Interactions of perinatal depression versus anxiety and infants' early temperament trajectories

This study examines the interplay between maternal depression/anxiety and infant temperament's developmental trajectory in 1687 Swedish-speaking mother-infant dyads from Uppsala County (2009-2019), Sweden. The sample includes a high proportion of university-educated individuals and a low share of foreign-born participants. Maternal depressive and anxiety symptoms were assessed using the Edinburgh Postnatal Depression Scale during gestational weeks 17 and 32 and postpartum at week 6. Multinomial regression explored associations between maternal variables and infant temperament trajectories at 6 weeks, 12 months, and 18 months. Prenatal anxiety is associated with the high-rising infant difficult temperament trajectory, while prenatal depression/anhedonia is associated with the stable-medium trajectory, attenuated postpartum. Associations between infant temperament and maternal mood depended on timing (pre/postpartum) and symptom type (depression/anhedonia vs. anxiety).

Identification of moderate effect size genes in autism spectrum disorder through a novel gene pairing approach

Autism Spectrum Disorder (ASD) arises from complex genetic and environmental factors, with inherited genetic variation playing a substantial role. This study introduces a novel approach to uncover moderate effect size (MES) genes in ASD, which individually do not meet the ASD liability threshold but collectively contribute when paired with specific other MES genes. Analyzing 10,795 families from the SPARK dataset, we identified 97 MES genes forming 50 significant gene pairs, demonstrating a substantial association with ASD when considered in tandem, but not individually. Our method leverages familial inheritance patterns and statistical analyses, refined by comparisons against control cohorts, to elucidate these gene pairs' contribution to ASD liability. Furthermore, expression profile analyses of these genes in brain tissues underscore their relevance to ASD pathology. This study underscores the complexity of ASD's genetic landscape, suggesting that gene combinations, beyond high impact single-gene mutations, significantly contribute to the disorder's etiology and heterogeneity. Our findings pave the way for new avenues in understanding ASD's genetic underpinnings and developing targeted therapeutic strategies.

Genome-wide association study identifies 30 obsessive-compulsive disorder associated loci

Obsessive-compulsive disorder (OCD) affects ~1% of the population and exhibits a high SNP-heritability, yet previous genome-wide association studies (GWAS) have provided limited information on the genetic etiology and underlying biological mechanisms of the disorder. We conducted a GWAS meta-analysis combining 53,660 OCD cases and 2,044,417 controls from 28 European-ancestry cohorts revealing 30 independent genome-wide significant SNPs and a SNP-based heritability of 6.7%. Separate GWAS for clinical, biobank, comorbid, and self-report sub-groups found no evidence of sample ascertainment impacting our results. Functional and positional QTL gene-based approaches identified 249 significant candidate risk genes for OCD, of which 25 were identified as putatively causal, highlighting WDR6, DALRD3, CTNND1 and genes in the MHC region. Tissue and single-cell enrichment analyses highlighted hippocampal and cortical excitatory neurons, along with D1- and D2-type dopamine receptor-containing medium spiny neurons, as playing a role in OCD risk. OCD displayed significant genetic correlations with 65 out of 112 examined phenotypes. Notably, it showed positive genetic correlations with all included psychiatric phenotypes, in particular anxiety, depression, anorexia nervosa, and Tourette syndrome, and negative correlations with a subset of the included autoimmune disorders, educational attainment, and body mass index.. This study marks a significant step toward unraveling its genetic landscape and advances understanding of OCD genetics, providing a foundation for future interventions to address this debilitating disorder.

Familial risk of postpartum psychosis

Objective

Postpartum psychosis, a mood disorder triggered by childbirth, is one of the most severe psychiatric conditions, with high risks of suicide and infanticide if untreated. While it is evident that genetic factors play a crucial role in disorder risk, the exact extent of their importance is yet to be determined.

Methods

This cohort study consisted of 1,648,759 women from the Swedish nationwide registers, of whom 2,514 (0.15%) experienced postpartum psychosis within three months of their first-ever childbirth. We estimated the relative recurrence risk of postpartum psychosis for female full siblings and cousins as a measure of familial, genetic, and environmental risk.

Results

Relative recurrence risk of postpartum psychosis in full siblings was 10.69 (95% CI=6.60-16.26) when adjusted for year of and age at childbirth. Although cousins showed an elevated relative recurrence risk, these results did not reach statistical significance (1.78, 95% CI=0.70-3.62). Despite the higher familial risk of postpartum psychosis among full siblings, the absolute risk for women with an affected sibling is relatively low, estimated at 1.55% within the entire population.

Conclusions

The observed increased risk of postpartum psychosis in full siblings suggests both genetic and shared environmental influences. However, the lack of significant results in cousins hampers a definitive distinction between these factors. Furthermore, despite increased relative recurrence risk in siblings, their overall likelihood of developing postpartum psychosis remains low. Our study underscores the need for further research to better understand the intricate interplay of genetics and environment in the development of postpartum psychosis.

