Evaluating and improving health equity and fairness of polygenic scores

Polygenic scores (PGSs) are quantitative metrics for predicting phenotypic values, such as human height or disease status. Some PGS methods require only summary statistics of a relevant genome-wide association study (GWAS) for their score. One such method is Lassosum, which inherits the model selection advantages of Lasso to select a meaningful subset of the GWAS single-nucleotide polymorphisms as predictors from their association statistics. However, even efficient scores like Lassosum, when derived from European-based GWASs, are poor predictors of phenotype for subjects of non-European ancestry; that is, they have limited portability to other ancestries. To increase the portability of Lassosum, when GWAS information and estimates of linkage disequilibrium are available for both ancestries, we propose Joint-Lassosum (JLS). In the simulation settings we explore, JLS provides more accurate PGSs compared to other methods, especially when measured in terms of fairness. In analyses of UK Biobank data, JLS was computationally more efficient but slightly less accurate than a Bayesian comparator, SDPRX. Like all PGS methods, JLS requires selection of predictors, which are determined by data-driven tuning parameters. We describe a new approach to selecting tuning parameters and note its relevance for model selection for any PGS. We also draw connections to the literature on algorithmic fairness and discuss how JLS can help mitigate fairness-related harms that might result from the use of PGSs in clinical settings. While no PGS method is likely to be universally portable, due to the diversity of human populations and unequal information content of GWASs for different ancestries, JLS is an effective approach for enhancing portability and reducing predictive bias.

Heritable Composite Phenotypes Defined by Combinations of Conduct Problem, Depression, and Temperament Features: Contributions to risk for Alcohol Problems

The genetic architectures underlying symptoms of conduct problems and depression have largely been examined separately and without incorporating temperament, despite evidence for their genetic overlap. We examined how symptoms and temperament dimensions were transmitted together in families to identify highly heritable composite phenotypes, and how these composite phenotypes predicted alcohol outcomes in young adulthood. Participants (N = 486) were drawn from the third generation of families oversampled for alcohol use disorder in the first generation. Conduct problems, depression, and temperament were reported at 11-19 years old and alcohol outcomes at 18-26 years old. Using principal components of heritability analysis, we found seven highly heritable composite phenotypes, five of which predicted alcohol outcomes: three characterized by co-occurring conduct problems and depression and two by conduct problems. Novel composite phenotypes that were characterized by both conduct problems and depression showed different types of symptoms, temperament features, and genetic underpinnings. Children manifesting differing composite phenotypes might benefit from distinct treatments based on their unique etiologies.

Genetic associations with psychosis and affective disturbance in Alzheimer's disease

INTRODUCTION

Individuals with Alzheimer's disease (AD) commonly experience neuropsychiatric symptoms of psychosis (AD+P) and/or affective disturbance (depression, anxiety, and/or irritability, AD+A). This study's goal was to identify the genetic architecture of AD+P and AD+A, as well as their genetically correlated phenotypes.

METHODS

Genome-wide association meta-analysis of 9988 AD participants from six source studies with participants characterized for AD+P AD+A, and a joint phenotype (AD+A+P).

RESULTS

AD+P and AD+A were genetically correlated. However, AD+P and AD+A diverged in their genetic correlations with psychiatric phenotypes in individuals without AD. AD+P was negatively genetically correlated with bipolar disorder and positively with depressive symptoms. AD+A was positively correlated with anxiety disorder and more strongly correlated than AD+P with depressive symptoms. AD+P and AD+A+P had significant estimated heritability, whereas AD+A did not. Examination of the loci most strongly associated with the three phenotypes revealed overlapping and unique associations.

DISCUSSION

AD+P, AD+A, and AD+A+P have both shared and divergent genetic associations pointing to the importance of incorporating genetic insights into future treatment development.

Highlights

It has long been known that psychotic and affective symptoms are often comorbid in individuals diagnosed with Alzheimer's disease. Here we examined for the first time the genetic architecture underlying this clinical observation, determining that psychotic and affective phenotypes in Alzheimer's disease are genetically correlated.Nevertheless, psychotic and affective phenotypes in Alzheimer's disease diverged in their genetic correlations with psychiatric phenotypes assessed in individuals without Alzheimer's disease. Psychosis in Alzheimer's disease was negatively genetically correlated with bipolar disorder and positively with depressive symptoms, whereas the affective phenotypes in Alzheimer's disease were positively correlated with anxiety disorder and more strongly correlated than psychosis with depressive symptoms.Psychosis in Alzheimer's disease, and the joint psychotic and affective phenotype, had significant estimated heritability, whereas the affective in AD did not.Examination of the loci most strongly associated with the psychotic, affective, or joint phenotypes revealed overlapping and unique associations.

Comparison of gene expression in living and postmortem human brain

Molecular mechanisms of neuropsychiatric disorders are challenging to study in human brain. For decades, the preferred model has been to study postmortem human brain samples despite the limitations they entail. A recent study generated RNA sequencing data from biopsies of prefrontal cortex from living patients with Parkinson's Disease and compared gene expression to postmortem tissue samples, from which they found vast differences between the two. This led the authors to question the utility of postmortem human brain studies. Through re-analysis of the same data, we unexpectedly found that the living brain tissue samples were of much lower quality than the postmortem samples across multiple standard metrics. We also performed simulations that illustrate the effects of ignoring RNA degradation in differential gene expression analyses, showing the effects can be substantial and of similar magnitude to what the authors find. For these reasons, we believe the authors' conclusions are unjustified. To the contrary, while opportunities to study gene expression in the living brain are welcome, evidence that this eclipses the value of postmortem analyses is not apparent.

