmark, Finland, Israel, Norway, Sweden, USA) to promote research in autism geographical and temporal heterogeneity, phenotype, family and life course patterns, and etiology. iCARE devised solutions to challenges in multinational collaboration concerning data access security, confidentiality and management. Data are obtained by integrating existing national or state-wide, population-based, individual-level data systems and undergo rigorous harmonization and quality control processes. Analyses are performed using database federation via a computational infrastructure with a secure, web-based, interface. iCARE provides a unique, unprecedented resource in autism research that will significantly enhance the ability to detect environmental and genetic contributions to the causes and life course of autism.

ViPAR: a software platform for the Virtual Pooling and Analysis of Research Data

Abstract Background: Research studies exploring the determinants of disease require sufficient statistical power to detect meaningful effects. Sample size is often increased through centralized pooling of disparately located datasets, though ethical, privacy and data ownership issues can often hamper this process. Methods that facilitate the sharing of research data that are sympathetic with these issues and which allow flexible and detailed statistical analyses are therefore in critical need. We have created a software platform for the Virtual Pooling and Analysis of Research data (ViPAR), which employs free and open source methods to provide researchers with a web-based platform to analyse datasets housed in disparate locations. Methods: Database federation permits controlled access to remotely located datasets from a central location. The Secure Shell protocol allows data to be securely exchanged between devices over an insecure network. ViPAR combines these free technologies into a solution that facilitates ‘virtual pooling’ where data can be temporarily pooled into computer memory and made available for analysis without the need for permanent central storage. Results: Within the ViPAR infrastructure, remote sites manage their own harmonized research dataset in a database hosted at their site, while a central server hosts the data federation component and a secure analysis portal. When an analysis is initiated, requested data are retrieved from each remote site and virtually pooled at the central site. The data are then analysed by statistical software and, on completion, results of the analysis are returned to the user and the virtually pooled data are removed from memory. Conclusions: ViPAR is a secure, flexible and powerful analysis platform built on open source technology that is currently in use by large international consortia, and is made publicly available at [ http://bioinformatics.childhealthresearch.org.au/software/vipar/ ].

Parental age and the risk of bipolar disorders.

Studies on the association between parental age and bipolar disorder (BPD) are scarce and with inconsistent findings. The aim of this study was to examine the association of parental age and age difference between parents with risk of BPD in offspring.

Finnish Prenatal Study of Bipolar Disorders (FIPS-B): Overview, design and description of the sample

Abstract Background: Bipolar disorders (BPD) are chronic mental illnesses, the development of which involves genetic factors and environmental influences. Aims: The aim of this paper is to provide an overall description of the Finnish Prenatal Study of Bipolar Disorders (FIPS-B), including the study design, national registers and linkage of the registers. Methods: FIPS-B is a population-based prenatal epidemiological study of BPD with a nested case–control study design using several national registers. The registers used are: the Finnish Medical Birth Register (FMBR), the Finnish Hospital Discharge Register (FHDR), the Population Central Register and the Finnish Maternity Cohort (FMC), which are linked using the unique personal identity code (PIC). FIPS-B includes all children born from January 1, 1983 to December 31, 1998 and diagnosed with BPD in Finland by December 31, 2008. Results: The total number of cases included in the FIPS-B is 1887. The age at first diagnosis ranged from 4 to 25 years. Half (50.4%) of the cases utilized only outpatient services, 12.7% only inpatient services and the rest (36.9%) utilized both services. Offspring of mothers with the lowest educational level had an increased odds of BPD (OR = 1.46, 95% CI 1.13–1.88). The cumulative incidence of BPD in the population aged 25 years or younger was 11.6/10,000 in 2008. Conclusions:  FIPS-B has all the strengths of a register-based prenatal epidemiological study, along with the availability of maternal biomarkers, enabling it to examine several prenatal, perinatal and familial risk factors for BPD.

Prenatal smoking exposure and neuropsychiatric comorbidity of ADHD: a finnish nationwide population-based cohort study

BackgroundPrenatal smoking exposure has been associated with attention-deficit/hyperactivity disorder (ADHD). ADHD is commonly associated with a wide spectrum of psychiatric comorbidity. The association between smoking and neuropsychiatric comorbidity of ADHD has remained understudied. The aim of this study is to examine the association between prenatal exposure to maternal smoking and offspring ADHD, and test whether the smoking-ADHD associations are stronger when ADHD is accompanied by other lifetime neuropsychiatric comorbidities.MethodsThe study is based on a nested case-control design and includes all Finnish singletons born between 1991 and 2005 and diagnosed with ADHD by 2011 (n = 10,132), matched with four controls (n = 38,811) on date of birth, sex and residence in Finland.ResultsThe risk for ADHD with or without comorbidity was significantly increased among offspring exposed to maternal smoking on adjusting for potential confounders (OR = 1.75, CI 95 % = 1.65–1.86). Compared to the only ADHD cases, subjects with comorbid conduct disorder or oppositional defiant disorder had a significantly stronger association with smoking exposure (OR = 1.80, CI 95 % = 1.55–2.11).ConclusionsPrenatal smoking represents an important risk factor for the ADHD comorbid with CD/ODD. Further research on the association between prenatal smoking exposure and neuropsychiatric comorbidity of ADHD is needed considering the increased risk among these subjects of an overall poor health outcome as compared to only ADHD. In particular, studies utilizing biomarkers or including subjects with neuropsychiatric conditions with and without comorbid ADHD are needed.