Direct additive genetics and maternal effect contribute to the risk of Tourette disorder

BACKGROUND

Risk for Tourette disorder, and chronic motor or vocal tic disorders (referenced here inclusively as CTD), arise from a combination of genetic and environmental factors. While multiple studies have demonstrated the importance of direct additive genetic variation for CTD risk, little is known about the role of cross-generational transmission of genetic risk, such as maternal effect, which is not transmitted via the inherited parental genomes. Here, we partition sources of variation on CTD risk into direct additive genetic effect (narrow-sense heritability) and maternal effect.

METHODS

The study population consists of 2 522 677 individuals from the Swedish Medical Birth Register, who were born in Sweden between 1 January 1973 and 31 December 2000, and followed for a diagnosis of CTD through 31 December, 2013. We used generalised linear mixed models to partition the liability of CTD into: direct additive genetic effect, genetic maternal effect and environmental maternal effect.

RESULTS

We identified 6227 (0.2%) individuals in the birth cohort with a CTD diagnosis. A study of half-siblings showed that maternal half-siblings had twice higher risk of developing a CTD compared with paternal ones. We estimated 60.7% direct additive genetic effect (95% credible interval, 58.5% to 62.4%), 4.8% genetic maternal effect (95% credible interval, 4.4% to 5.1%) and 0.5% environmental maternal effect (95% credible interval, 0.2% to 7%).

CONCLUSIONS

Our results demonstrate genetic maternal effect contributes to the risk of CTD. Failure to account for maternal effect results in an incomplete understanding of the genetic risk architecture of CTD, as the risk for CTD is impacted by maternal effect which is above and beyond the risk from transmitted genetic effect.

Association Between Mental Health and Reproductive System Disorders in Women: A Systematic Review and Meta-analysis

Importance

Reproductive system and mental health disorders are commonly comorbid in women. Although the causes of this overlap remain elusive, evidence suggests potential shared environmental and genetic factors associated with risk.

Objective

To investigate the comorbidity between psychiatric and reproductive system disorders, both as broad diagnostic categories and among specific pairs of diagnoses.

Data Source

PubMed.

Study Selection

Observational studies published between January 1980 and December 2019 assessing prevalence of psychiatric disorders in women with reproductive system disorders and prevalence of reproductive system disorders in women with psychiatric disorders were included. The study did not include psychiatric and reproductive disorders triggered by life events (eg, trauma, infection, surgery) to address potential confounding.

Data Extraction and Synthesis

A search yielded 1197 records, of which 50 met the inclusion criteria for the qualitative and 31 for the quantitative synthesis in our study. A random-effects model was used for data synthesis and Egger test and I2 to assess study bias and heterogeneity. Data were analyzed from January to December 2022. This study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guideline.

Main Outcomes and Measures

Psychiatric and reproductive system disorders.

Results

A total of 1197 records were identified, of which 50 met the inclusion criteria for qualitative and 31 for quantitative synthesis. Diagnosis of a reproductive system disorder was associated with a 2- to 3-fold increased odds of having a psychiatric disorder (lower bound odds ratio [OR], 2.00; 95% CI, 1.41-2.83; upper bound OR; 2.88; 95% CI, 2.21-3.76). The analysis focused on specific diagnoses described in the literature and found that polycystic ovary syndrome was associated with increased odds of depression (population-based studies OR, 1.71; 95% CI, 1.19-2.45; clinical studies OR, 2.58; 95% CI, 1.57-4.23) and anxiety (population-based studies OR, 1.69; 95% CI, 1.36-2.10; clinical studies OR, 2.85; 95% CI, 1.98-4.09). Chronic pelvic pain was also associated with both depression (OR, 3.91; 95% CI, 1.81-8.46) and anxiety (OR, 2.33; 95% CI, 1.33-4.08). Few studies investigated risk of other reproductive system disorders in women with psychiatric disorders, or reverse associations (risk of reproductive system disorder among women with a psychiatric diagnosis).

Conclusions and Relevance

In this systematic review and meta-analysis, a high rate of reported co-occurrence between psychiatric and reproductive disorders overall was observed. However, data for many disorder pairs were limited. The available literature focused overwhelmingly on affective disorders in polycystic ovary syndrome, overlooking a substantial portion of disease overlap. As such, the associations between the majority of mental health outcomes and conditions of the female reproductive system are largely unknown.