Evaluating and Improving Health Equity and Fairness of Polygenic Scores

Polygenic scores (PGS) are quantitative metrics for predicting phenotypic values, such as human height or disease status. Some PGS methods require only summary statistics of a relevant genome-wide association study (GWAS) for their score. One such method is Lassosum, which inherits the model selection advantages of Lasso to select a meaningful subset of the GWAS single nucleotide polymorphisms as predictors from their association statistics. However, even efficient scores like Lassosum, when derived from European-based GWAS, are poor predictors of phenotype for subjects of non-European ancestry; that is, they have limited portability to other ancestries. To increase the portability of Lassosum, when GWAS information and estimates of linkage disequilibrium are available for both ancestries, we propose Joint-Lassosum. In the simulation settings we explore, Joint-Lassosum provides more accurate PGS compared with other methods, especially when measured in terms of fairness. Like all PGS methods, Joint-Lassosum requires selection of predictors, which are determined by data-driven tuning parameters. We describe a new approach to selecting tuning parameters and note its relevance for model selection for any PGS. We also draw connections to the literature on algorithmic fairness and discuss how Joint-Lassosum can help mitigate fairness-related harms that might result from the use of PGS scores in clinical settings. While no PGS method is likely to be universally portable, due to the diversity of human populations and unequal information content of GWAS for different ancestries, Joint-Lassosum is an effective approach for enhancing portability and reducing predictive bias.

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.

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.

Schizophrenia-associated differential DNA methylation in brain is distributed across the genome and annotated to MAD1L1, a locus at which DNA methylation and transcription phenotypes share genetic variation with schizophrenia risk

DNA methylation (DNAm), the addition of a methyl group to a cytosine in DNA, plays an important role in the regulation of gene expression. Single-nucleotide polymorphisms (SNPs) associated with schizophrenia (SZ) by genome-wide association studies (GWAS) often influence local DNAm levels. Thus, DNAm alterations, acting through effects on gene expression, represent one potential mechanism by which SZ-associated SNPs confer risk. In this study, we investigated genome-wide DNAm in postmortem superior temporal gyrus from 44 subjects with SZ and 44 non-psychiatric comparison subjects using Illumina Infinium MethylationEPIC BeadChip microarrays, and extracted cell-type-specific methylation signals by applying tensor composition analysis. We identified SZ-associated differential methylation at 242 sites, and 44 regions containing two or more sites (FDR cutoff of q = 0.1) and determined a subset of these were cell-type specific. We found mitotic arrest deficient 1-like 1 (MAD1L1), a gene within an established GWAS risk locus, harbored robust SZ-associated differential methylation. We investigated the potential role of MAD1L1 DNAm in conferring SZ risk by assessing for colocalization among quantitative trait loci for methylation and gene transcripts (mQTLs and tQTLs) in brain tissue and GWAS signal at the locus using multiple-trait-colocalization analysis. We found that mQTLs and tQTLs colocalized with the GWAS signal (posterior probability >0.8). Our findings suggest that alterations in MAD1L1 methylation and transcription may mediate risk for SZ at the MAD1L1-containing locus. Future studies to identify how SZ-associated differential methylation affects MAD1L1 biological function are indicated.

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.

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.

Genome-wide association identifies the first risk loci for psychosis in Alzheimer disease

Psychotic symptoms, defined as the occurrence of delusions or hallucinations, are frequent in Alzheimer disease (AD with psychosis, AD + P). AD + P affects ~50% of individuals with AD, identifies a subgroup with poor outcomes, and is associated with a greater degree of cognitive impairment and depressive symptoms, compared to subjects without psychosis (AD - P). Although the estimated heritability of AD + P is 61%, genetic sources of risk are unknown. We report a genome-wide meta-analysis of 12,317 AD subjects, 5445 AD + P. Results showed common genetic variation accounted for a significant portion of heritability. Two loci, one in ENPP6 (rs9994623, O.R. (95%CI) 1.16 (1.10, 1.22), p = 1.26 × 10^-8) and one spanning the 3'-UTR of an alternatively spliced transcript of SUMF1 (rs201109606, O.R. 0.65 (0.56-0.76), p = 3.24 × 10^-8), had genome-wide significant associations with AD + P. Gene-based analysis identified a significant association with APOE, due to the APOE risk haplotype ε4. AD + P demonstrated negative genetic correlations with cognitive and educational attainment and positive genetic correlation with depressive symptoms. We previously observed a negative genetic correlation with schizophrenia; instead, we now found a stronger negative correlation with the related phenotype of bipolar disorder. Analysis of polygenic risk scores supported this genetic correlation and documented a positive genetic correlation with risk variation for AD, beyond the effect of ε4. We also document a small set of SNPs likely to affect risk for AD + P and AD or schizophrenia. These findings provide the first unbiased identification of the association of psychosis in AD with common genetic variation and provide insights into its genetic architecture.

Whole-Genome and RNA Sequencing Reveal Variation and Transcriptomic Coordination in the Developing Human Prefrontal Cortex

Gene expression levels vary across developmental stage, cell type, and region in the brain. Genomic variants also contribute to the variation in expression, and some neuropsychiatric disorder loci may exert their effects through this mechanism. To investigate these relationships, we present BrainVar, a unique resource of paired whole-genome and bulk tissue RNA sequencing from the dorsolateral prefrontal cortex of 176 individuals across prenatal and postnatal development. Here we identify common variants that alter gene expression (expression quantitative trait loci [eQTLs]) constantly across development or predominantly during prenatal or postnatal stages. Both "constant" and "temporal-predominant" eQTLs are enriched for loci associated with neuropsychiatric traits and disorders and colocalize with specific variants. Expression levels of more than 12,000 genes rise or fall in a concerted late-fetal transition, with the transitional genes enriched for cell-type-specific genes and neuropsychiatric risk loci, underscoring the importance of cataloging developmental trajectories in understanding cortical physiology and pathology.

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.

Functional connectome fingerprinting accuracy in youths and adults is similar when examined on the same day and 1.5-years apart

Pioneering studies have shown that individual correlation measures from resting‐state functional magnetic resonance imaging studies can identify another scan from that same individual. This method is known as “connectotyping” or functional connectome “fingerprinting.” We analyzed a unique dataset of 12–30 years old (N = 140) individuals who had two distinct resting state scans on the same day and again 12–18 months later to assess the sensitivity and specificity of fingerprinting accuracy across different time scales (same day, ~1.5 years apart) and developmental periods (youths, adults). Sensitivity and specificity to identify one's own scan was high (average AUC = 0.94), although it was significantly higher in the same day (average AUC = 0.97) than 1.5‐years later (average AUC = 0.91). Accuracy in youths (average AUC = 0.93) was not significantly different from adults (average AUC = 0.96). Multiple statistical methods revealed select connections from the Frontoparietal, Default, and Dorsal Attention networks enhanced the ability to identify an individual. Identification of these features generalized across datasets and improved fingerprinting accuracy in a longitudinal replication data set (N = 208). These results provide a framework for understanding the sensitivity and specificity of fingerprinting accuracy in adolescents and adults at multiple time scales. Importantly, distinct features of one's “fingerprint” contribute to one's uniqueness, suggesting that cognitive and default networks play a primary role in the individualization of one's connectome.

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.

Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism

We present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n = 35,584 total samples, 11,986 with ASD). Using an enhanced analytical framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate of 0.1 or less. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained to have severe neurodevelopmental delay, whereas 53 show higher frequencies in individuals ascertained to have ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In cells from the human cortex, expression of risk genes is enriched in excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatory-inhibitory imbalance underlying ASD.

Age dependent association of inbreeding with risk for schizophrenia in Egypt

BACKGROUND

Self-reported consanguinity is associated with risk for schizophrenia (SZ) in several inbred populations, but estimates using DNA-based coefficients of inbreeding are unavailable. Further, it is not known whether recessively inherited risk mutations can be identified through homozygosity by descent (HBD) mapping.

METHODS

We studied self-reported and DNA-based estimates of inbreeding among Egyptian patients with SZ (n = 421, DSM IV criteria) and adult controls without psychosis (n = 301), who were evaluated using semi-structured diagnostic interview schedules and genotyped using the Illumina Infinium PsychArray. Following quality control checks, coefficients of inbreeding (F) and regions of homozygosity (ROH) were estimated using PLINK software for HBD analysis. Exome sequencing was conducted in selected cases.

RESULTS

Inbreeding was associated with schizophrenia based on self-reported consanguinity (χ2 = 4.506, 1 df, p = 0.034) and DNA-based estimates for inbreeding (F); the latter with a significant F × age interaction (β = 32.34, p = 0.0047). The association was most notable among patients older than age 40 years. Eleven ROH were over-represented in cases on chromosomes 1, 3, 6, 11, and 14; all but one region is novel for schizophrenia risk. Exome sequencing identified six recessively-acting genes in ROH with loss-of-function variants; one of which causes primary hereditary microcephaly.

CONCLUSIONS

We propose consanguinity as an age-dependent risk factor for SZ in Egypt. HBD mapping is feasible for SZ in adequately powered samples.

Identification of common genetic risk variants for autism spectrum disorder

Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD.

Genome-wide de novo risk score implicates promoter variation in autism spectrum disorder

Whole-genome sequencing (WGS) has facilitated the first genome-wide evaluations of the contribution of de novo noncoding mutations to complex disorders. Using WGS, we identified 255,106 de novo mutations among sample genomes from members of 1902 quartet families in which one child, but not a sibling or their parents, was affected by autism spectrum disorder (ASD). In contrast to coding mutations, no noncoding functional annotation category, analyzed in isolation, was significantly associated with ASD. Casting noncoding variation in the context of a de novo risk score across multiple annotation categories, however, did demonstrate association with mutations localized to promoter regions. We found that the strongest driver of this promoter signal emanates from evolutionarily conserved transcription factor binding sites distal to the transcription start site. These data suggest that de novo mutations in promoter regions, characterized by evolutionary and functional signatures, contribute to ASD.

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.

Genetic risk for schizophrenia and psychosis in Alzheimer disease

Psychotic symptoms, defined as the occurrence of delusions or hallucinations, are frequent in Alzheimer disease (AD), affecting ~40 to 60% of individuals with AD (AD with psychosis (AD+P)). In comparison with AD subjects without psychosis, AD+P subjects have more rapid cognitive decline and poor outcomes. Prior studies have estimated the heritability of psychosis in AD at 61%, but the underlying genetic sources of this risk are not known. We evaluated a Discovery Cohort of 2876 AD subjects with (N=1761) or without psychosis (N=1115). All subjects were genotyped using a custom genotyping array designed to evaluate single-nucleotide polymorphisms (SNPs) with evidence of genetic association with AD+P and include SNPs affecting or putatively affecting risk for schizophrenia and AD. Results were replicated in an independent cohort of 2194 AD subjects with (N=734) or without psychosis (N=1460). We found that AD+P is associated with polygenic risk for a set of novel loci and inversely associated with polygenic risk for schizophrenia. Among the biologic pathways identified by the associations of schizophrenia SNPs with AD+P are endosomal trafficking, autophagy and calcium channel signaling. To the best of our knowledge, these findings provide the first clear demonstration that AD+P is associated with common genetic variation. In addition, they provide an unbiased link between polygenic risk for schizophrenia and a lower risk of psychosis in AD. This provides an opportunity to leverage progress made in identifying the biologic effects of schizophrenia alleles to identify novel mechanisms protecting against more rapid cognitive decline and psychosis risk in AD.

Joint evaluation of serum C-Reactive Protein levels and polygenic risk scores as risk factors for schizophrenia

Several studies have indicated infectious and immune-related abnormalities in schizophrenia (Scz), including elevated serum C-reactive protein (CRP) - a well-known proxy for infections/immune abnormalities. A portion of the genetic risk for Scz can be estimated using the polygenic risk score (PGRS). It is not known whether there is an interaction in the risks traceable to CRP and PGRS. Patients with Scz and individuals without psychosis were evaluated systematically using DSM IV criteria (N=794, N=446, respectively). To estimate risk for Scz attributable to CRP and PGRS, serum from these participants was assayed for CRP levels using enzyme linked immunosorbent assays. PGRS was estimated from common DNA polymorphisms associated with Scz from genome wide association studies. CRP level and PGRS were not significantly correlated. Using a generalized linear logistic model, case/control status was evaluated in relation to the following predictors: CRP, PGRS, and demographic variables. CRP and PGRS were individually associated with case status; CRP: odds ratio (OR) 1.27, 95% confidence intervals (95% CI) 1.12, 1.43; p = 0.0001; PGRS: OR 1.66, 95% CI 1.47, 1.89; p = 1.28 ×10^-15. There were no significant interactions between PGRS and CRP for predicting Scz versus control status.

A Pleiotropic Missense Variant in SLC39A8 Is Associated With Crohn's Disease and Human Gut Microbiome Composition

BACKGROUND & AIMS

Genome-wide association studies have identified 200 inflammatory bowel disease (IBD) loci, but the genetic architecture of Crohn's disease (CD) and ulcerative colitis remain incompletely defined. Here, we aimed to identify novel associations between IBD and functional genetic variants using the Illumina ExomeChip (San Diego, CA).