Comorbidities in autism spectrum disorder and their etiologies

Individuals with autism spectrum disorder (ASD), in addition to the core features of the disease, experience a higher burden of co-occurring medical conditions. This study sought to describe the frequency and distribution of comorbidit conditions in individuals with ASD, and systematically evaluate the possibility that pre- and postnatal exposures (e.g., preterm birth, hypoxia at birth, traumatic brain injury, and fetal alcohol syndrome) associated with ASD may also be linked with distinct comorbidities. We used the SPARK study database, launched by the Simons Foundation Autism Research Initiative (SFARI). Comorbidities considered in the study included neurological, cognitive, psychiatric, and physical conditions. The study sample consisted of 42,569 individuals with ASD and their 11,389 non-ASD siblings (full and half siblings). Majority (74%) of individuals with ASD had at least one comorbidity, and had a greater average number of comorbidities than their non-ASD siblings. Preterm birth and hypoxia at birth were the most common peri-natal exposures in the sample. In logistic regression models adjusted for covariates, these exposures were associated with several distinct comorbidities in ASD cases, including attention and behavior problems, psychiatric and neurological disorders, and growth conditions. A similar pattern of association was also observed in non-ASD siblings. Our findings underscore that individuals with ASD experience a greater burden of comorbidities, which could be partly attributable to the higher rates of perinatal exposures compared to their non-ASD siblings. Study findings, if replicated in other samples, can inform the etiology of comorbidity in ASD.

Phenotypic Impact of Rare Potentially Damaging Copy Number Variation in Obsessive-Compulsive Disorder and Chronic Tic Disorders

BACKGROUND

Recent studies report an important-and previously underestimated-role of rare variation in risk of obsessive-compulsive disorder (OCD) and chronic tic disorders (CTD). Using data from a large epidemiological study, we evaluate the distribution of potentially damaging copy number variation (pdCNV) in OCD and CTD, examining associations between pdCNV and the phenotypes of probands, including a consideration of early- vs. late-diagnoses.

METHOD

The Obsessive-Compulsive Inventory-Revised (OCI-R) questionnaire was used to ascertain psychometric profiles of OCD probands. CNV were identified genome-wide using chromosomal microarray data.

RESULTS

For 993 OCD cases, 86 (9%) were identified as pdCNV carriers. The most frequent pdCNV found was at the 16p13.11 region. There was no significant association between pdCNV and the OCI-R total score. However, pdCNV was associated with Obsessing and Checking subscores. There was no significant difference in pdCNV frequency between early- vs. late-diagnosed OCD probands. Of the 217 CTD cases, 18 (8%) were identified as pdCNV carriers. CTD probands with pdCNV were significantly more likely to have co-occurring autism spectrum disorder (ASD).

CONCLUSIONS

pdCNV represents part of the risk architecture for OCD and CTD. If replicated, our findings suggest pdCNV impact some OCD symptoms. Genes within the 16p13.11 region are potential OCD risk genes.

Psychometric properties of the Swedish translation of the Obsessive-Compulsive Inventory-Revised and the population characteristics of the symptom dimensions of OCD

PURPOSE

EGOS is an epidemiological obsessive-compulsive disorder (OCD) cohort in Sweden. Individuals contributed DNA for genotyping and sequencing and completed a Swedish translation of the Obsessive-Compulsive Inventory-Revised (OCI-R), a self-report questionnaire for assessing the severity of OCD. This study aimed first to evaluate the psychometric properties of the Swedish translation of the OCI-R and then shed light on the frequency, severity, and symptom dimensions of OCD comorbid with other psychiatric disorders.

METHODS

OCI-R data were available for 1010 individuals diagnosed with OCD, and 124 individuals diagnosed with chronic tic disorders without OCD used as a comparison group. We first performed a confirmatory factor analysis to confirm the six-factor structure of OCI-R. Then, we estimated Cronbach's α coefficient and the generalizability coefficient to evaluate the internal consistency of the OCI-R. We linked the data from the Swedish national registries to access and analyze psychiatric comorbidities of OCD.

RESULTS

The Swedish translation of OCI-R demonstrated internal consistency and clear agreement with the OCI-R six-factor model. The mean total OCI-R score for females was significantly higher than for males. The most comorbid psychiatric condition to OCD were anxiety disorders (13.6%) and major depression (12%).

CONCLUSION

The Swedish translation of OCI-R was a valid and reliable measure for assessing the severity of OCD. We observed that individuals with OCD frequently had additional comorbid psychiatric disorders and that the severity of OCD was significantly higher in individuals with at least one additional psychiatric comorbidity as compared to individuals with no psychiatric comorbidity.

Rare coding variation provides insight into the genetic architecture and phenotypic context of autism

Some individuals with autism spectrum disorder (ASD) carry functional mutations rarely observed in the general population. We explored the genes disrupted by these variants from joint analysis of protein-truncating variants (PTVs), missense variants and copy number variants (CNVs) in a cohort of 63,237 individuals. We discovered 72 genes associated with ASD at false discovery rate (FDR) ≤ 0.001 (185 at FDR ≤ 0.05). De novo PTVs, damaging missense variants and CNVs represented 57.5%, 21.1% and 8.44% of association evidence, while CNVs conferred greatest relative risk. Meta-analysis with cohorts ascertained for developmental delay (DD) (n = 91,605) yielded 373 genes associated with ASD/DD at FDR ≤ 0.001 (664 at FDR ≤ 0.05), some of which differed in relative frequency of mutation between ASD and DD cohorts. The DD-associated genes were enriched in transcriptomes of progenitor and immature neuronal cells, whereas genes showing stronger evidence in ASD were more enriched in maturing neurons and overlapped with schizophrenia-associated genes, emphasizing that these neuropsychiatric disorders may share common pathways to risk.