METHODS

Genotyping was performed in 10,523 IBD cases and 5726 non-IBD controls. There were 91,713 functional single-nucleotide polymorphism loci in coding regions analyzed. A novel identified association was replicated further in 2 independent cohorts. We further examined the association of the identified single-nucleotide polymorphism with microbiota from 338 mucosal lavage samples in the Mucosal Luminal Interface cohort measured using 16S sequencing.

RESULTS

We identified an association between CD and a missense variant encoding alanine or threonine at position 391 in the zinc transporter solute carrier family 39, member 8 protein (SLC39A8 alanine 391 threonine, rs13107325) and replicated the association with CD in 2 replication cohorts (combined meta-analysis P = 5.55 × 10(-13)). This variant has been associated previously with distinct phenotypes including obesity, lipid levels, blood pressure, and schizophrenia. We subsequently determined that the CD risk allele was associated with altered colonic mucosal microbiome composition in both healthy controls (P = .009) and CD cases (P = .0009). Moreover, microbes depleted in healthy carriers strongly overlap with those reduced in CD patients (P = 9.24 × 10(-16)) and overweight individuals (P = 6.73 × 10(-16)).

CONCLUSIONS

Our results suggest that an SLC39A8-dependent shift in the gut microbiome could explain its pleiotropic effects on multiple complex diseases including CD.

Analysis of Shared Haplotypes amongst Palauans Maps Loci for Psychotic Disorders to 4q28 and 5q23-q31

To localize genetic variation affecting risk for psychotic disorders in the population of Palau, we genotyped DNA samples from 203 Palauan individuals diagnosed with psychotic disorders, broadly defined, and 125 control subjects using a genome-wide single nucleotide polymorphism array. Palau has unique features advantageous for this study: due to its population history, Palauans are substantially interrelated; affected individuals often, but not always, cluster in families; and we have essentially complete ascertainment of affected individuals. To localize risk variants to genomic regions, we evaluated long-shared haplotypes, ≥10 Mb, identifying clusters of affected individuals who share such haplotypes. This extensive sharing, typically identical by descent, was significantly greater in cases than population controls, even after controlling for relatedness. Several regions of the genome exhibited substantial excess of shared haplotypes for affected individuals, including 3p21, 3p12, 4q28, and 5q23-q31. Two of these regions, 4q28 and 5q23-q31, showed significant linkage by traditional LOD score analysis and could harbor variants of more sizeable risk for psychosis or a multiplicity of risk variants. The pattern of haplotype sharing in 4q28 highlights <i>PCDH10</i>, encoding a cadherin-related neuronal receptor, as possibly involved in risk.

A genome-wide association study of autism using the Simons Simplex Collection: Does reducing phenotypic heterogeneity in autism increase genetic homogeneity?

BACKGROUND

Phenotypic heterogeneity in autism has long been conjectured to be a major hindrance to the discovery of genetic risk factors, leading to numerous attempts to stratify children based on phenotype to increase power of discovery studies. This approach, however, is based on the hypothesis that phenotypic heterogeneity closely maps to genetic variation, which has not been tested. Our study examines the impact of subphenotyping of a well-characterized autism spectrum disorder (ASD) sample on genetic homogeneity and the ability to discover common genetic variants conferring liability to ASD.

METHODS

Genome-wide genotypic data of 2576 families from the Simons Simplex Collection were analyzed in the overall sample and phenotypic subgroups defined on the basis of diagnosis, IQ, and symptom profiles. We conducted a family-based association study, as well as estimating heritability and evaluating allele scores for each phenotypic subgroup.

RESULTS

Association analyses revealed no genome-wide significant association signal. Subphenotyping did not increase power substantially. Moreover, allele scores built from the most associated single nucleotide polymorphisms, based on the odds ratio in the full sample, predicted case status in subsets of the sample equally well and heritability estimates were very similar for all subgroups.

CONCLUSIONS

In genome-wide association analysis of the Simons Simplex Collection sample, reducing phenotypic heterogeneity had at most a modest impact on genetic homogeneity. Our results are based on a relatively small sample, one with greater homogeneity than the entire population; if they apply more broadly, they imply that analysis of subphenotypes is not a productive path forward for discovering genetic risk variants in ASD.

The autism-associated chromatin modifier CHD8 regulates other autism risk genes during human neurodevelopment

Recent studies implicate chromatin modifiers in autism spectrum disorder (ASD) through the identification of recurrent de novo loss of function mutations in affected individuals. ASD risk genes are co-expressed in human midfetal cortex, suggesting that ASD risk genes converge in specific regulatory networks during neurodevelopment. To elucidate such networks, we identify genes targeted by CHD8, a chromodomain helicase strongly associated with ASD, in human midfetal brain, human neural stem cells (hNSCs) and embryonic mouse cortex. CHD8 targets are strongly enriched for other ASD risk genes in both human and mouse neurodevelopment, and converge in ASD-associated co-expression networks in human midfetal cortex. CHD8 knockdown in hNSCs results in dysregulation of ASD risk genes directly targeted by CHD8. Integration of CHD8-binding data into ASD risk models improves detection of risk genes. These results suggest loss of CHD8 contributes to ASD by perturbing an ancient gene regulatory network during human brain development.

Joint analysis of psychiatric disorders increases accuracy of risk prediction for schizophrenia, bipolar disorder, and major depressive disorder

Genetic risk prediction has several potential applications in medical research and clinical practice and could be used, for example, to stratify a heterogeneous population of patients by their predicted genetic risk. However, for polygenic traits, such as psychiatric disorders, the accuracy of risk prediction is low. Here we use a multivariate linear mixed model and apply multi-trait genomic best linear unbiased prediction for genetic risk prediction. This method exploits correlations between disorders and simultaneously evaluates individual risk for each disorder. We show that the multivariate approach significantly increases the prediction accuracy for schizophrenia, bipolar disorder, and major depressive disorder in the discovery as well as in independent validation datasets. By grouping SNPs based on genome annotation and fitting multiple random effects, we show that the prediction accuracy could be further improved. The gain in prediction accuracy of the multivariate approach is equivalent to an increase in sample size of 34% for schizophrenia, 68% for bipolar disorder, and 76% for major depressive disorders using single trait models. Because our approach can be readily applied to any number of GWAS datasets of correlated traits, it is a flexible and powerful tool to maximize prediction accuracy. With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low polygenic risk.

Characterizing runs of homozygosity and their impact on risk for psychosis in a population isolate

An increased abundance of runs of homozygosity (ROH) has been associated with risk for various diseases, including schizophrenia. Here we investigate the characteristics of ROH in Palau, an Oceanic population, evaluating whether these characteristics are related to risk for psychotic disorders and the nature of this association. To accomplish these aims we evaluate a sample of 203 cases with schizophrenia and related psychotic disorders-representing almost complete ascertainment of affected individuals in the population-and contrast their ROH to that of 125 subjects chosen to function as controls. While Palauan diagnosed with psychotic disorders tend to have slightly more ROH regions than controls, the distinguishing features are that they have longer ROH regions, greater total length of ROH, and their ROH tends to co-occur more often at the same locus. The nature of the sample allows us to investigate whether rare, highly penetrant recessive variants generate such case-control differences in ROH. Neither rare, highly penetrant recessive variants nor individual common variants of large effect account for a substantial proportion of risk for psychosis in Palau. These results suggest a more nuanced model for risk is required to explain patterns of ROH for this population.

Transcriptional consequences of 16p11.2 deletion and duplication in mouse cortex and multiplex autism families

Reciprocal copy-number variation (CNV) of a 593 kb region of 16p11.2 is a common genetic cause of autism spectrum disorder (ASD), yet it is not completely penetrant and can manifest in a wide array of phenotypes. To explore its molecular consequences, we performed RNA sequencing of cerebral cortex from mouse models with CNV of the syntenic 7qF3 region and lymphoblast lines from 34 members of 7 multiplex ASD-affected families harboring the 16p11.2 CNV. Expression of all genes in the CNV region correlated well with their DNA copy number, with no evidence of dosage compensation. We observed effects on gene expression outside the CNV region, including apparent positional effects in cis and in trans at genomic segments with evidence of physical interaction in Hi-C chromosome conformation data. One of the most significant positional effects was telomeric to the 16p11.2 CNV and includes the previously described "distal" 16p11.2 microdeletion. Overall, 16p11.2 CNV was associated with altered expression of genes and networks that converge on multiple hypotheses of ASD pathogenesis, including synaptic function (e.g., NRXN1, NRXN3), chromatin modification (e.g., CHD8, EHMT1, MECP2), transcriptional regulation (e.g., TCF4, SATB2), and intellectual disability (e.g., FMR1, CEP290). However, there were differences between tissues and species, with the strongest effects being consistently within the CNV region itself. Our analyses suggest that through a combination of indirect regulatory effects and direct effects on nuclear architecture, alteration of 16p11.2 genes disrupts expression networks that involve other genes and pathways known to contribute to ASD, suggesting an overlap in mechanisms of pathogenesis.

Modest impact on risk for autism spectrum disorder of rare copy number variants at 15q11.2, specifically breakpoints 1 to 2

The proximal region of chromosome 15 is one of the genomic hotspots for copy number variants (CNVs). Among the rearrangements observed in this region, CNVs from the interval between the common breakpoints 1 and 2 (BP1 and BP2) have been reported cosegregating with autism spectrum disorder (ASD). Although evidence supporting an association between BP1-BP2 CNVs and autism accumulates, the magnitude of the effect of BP1-BP2 CNVs remains elusive, posing a great challenge to recurrence-risk counseling. To gain further insight into their pathogenicity for ASD, we estimated the penetrance of the BP1-BP2 CNVs for ASD as well as their effects on ASD-related phenotypes in a well-characterized ASD sample (n = 2525 families). Transmission disequilibrium test revealed significant preferential transmission only for the duplicated chromosome in probands (20T:9NT). The penetrance of the BP1-BP2 CNVs for ASD was low, conferring additional risks of 0.3% (deletion) and 0.8% (duplication). Stepwise regression analyses suggest a greater effect of the CNVs on ASD-related phenotype in males and when maternally inherited. Taken together, the results are consistent with BP1-BP2 CNVs as risk factors for autism. However, their effect is modest, more akin to that seen for common variants. To be consistent with the current American College of Medical Genetics guidelines for interpretation of postnatal CNV, the BP1-BP2 deletion and duplication CNVs would probably best be classified as variants of uncertain significance (VOUS): they appear to have an impact on risk, but one so modest that these CNVs do not merit pathogenic status.

Convergence of genes and cellular pathways dysregulated in autism spectrum disorders

Rare copy-number variation (CNV) is an important source of risk for autism spectrum disorders (ASDs). We analyzed 2,446 ASD-affected families and confirmed an excess of genic deletions and duplications in affected versus control groups (1.41-fold, p = 1.0 × 10⁻⁵) and an increase in affected subjects carrying exonic pathogenic CNVs overlapping known loci associated with dominant or X-linked ASD and intellectual disability (odds ratio = 12.62, p = 2.7 × 10⁻¹⁵, ∼3% of ASD subjects). Pathogenic CNVs, often showing variable expressivity, included rare de novo and inherited events at 36 loci, implicating ASD-associated genes (CHD2, HDAC4, and GDI1) previously linked to other neurodevelopmental disorders, as well as other genes such as SETD5, MIR137, and HDAC9. Consistent with hypothesized gender-specific modulators, females with ASD were more likely to have highly penetrant CNVs (p = 0.017) and were also overrepresented among subjects with fragile X syndrome protein targets (p = 0.02). Genes affected by de novo CNVs and/or loss-of-function single-nucleotide variants converged on networks related to neuronal signaling and development, synapse function, and chromatin regulation.

Rare deleterious mutations of the gene EFR3A in autism spectrum disorders

BACKGROUND

Whole-exome sequencing studies in autism spectrum disorder (ASD) have identified de novo mutations in novel candidate genes, including the synaptic gene Eighty-five Requiring 3A (EFR3A). EFR3A is a critical component of a protein complex required for the synthesis of the phosphoinositide PtdIns4P, which has a variety of functions at the neural synapse. We hypothesized that deleterious mutations in EFR3A would be significantly associated with ASD.