The Genetic Architecture of Obsessive-Compulsive Disorder: Contribution of Liability to OCD From Alleles Across the Frequency Spectrum

OBJECTIVE

Obsessive-compulsive disorder (OCD) is known to be substantially heritable; however, the contribution of genetic variation across the allele frequency spectrum to this heritability remains uncertain. The authors used two new homogeneous cohorts to estimate the heritability of OCD from inherited genetic variation and contrasted the results with those of previous studies.

METHODS

The sample consisted of 2,090 Swedish-born individuals diagnosed with OCD and 4,567 control subjects, all genotyped for common genetic variants, specifically >400,000 single-nucleotide polymorphisms (SNPs) with minor allele frequency (MAF) ≥0.01. Using genotypes of these SNPs to estimate distant familial relationships among individuals, the authors estimated the heritability of OCD, both overall and partitioned according to MAF bins.

RESULTS

Narrow-sense heritability of OCD was estimated at 29% (SE=4%). The estimate was robust, varying only modestly under different models. Contrary to an earlier study, however, SNPs with MAF between 0.01 and 0.05 accounted for 10% of heritability, and estimated heritability per MAF bin roughly followed expectations based on a simple model for SNP-based heritability.

CONCLUSIONS

These results indicate that common inherited risk variation (MAF ≥0.01) accounts for most of the heritable variation in OCD. SNPs with low MAF contribute meaningfully to the heritability of OCD, and the results are consistent with expectation under the "infinitesimal model" (also referred to as the "polygenic model"), where risk is influenced by a large number of loci across the genome and across MAF bins.

Clinical Characterization of Copy Number Variants Associated With Neurodevelopmental Disorders in a Large-scale Multiancestry Biobank

IMPORTANCE

Past studies identified rare copy number variants (CNVs) as risk factors for neurodevelopmental disorders (NDDs), including autism spectrum disorder and schizophrenia. However, the clinical characterization of NDD CNVs is understudied in population cohorts unselected for neuropsychiatric disorders and in cohorts of diverse ancestry.

OBJECTIVE

To identify individuals harboring NDD CNVs in a multiancestry biobank and to query their enrichment for select neuropsychiatric disorders as well as association with multiple medical disorders.

DESIGN, SETTINGS, AND PARTICIPANTS

In a series of phenotypic enrichment and association analyses, NDD CNVs were clinically characterized among 24 877 participants in the BioMe biobank, an electronic health record-linked biobank derived from the Mount Sinai Health System, New York, New York. Participants were recruited into the biobank since September 2007 across diverse ancestry and medical and neuropsychiatric specialties. For the current analyses, electronic health record data were analyzed from May 2004 through May 2019.

MAIN OUTCOMES AND MEASURES

NDD CNVs were identified using a consensus of 2 CNV calling algorithms, based on whole-exome sequencing and genotype array data, followed by novel in-silico clinical assessments.

RESULTS

Of 24 877 participants, 14 586 (58.7%) were female; self-reported ancestry categories included 5965 (24.0%) who were of African ancestry, 7892 (31.7%) who were of European ancestry, and 8536 (34.3%) who were of Hispanic ancestry; and the mean (SD) age was 50.5 (17.3) years. Among 24 877 individuals, the prevalence of 64 NDD CNVs was 2.5% (n = 627), with prevalence varying by locus, corroborating the presence of some relatively highly prevalent NDD CNVs (eg, 15q11.2 deletion/duplication). An aggregate set of NDD CNVs were enriched for congenital disorders (odds ratio, 2.0; 95% CI, 1.1-3.5; P = .01) and major depressive disorder (odds ratio, 1.5; 95% CI, 1.1-2.0; P = .01). In a meta-analysis of medical diagnoses (n = 195 hierarchically clustered diagnostic codes), NDD CNVs were significantly associated with several medical outcomes, including essential hypertension (z score = 3.6; P = 2.8 × 10-4), kidney failure (z score = 3.3; P = 1.1 × 10-3), and obstructive sleep apnea (z score = 3.4; P = 8.1 × 10-4) and, in another analysis, morbid obesity (z score = 3.8; P = 1.3 × 10-4). Further, NDD CNVs were associated with increased body mass index in a multiancestry analysis (β = 0.19; 95% CI, 0.10-0.31; P = .003). For 36 common serum tests, there was no association with NDD CNVs.