METHODS

We conducted a large case/control association study by deep resequencing and analysis of whole-exome data for coding and splice site variants in EFR3A. We determined the potential impact of these variants on protein structure and function by a variety of conservation measures and analysis of the Saccharomyces cerevisiae Efr3 crystal structure. We also analyzed the expression pattern of EFR3A in human brain tissue.

RESULTS

Rare nonsynonymous mutations in EFR3A were more common among cases (16 / 2,196 = 0.73%) than matched controls (12 / 3,389 = 0.35%) and were statistically more common at conserved nucleotides based on an experiment-wide significance threshold (P = 0.0077, permutation test). Crystal structure analysis revealed that mutations likely to be deleterious were also statistically more common in cases than controls (P = 0.017, Fisher exact test). Furthermore, EFR3A is expressed in cortical neurons, including pyramidal neurons, during human fetal brain development in a pattern consistent with ASD-related genes, and it is strongly co-expressed (P < 2.2 × 10(-16), Wilcoxon test) with a module of genes significantly associated with ASD.

CONCLUSIONS

Rare deleterious mutations in EFR3A were found to be associated with ASD using an experiment-wide significance threshold. Synaptic phosphoinositide metabolism has been strongly implicated in syndromic forms of ASD. These data for EFR3A strengthen the evidence for the involvement of this pathway in idiopathic autism.

DAWN: a framework to identify autism genes and subnetworks using gene expression and genetics

BACKGROUND

De novo loss-of-function (dnLoF) mutations are found twofold more often in autism spectrum disorder (ASD) probands than their unaffected siblings. Multiple independent dnLoF mutations in the same gene implicate the gene in risk and hence provide a systematic, albeit arduous, path forward for ASD genetics. It is likely that using additional non-genetic data will enhance the ability to identify ASD genes.

METHODS

To accelerate the search for ASD genes, we developed a novel algorithm, DAWN, to model two kinds of data: rare variations from exome sequencing and gene co-expression in the mid-fetal prefrontal and motor-somatosensory neocortex, a critical nexus for risk. The algorithm casts the ensemble data as a hidden Markov random field in which the graph structure is determined by gene co-expression and it combines these interrelationships with node-specific observations, namely gene identity, expression, genetic data and the estimated effect on risk.

RESULTS

Using currently available genetic data and a specific developmental time period for gene co-expression, DAWN identified 127 genes that plausibly affect risk, and a set of likely ASD subnetworks. Validation experiments making use of published targeted resequencing results demonstrate its efficacy in reliably predicting ASD genes. DAWN also successfully predicts known ASD genes, not included in the genetic data used to create the model.

CONCLUSIONS

Validation studies demonstrate that DAWN is effective in predicting ASD genes and subnetworks by leveraging genetic and gene expression data. The findings reported here implicate neurite extension and neuronal arborization as risks for ASD. Using DAWN on emerging ASD sequence data and gene expression data from other brain regions and tissues would likely identify novel ASD genes. DAWN can also be used for other complex disorders to identify genes and subnetworks in those disorders.

Coexpression networks implicate human midfetal deep cortical projection neurons in the pathogenesis of autism

Autism spectrum disorder (ASD) is a complex developmental syndrome of unknown etiology. Recent studies employing exome- and genome-wide sequencing have identified nine high-confidence ASD (hcASD) genes. Working from the hypothesis that ASD-associated mutations in these biologically pleiotropic genes will disrupt intersecting developmental processes to contribute to a common phenotype, we have attempted to identify time periods, brain regions, and cell types in which these genes converge. We have constructed coexpression networks based on the hcASD "seed" genes, leveraging a rich expression data set encompassing multiple human brain regions across human development and into adulthood. By assessing enrichment of an independent set of probable ASD (pASD) genes, derived from the same sequencing studies, we demonstrate a key point of convergence in midfetal layer 5/6 cortical projection neurons. This approach informs when, where, and in what cell types mutations in these specific genes may be productively studied to clarify ASD pathophysiology.

Adjusting head circumference for covariates in autism: clinical correlates of a highly heritable continuous trait

BACKGROUND

Brain development follows a different trajectory in children with autism spectrum disorders (ASD) than in typically developing children. A proxy for neurodevelopment could be head circumference (HC), but studies assessing HC and its clinical correlates in ASD have been inconsistent. This study investigates HC and clinical correlates in the Simons Simplex Collection cohort.

METHODS

We used a mixed linear model to estimate effects of covariates and the deviation from the expected HC given parental HC (genetic deviation). After excluding individuals with incomplete data, 7225 individuals in 1891 families remained for analysis. We examined the relationship between HC/genetic deviation of HC and clinical parameters.

RESULTS

Gender, age, height, weight, genetic ancestry, and ASD status were significant predictors of HC (estimate of the ASD effect = .2 cm). HC was approximately normally distributed in probands and unaffected relatives, with only a few outliers. Genetic deviation of HC was also normally distributed, consistent with a random sampling of parental genes. Whereas larger HC than expected was associated with ASD symptom severity and regression, IQ decreased with the absolute value of the genetic deviation of HC.

CONCLUSIONS

Measured against expected values derived from covariates of ASD subjects, statistical outliers for HC were uncommon. HC is a strongly heritable trait, and population norms for HC would be far more accurate if covariates including genetic ancestry, height, and age were taken into account. The association of diminishing IQ with absolute deviation from predicted HC values suggests HC could reflect subtle underlying brain development and warrants further investigation.

REFINING GENETICALLY INFERRED RELATIONSHIPS USING TREELET COVARIANCE SMOOTHING

Recent technological advances coupled with large sample sets have uncovered many factors underlying the genetic basis of traits and the predisposition to complex disease, but much is left to discover. A common thread to most genetic investigations is familial relationships. Close relatives can be identified from family records, and more distant relatives can be inferred from large panels of genetic markers. Unfortunately these empirical estimates can be noisy, especially regarding distant relatives. We propose a new method for denoising genetically-inferred relationship matrices by exploiting the underlying structure due to hierarchical groupings of correlated individuals. The approach, which we call Treelet Covariance Smoothing, employs a multiscale decomposition of covariance matrices to improve estimates of pairwise relationships. On both simulated and real data, we show that smoothing leads to better estimates of the relatedness amongst distantly related individuals. We illustrate our method with a large genome-wide association study and estimate the "heritability" of body mass index quite accurately. Traditionally heritability, defined as the fraction of the total trait variance attributable to additive genetic effects, is estimated from samples of closely related individuals using random effects models. We show that by using smoothed relationship matrices we can estimate heritability using population-based samples. Finally, while our methods have been developed for refining genetic relationship matrices and improving estimates of heritability, they have much broader potential application in statistics. Most notably, for error-in-variables random effects models and settings that require regularization of matrices with block or hierarchical structure.