CONCLUSIONS AND RELEVANCE

Clinical features of individuals harboring NDD CNVs were elucidated in a large-scale, multiancestry biobank, identifying enrichments for congenital disorders and major depressive disorder as well as associations with several medical outcomes, including hypertension, kidney failure, and obesity and obesity-related phenotypes, specifically obstructive sleep apnea and increased body mass index. The association between NDD CNVs and obesity outcomes indicate further potential pleiotropy of NDD CNVs beyond neurodevelopmental outcomes previously reported. Future clinical genetic investigations may lead to insights of at-risk individuals and therapeutic strategies targeting specific genetic variants. The importance of diverse inclusion within biobanks and considering the effect of rare genetic variants in a multiancestry context is evident.

Family history of breast cancer is associated with elevated risk of prostate cancer: evidence for shared genetic risks

INTRODUCTION

Although breast and prostate cancers arise in different organs and are more frequent in the opposite sex, multiple studies have reported an association between their family history. Analysis of single nucleotide polymorphism data, based on distant relatives, has revealed a small positive genetic correlation between these cancers explained by common variants. The estimate of genetic correlation based on close relatives reveals the extent to which shared genetic risks are explained by both common and rare variants. This estimate is unknown for breast and prostate cancer.

METHOD

We estimated the relative risks, heritability, and genetic correlation of breast cancer and prostate cancer, based on the Minnesota Breast and Prostate Cancer Study, a family study of 141 families ascertained for breast cancer.

RESULTS

Heritability of breast cancer was 0.34 (95% credible interval: 0.23-0.49) and 0.65 (95% credible interval: 0.36-0.97) for prostate cancer, and the genetic correlation was 0.23. In terms of odds ratios, these values correspond to a 1.3 times higher odds of breast cancer among probands, given that the brother has prostate cancer.

CONCLUSION

This study shows the inherent relation between prostate cancer and breast cancer; an incident of one in a family increases the risk of developing the other. The large difference between estimates of genetic correlation from distant and close relatives, if replicated, suggests that rare variants contribute to the shared genetic risk of breast and prostate cancer. However, the difference could steam from genotype-by-family effects shared between the two types of cancers.

Prevalence and phenotypic impact of rare potentially damaging variants in autism spectrum disorder

BACKGROUND

The Autism Sequencing Consortium identified 102 high-confidence autism spectrum disorder (ASD) genes, showing that individuals with ASD and with potentially damaging single nucleotide variation (pdSNV) in these genes had lower cognitive levels and delayed age at walking, when compared to ASD participants without pdSNV. Here, we made use of a Swedish sample of individuals with ASD (called PAGES, for Population-Based Autism Genetics & Environment Study) to evaluate the frequency of pdSNV and their impact on medical and psychiatric phenotypes, using an epidemiological frame and universal health reporting. We then combine findings with those for potentially damaging copy number variation (pdCNV).

METHODS

SNV and CNV calls were generated from whole-exome sequencing and chromosome microarray data, respectively. Birth and medical register data were used to collect phenotypes.

RESULTS

Of 808 individuals assessed by sequencing, 69 (9%) had pdSNV in the 102 ASC genes, and 144 (18%) had pdSNV in the 102 ASC genes or in a larger set of curated neurodevelopmental genes (from the Deciphering Developmental Disorders study, the gene2phenotype database, and the Radboud University gene lists). Three or more individuals had pdSNV in GRIN2B, POGZ, SATB1, DYNC1H1, SCN8A, or CREBBP. In comparison, out of the 996 individuals from whom CNV were called, 105 (11%) carried one or more pdCNV, including four or more individuals with CNV in the recurrent 15q11q13, 22q11.2, and 16p11.2 loci. Carriers of pdSNV were more likely to have intellectual disability (ID) and epilepsy, while carriers of pdCNV showed increased rates of congenital anomalies and scholastic skill disorders. Carriers of either pdSNV or pdCNV were more likely to have ID, scholastic skill disorders, and epilepsy.

LIMITATIONS

The cohort only included individuals with autistic disorder, the more severe form of ASD, and phenotypes are defined from medical registers. Not all genes studied are definitively ASD genes, and we did not have de novo information to aid in classification.

CONCLUSIONS

In this epidemiological sample, rare pdSNV were more common than pdCNV and the combined yield of potentially damaging variation was substantial at 27%. The results provide compelling rationale for the use of high-throughout sequencing as part of routine clinical workup for ASD and support the development of precision medicine in ASD.

How rare and common risk variation jointly affect liability for autism spectrum disorder

BACKGROUND

Genetic studies have implicated rare and common variations in liability for autism spectrum disorder (ASD). Of the discovered risk variants, those rare in the population invariably have large impact on liability, while common variants have small effects. Yet, collectively, common risk variants account for the majority of population-level variability. How these rare and common risk variants jointly affect liability for individuals requires further study.