Persistent infection with neurotropic herpes viruses and cognitive impairment

BACKGROUND

Herpes virus infections can cause cognitive impairment during and after acute encephalitis. Although chronic, latent/persistent infection is considered to be relatively benign, some studies have documented cognitive impairment in exposed persons that is untraceable to encephalitis. These studies were conducted among schizophrenia (SZ) patients or older community dwellers, among whom it is difficult to control for the effects of co-morbid illness and medications. To determine whether the associations can be generalized to other groups, we examined a large sample of younger control individuals, SZ patients and their non-psychotic relatives (n=1852). Method Using multivariate models, cognitive performance was evaluated in relation to exposures to herpes simplex virus type 1 (HSV-1), herpes simplex virus type 2 (HSV-2) and cytomegalovirus (CMV), controlling for familial and diagnostic status and sociodemographic variables, including occupation and educational status. Composite cognitive measures were derived from nine cognitive domains using principal components of heritability (PCH). Exposure was indexed by antibodies to viral antigens.

RESULTS

PCH1, the most heritable component of cognitive performance, declines with exposure to CMV or HSV-1 regardless of case/relative/control group status (p = 1.09 × 10-5 and 0.01 respectively), with stronger association with exposure to multiple herpes viruses (β = -0.25, p = 7.28 × 10-10). There were no significant interactions between exposure and group status.

CONCLUSIONS

Latent/persistent herpes virus infections can be associated with cognitive impairments regardless of other health status.

Principal components of heritability from neurocognitive domains differ between families with schizophrenia and control subjects

OBJECTIVE

Various measures of neurocognitive function show mean differences among individuals with schizophrenia (SZ), their relatives, and population controls. We use eigenvector transformations that maximize heritability of multiple neurocognitive measures, namely principal components of heritability (PCH), and evaluate how they distribute in SZ families and controls.

METHODS

African-Americans with SZ or schizoaffective disorder (SZA) (n = 514), their relatives (n = 1092), and adult controls (n = 300) completed diagnostic interviews and computerized neurocognitive tests. PCH were estimated from 9 neurocognitive domains. Three PCH, PCH1-PCH3, were modeled to determine if status (SZ, relative, and control), other psychiatric covariates, and education were significant predictors of mean values. A small-scale linkage analysis was also conducted in a subset of the sample.

RESULTS

PCH1, PCH2, and PCH3 account for 72% of the genetic variance. PCH1 represents 8 of 9 neurocognitive domains, is most highly correlated with spatial processing and emotion recognition, and has unadjusted heritability of 68%. The means for PCH1 differ significantly among SZ, their relatives, and controls. PCH2, orthogonal to PCH1, is most closely correlated with working memory and has an unadjusted heritability of 45%. Mean PCH2 is different only between SZ families and controls. PCH3 apparently represents a heritable component of neurocognition similar across the 3 diagnostic groups. No significant linkage evidence to PCH1-PCH3 or individual neurocognitive measures was discovered.

CONCLUSIONS

PCH1 is highly heritable and genetically correlated with SZ. It should prove useful in future genetic analyses. Mean PCH2 differentiates SZ families and controls but not SZ and unaffected family members.

Genome-wide association study of Alzheimer's disease with psychotic symptoms

Psychotic symptoms occur in ~40% of subjects with Alzheimer's disease (AD) and are associated with more rapid cognitive decline and increased functional deficits. They show heritability up to 61% and have been proposed as a marker for a disease subtype suitable for gene mapping efforts. We undertook a combined analysis of three genome-wide association studies (GWASs) to identify loci that (1) increase susceptibility to an AD and subsequent psychotic symptoms; or (2) modify risk of psychotic symptoms in the presence of neurodegeneration caused by AD. In all, 1299 AD cases with psychosis (AD+P), 735 AD cases without psychosis (AD-P) and 5659 controls were drawn from Genetic and Environmental Risk in AD Consortium 1 (GERAD1), the National Institute on Aging Late-Onset Alzheimer's Disease (NIA-LOAD) family study and the University of Pittsburgh Alzheimer Disease Research Center (ADRC) GWASs. Unobserved genotypes were imputed to provide data on >1.8 million single-nucleotide polymorphisms (SNPs). Analyses in each data set were completed comparing (1) AD+P to AD-P cases, and (2) AD+P cases with controls (GERAD1, ADRC only). Aside from the apolipoprotein E (APOE) locus, the strongest evidence for association was observed in an intergenic region on chromosome 4 (rs753129; 'AD+PvAD-P' P=2.85 × 10(-7); 'AD+PvControls' P=1.11 × 10(-4)). SNPs upstream of SLC2A9 (rs6834555, P=3.0 × 10(-7)) and within VSNL1 (rs4038131, P=5.9 × 10(-7)) showed strongest evidence for association with AD+P when compared with controls. These findings warrant further investigation in larger, appropriately powered samples in which the presence of psychotic symptoms in AD has been well characterized.

Evaluation of HLA polymorphisms in relation to schizophrenia risk and infectious exposure

BACKGROUND

Genome-wide association studies (GWAS) implicate single nucleotide polymorphisms (SNPs) on chromosome 6p21.3-22.1, the human leukocyte antigen (HLA) region, as common risk factors for schizophrenia (SZ). Other studies implicate viral and protozoan exposure. Our study tests chromosome 6p SNPs for effects on SZ risk with and without exposure.

METHOD

GWAS-significant SNPs and ancestry-informative marker SNPs were analyzed among African American patients with SZ (n = 604) and controls (n = 404). Exposure to herpes simplex virus, type 1 (HSV-1), cytomegalovirus (CMV), and Toxoplasma gondii (TOX) was assayed using specific antibody assays.

RESULTS

Five SNPs were nominally associated with SZ, adjusted for population admixture (P < .05, uncorrected for multiple comparisons). These SNPs were next analyzed in relation to infectious exposure. Multivariate analysis indicated significant association between rs3130297 genotype and HSV-1 exposure; the associated allele was different from the SZ risk allele.