METHODS

To explore how common and rare variants jointly affect liability, we assessed two cohorts of ASD families characterized for rare and common genetic variations (Simons Simplex Collection and Population-Based Autism Genetics and Environment Study). We analyzed data from 3011 affected subjects, as well as two cohorts of unaffected individuals characterized for common genetic variation: 3011 subjects matched for ancestry to ASD subjects and 11,950 subjects for estimating allele frequencies. We used genetic scores, which assessed the relative burden of common genetic variation affecting risk of ASD (henceforth "burden"), and determined how this burden was distributed among three subpopulations: ASD subjects who carry a potentially damaging variant implicated in risk of ASD ("PDV carriers"); ASD subjects who do not ("non-carriers"); and unaffected subjects who are assumed to be non-carriers.

RESULTS

Burden harbored by ASD subjects is stochastically greater than that harbored by control subjects. For PDV carriers, their average burden is intermediate between non-carrier ASD and control subjects. Both carrier and non-carrier ASD subjects have greater burden, on average, than control subjects. The effects of common and rare variants likely combine additively to determine individual-level liability.

LIMITATIONS

Only 305 ASD subjects were known PDV carriers. This relatively small subpopulation limits this study to characterizing general patterns of burden, as opposed to effects of specific PDVs or genes. Also, a small fraction of subjects that are categorized as non-carriers could be PDV carriers.

CONCLUSIONS

Liability arising from common and rare risk variations likely combines additively to determine risk of any individual diagnosed with ASD. On average, ASD subjects carry a substantial burden of common risk variation, even if they also carry a rare PDV affecting risk.

Genetics of obsessive-compulsive disorder

BACKGROUND

Obsessive-compulsive disorder (OCD) is a psychiatric disorder with multiple symptom dimensions (e.g. contamination, symmetry). OCD clusters in families and decades of twin studies clearly demonstrate an important role for genetics in the etiology of the disorder.

METHODS

In this review, we summarize the genetic epidemiology and molecular genetic studies of OCD and obsessive-compulsive symptoms.

RESULTS

OCD is a heritable, polygenic disorder with contributions from both common and rare variants, including de novo deleterious variations. Multiple studies have provided reliable support for a large additive genetic contribution to liability to OCD, with discrete OCD symptom dimensions having both shared and unique genetic risks. Genome-wide association studies have not produced significant results yet, likely because of small sample sizes, but larger meta-analyses are forthcoming. Both twin and genome-wide studies show that OCD shares genetic risk with its comorbid conditions (e.g. Tourette syndrome and anorexia nervosa).

CONCLUSIONS

Despite significant efforts to uncover the genetic basis of OCD, the mechanistic understanding of how genetic and environmental risk factors interact and converge at the molecular level to result in OCD's heterogeneous phenotype is still mostly unknown. Future investigations should increase ancestral genetic diversity, explore age and/or sex differences in genetic risk for OCD and expand the study of pharmacogenetics, gene expression, gene × environment interactions and epigenetic mechanisms for OCD.

Systematic review and meta-analysis identify significant relationships between clinical anxiety and lower urinary tract symptoms

BACKGROUND

Lower urinary tract symptoms (LUTS), such as voiding symptoms, overactive bladder, and interstitial cystitis, and anxiety disorders are often comorbid conditions in patients. However, the existing evidence regarding the rates and nature of the co-occurrence of these conditions has not been systematically evaluated. The aim of this study was to examine these relationships.

METHODS

We conducted a systematic review and meta-analysis to examine the relationship between LUTS and anxiety. We searched for articles published from January 1990 to July 2019 in PubMed, CENTRAL, PsycINFO, and Google Scholar. Outcomes were anxiety-related disorders and symptoms (clinically significant anxiety) and LUTS. We performed random-effects meta-analyses, inspected funnel plots, and applied the Egger's test to evaluate publication bias. We followed PRISMA guidelines and recorded our protocol on PROSPERO (ID = CRD42019118607).

RESULTS

We identified 814 articles, of which 94 fulfilled inclusion criteria, and 23 had sufficient data for meta-analysis. The odds ratio (OR) for clinically significant anxiety among individuals with LUTS was 2.87 (95% CI: 2.38,3.46, p < .001). The OR for LUTS among individuals with clinically significant anxiety was 2.87 (95% CI: 1.07,7.74, p < .001), although very few studies examined this relationship. A large value of I² index suggests high heterogeneity between studies.

CONCLUSION

The results demonstrate a significant association between clinically significant anxiety and LUTS in both females and males. There were limited studies on younger individuals and on individuals ascertained for clinically significant anxiety, which should motivate further study in these areas. Understanding the co-occurrence of these conditions will lead to better prevention and interventions to ameliorate the progression of the symptoms and improve the quality of life. A thorough assessment of anxiety may provide more optimal care for LUTS patients.

Cohort profile: Epidemiology and Genetics of Obsessive-compulsive disorder and chronic tic disorders in Sweden (EGOS)

PURPOSE

The EGOS study (Epidemiology and Genetics of Obsessive-compulsive disorder and chronic tic disorders in Sweden) is a large-scale, epidemiological, prospective cohort that is used to identify genetic and environmental risk factors in the etiology of obsessive-compulsive disorder (OCD) and chronic tic disorders (CTD).

METHODS

Individuals born between January 1954 and December 1998 with at least two diagnoses of OCD or CTD at different timepoints in the National Patient Register (NPR), and followed between January 1997 and December 2012, represent the EGOS source population (n = 20,374). The Swedish Multi-Generation Registry (MGR) are then used to define family relatedness for all cases and additional phenotypic and demographic data added to the resultant database. To create an epidemiologically valid subset of the source cohort that also includes biospecimens and additional phenotyping, we contact cases from within the source population. To date, 6832 invitations have been sent out and 1853 (27%) have elected to participate in the EGOS biospecimen collection.

RESULTS

To date, 1608 biological samples have been collected, of which 1249 are genotyped and 832 supplementary Obsessive-Compulsive Inventory-Revised (OCI-R) and/or Florida Obsessive-Compulsive Inventory (FOCI) have been completed by individuals with OCD and/or CTD, age 16-64 years. DNA samples are genotyped using Infinium Global Screening Array and will undergo whole-exome sequencing in the future. Detailed information is available for each individual through linkage to the Swedish national registers, e.g., identification of additional psychiatric diagnoses, medical diagnoses, birth-related variables, and relevant demographic and social data.

CONCLUSION

EGOS benefits from a genetically homogeneous sample with epidemiological ascertainment, minimizing the risk of confounding due to population stratification on ascertainment bias. In addition, this study is built upon clinical diagnoses of OCD and CTD in specialized psychiatric care, which reduces further biases and case misclassification.

Maternal Effects as Causes of Risk for Obsessive-Compulsive Disorder

BACKGROUND

While genetic variation has a known impact on the risk for obsessive-compulsive disorder (OCD), there is also evidence that there are maternal components to this risk. Here, we partitioned sources of variation, including direct genetic and maternal effects, on risk for OCD.

METHODS

The study population consisted of 822,843 individuals from the Swedish Medical Birth Register, born in Sweden between January 1, 1982, and December 31, 1990, and followed for a diagnosis of OCD through December 31, 2013. Diagnostic information about OCD was obtained using the Swedish National Patient Register.

RESULTS

A total of 7184 individuals in the birth cohort (0.87%) were diagnosed with OCD. After exploring various generalized linear mixed models to fit the diagnostic data, genetic maternal effects accounted for 7.6% (95% credible interval: 6.9%-8.3%) of the total variance in risk for OCD for the best model, and direct additive genetics accounted for 35% (95% credible interval: 32.3%-36.9%). These findings were robust under alternative models.

CONCLUSIONS

Our results establish genetic maternal effects as influencing risk for OCD in offspring. We also show that additive genetic effects in OCD are overestimated when maternal effects are not modeled.

Association of Genetic and Environmental Factors With Autism in a 5-Country Cohort

IMPORTANCE

The origins and development of autism spectrum disorder (ASD) remain unresolved. No individual-level study has provided estimates of additive genetic, maternal, and environmental effects in ASD across several countries.

OBJECTIVE

To estimate the additive genetic, maternal, and environmental effects in ASD.

DESIGN, SETTING, AND PARTICIPANTS

Population-based, multinational cohort study including full birth cohorts of children from Denmark, Finland, Sweden, Israel, and Western Australia born between January 1, 1998, and December 31, 2011, and followed up to age 16 years. Data were analyzed from September 23, 2016 through February 4, 2018.

MAIN OUTCOMES AND MEASURES

Across 5 countries, models were fitted to estimate variance components describing the total variance in risk for ASD occurrence owing to additive genetics, maternal, and shared and nonshared environmental effects.

RESULTS

The analytic sample included 2 001 631 individuals, of whom 1 027 546 (51.3%) were male. Among the entire sample, 22 156 were diagnosed with ASD. The median (95% CI) ASD heritability was 80.8% (73.2%-85.5%) for country-specific point estimates, ranging from 50.9% (25.1%-75.6%) (Finland) to 86.8% (69.8%-100.0%) (Israel). For the Nordic countries combined, heritability estimates ranged from 81.2% (73.9%-85.3%) to 82.7% (79.1%-86.0%). Maternal effect was estimated to range from 0.4% to 1.6%. Estimates of genetic, maternal, and environmental effects for autistic disorder were similar with ASD.

CONCLUSIONS AND RELEVANCE

Based on population data from 5 countries, the heritability of ASD was estimated to be approximately 80%, indicating that the variation in ASD occurrence in the population is mostly owing to inherited genetic influences, with no support for contribution from maternal effects. The results suggest possible modest differences in the sources of ASD risk between countries.

Heritable Variation, With Little or No Maternal Effect, Accounts for Recurrence Risk to Autism Spectrum Disorder in Sweden

BACKGROUND

Autism spectrum disorder (ASD) has both genetic and environmental origins, including potentially maternal effects. Maternal effects describe the association of one or more maternal phenotypes with liability to ASD in progeny that are independent of maternally transmitted risk alleles. While maternal effects could play an important role, consistent with association to maternal traits such as immune status, no study has estimated maternal, additive genetic, and environmental effects in ASD.

METHODS

Using a population-based sample consisting of all children born in Sweden from 1998 to 2007 and their relatives, we fitted statistical models to family data to estimate the variance in ASD liability originating from maternal, additive genetic, and shared environmental effects. We calculated sibling and cousin family recurrence risk ratio as a direct measure of familial, genetic, and environmental risk factors and repeated the calculations on diagnostic subgroups, specifically autistic disorder (AD) and spectrum disorder (SD), which included Asperger's syndrome and/or pervasive developmental disorder not otherwise specified.

RESULTS

The sample consisted of 776,212 children of whom 11,231 had a diagnosis of ASD: 4554 with AD, 6677 with SD. We found support for large additive genetic contribution to liability; heritability (95% confidence interval [CI]) was estimated to 84.8% (95% CI: 73.1-87.3) for ASD, 79.6% (95% CI: 61.2-85.1) for AD, and 76.4% (95% CI: 63.0-82.5) for SD.

CONCLUSIONS

There was modest, if any, contribution of maternal effects to liability for ASD, including subtypes AD and SD, and there was no support for shared environmental effects. These results show liability to ASD arises largely from additive genetic variation.

A Flexible Computational Framework Using R and Map-Reduce for Permutation Tests of Massive Genetic Analysis of Complex Traits

In quantitative trait locus (QTL) mapping significance of putative QTL is often determined using permutation testing. The computational needs to calculate the significance level are immense, 10⁴ up to 10⁸ or even more permutations can be needed. We have previously introduced the PruneDIRECT algorithm for multiple QTL scan with epistatic interactions. This algorithm has specific strengths for permutation testing. Here, we present a flexible, parallel computing framework for identifying multiple interacting QTL using the PruneDIRECT algorithm which uses the map-reduce model as implemented in Hadoop. The framework is implemented in R, a widely used software tool among geneticists. This enables users to rearrange algorithmic steps to adapt genetic models, search algorithms, and parallelization steps to their needs in a flexible way. Our work underlines the maturity of accessing distributed parallel computing for computationally demanding bioinformatics applications through building workflows within existing scientific environments. We investigate the PruneDIRECT algorithm, comparing its performance to exhaustive search and DIRECT algorithm using our framework on a public cloud resource. We find that PruneDIRECT is vastly superior for permutation testing, and perform 2 ×10⁵ permutations for a 2D QTL problem in 15 hours, using 100 cloud processes. We show that our framework scales out almost linearly for a 3D QTL search.

Fast and accurate detection of multiple quantitative trait Loci

We present a new computational scheme that enables efficient and reliable quantitative trait loci (QTL) scans for experimental populations. Using a standard brute-force exhaustive search effectively prohibits accurate QTL scans involving more than two loci to be performed in practice, at least if permutation testing is used to determine significance. Some more elaborate global optimization approaches, for example, DIRECT have been adopted earlier to QTL search problems. Dramatic speedups have been reported for high-dimensional scans. However, since a heuristic termination criterion must be used in these types of algorithms, the accuracy of the optimization process cannot be guaranteed. Indeed, earlier results show that a small bias in the significance thresholds is sometimes introduced. Our new optimization scheme, PruneDIRECT, is based on an analysis leading to a computable (Lipschitz) bound on the slope of a transformed objective function. The bound is derived for both infinite- and finite-size populations. Introducing a Lipschitz bound in DIRECT leads to an algorithm related to classical Lipschitz optimization. Regions in the search space can be permanently excluded (pruned) during the optimization process. Heuristic termination criteria can thus be avoided. Hence, PruneDIRECT has a well-defined error bound and can in practice be guaranteed to be equivalent to a corresponding exhaustive search. We present simulation results that show that for simultaneous mapping of three QTLS using permutation testing, PruneDIRECT is typically more than 50 times faster than exhaustive search. The speedup is higher for stronger QTL. This could be used to quickly detect strong candidate eQTL networks.

Sequential Markov coalescent algorithms for population models with demographic structure

We analyse sequential Markov coalescent algorithms for populations with demographic structure: for a bottleneck model, a population-divergence model, and for a two-island model with migration. The sequential Markov coalescent method is an approximation to the coalescent suggested by McVean and Cardin, and by Marjoram and Wall. Within this algorithm we compute, for two individuals randomly sampled from the population, the correlation between times to the most recent common ancestor and the linkage probability corresponding to two different loci with recombination rate R between them. These quantities characterise the linkage between the two loci in question. We find that the sequential Markov coalescent method approximates the coalescent well in general in models with demographic structure. An exception is the case where individuals are sampled from populations separated by reduced gene flow. In this situation, the correlations may be significantly underestimated. We explain why this is the case.