CONCLUSIONS

We propose a model for the genesis of SZ incorporating genomic variation in the HLA region and neurotropic viral exposure for testing in additional, independent African American samples.

Individual common variants exert weak effects on the risk for autism spectrum disorders

While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm< 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest.

Common genetic variants, acting additively, are a major source of risk for autism

Background

Autism spectrum disorders (ASD) are early onset neurodevelopmental syndromes typified by impairments in reciprocal social interaction and communication, accompanied by restricted and repetitive behaviors. While rare and especially de novo genetic variation are known to affect liability, whether common genetic polymorphism plays a substantial role is an open question and the relative contribution of genes and environment is contentious. It is probable that the relative contributions of rare and common variation, as well as environment, differs between ASD families having only a single affected individual (simplex) versus multiplex families who have two or more affected individuals.

Methods

By using quantitative genetics techniques and the contrast of ASD subjects to controls, we estimate what portion of liability can be explained by additive genetic effects, known as narrow-sense heritability. We evaluate relatives of ASD subjects using the same methods to evaluate the assumptions of the additive model and partition families by simplex/multiplex status to determine how heritability changes with status.

Results

By analyzing common variation throughout the genome, we show that common genetic polymorphism exerts substantial additive genetic effects on ASD liability and that simplex/multiplex family status has an impact on the identified composition of that risk. As a fraction of the total variation in liability, the estimated narrow-sense heritability exceeds 60% for ASD individuals from multiplex families and is approximately 40% for simplex families. By analyzing parents, unaffected siblings and alleles not transmitted from parents to their affected children, we conclude that the data for simplex ASD families follow the expectation for additive models closely. The data from multiplex families deviate somewhat from an additive model, possibly due to parental assortative mating.

Conclusions

Our results, when viewed in the context of results from genome-wide association studies, demonstrate that a myriad of common variants of very small effect impacts ASD liability.

Genome-wide transcriptome profiling reveals the functional impact of rare de novo and recurrent CNVs in autism spectrum disorders

Copy-number variants (CNVs) are a major contributor to the pathophysiology of autism spectrum disorders (ASDs), but the functional impact of CNVs remains largely unexplored. Because brain tissue is not available from most samples, we interrogated gene expression in lymphoblasts from 244 families with discordant siblings in the Simons Simplex Collection in order to identify potentially pathogenic variation. Our results reveal that the overall frequency of significantly misexpressed genes (which we refer to here as outliers) identified in probands and unaffected siblings does not differ. However, in probands, but not their unaffected siblings, the group of outlier genes is significantly enriched in neural-related pathways, including neuropeptide signaling, synaptogenesis, and cell adhesion. We demonstrate that outlier genes cluster within the most pathogenic CNVs (rare de novo CNVs) and can be used for the prioritization of rare CNVs of potentially unknown significance. Several nonrecurrent CNVs with significant gene-expression alterations are identified (these include deletions in chromosomal regions 3q27, 3p13, and 3p26 and duplications at 2p15), suggesting that these are potential candidate ASD loci. In addition, we identify distinct expression changes in 16p11.2 microdeletions, 16p11.2 microduplications, and 7q11.23 duplications, and we show that specific genes within the 16p CNV interval correlate with differences in head circumference, an ASD-relevant phenotype. This study provides evidence that pathogenic structural variants have a functional impact via transcriptome alterations in ASDs at a genome-wide level and demonstrates the utility of integrating gene expression with mutation data for the prioritization of genes disrupted by potentially pathogenic mutations.

Vitamin D insufficiency and severe asthma exacerbations in Puerto Rican children

RATIONALE

Vitamin D insufficiency (a serum 25(OH)D <30 ng/ml) has been associated with severe asthma exacerbations, but this could be explained by underlying racial ancestry or disease severity. Little is known about vitamin D and asthma in Puerto Ricans.

OBJECTIVES

To examine whether vitamin D insufficiency is associated with severe asthma exacerbations in Puerto Rican children, independently of racial ancestry, atopy, and time outdoors.

METHODS

A cross-sectional study was conducted of 560 children ages 6-14 years with (n = 287) and without (n = 273) asthma in San Juan, Puerto Rico. We measured plasma vitamin D and estimated the percentage of African racial ancestry among participants using genome-wide genotypic data. We tested whether vitamin D insufficiency is associated with severe asthma exacerbations, lung function, or atopy (greater than or equal to one positive IgE to allergens) using logistic or linear regression. Multivariate models were adjusted for African ancestry, time outdoors, atopy, and other covariates.

MEASUREMENTS AND MAIN RESULTS

Vitamin D insufficiency was common in children with (44%) and without (47%) asthma. In multivariate analyses, vitamin D insufficiency was associated with higher odds of greater than or equal to one severe asthma exacerbation in the prior year (odds ratio [OR], 2.6; 95% confidence interval [CI], 1.5-4.9; P = 0.001) and atopy, and a lower FEV(1)/FVC in cases. After stratification by atopy, the magnitude of the association between vitamin D insufficiency and severe exacerbations was greater in nonatopic (OR, 6.2; 95% CI, 2-21.6; P = 0.002) than in atopic (OR, 2; 95% CI, 1-4.1; P = 0.04) cases.

CONCLUSIONS

Vitamin D insufficiency is associated with severe asthma exacerbations in Puerto Rican children, independently of racial ancestry, atopy, or markers of disease severity or control.

African ancestry and lung function in Puerto Rican children

BACKGROUND

Puerto Rican and African American subjects share a significant proportion of African ancestry. Recent findings suggest that African ancestry influences lung function in African American adults.

OBJECTIVE

We sought to examine whether a greater proportion of African ancestry is associated with lower FEV(1) and forced vital capacity (FVC) in Puerto Rican children independently of socioeconomic status, health care access, or key environmental/lifestyle factors.

METHODS

We performed a cross-sectional case-control study of 943 Puerto Rican children aged 6 to 14 years with (n= 520) and without (n= 423) asthma (defined as physician-diagnosed asthma and wheeze in the prior year) living in Hartford, Connecticut (n= 383), and San Juan, Puerto Rico (n= 560). We estimated the percentage of African racial ancestry in study participants using genome-wide genotypic data. We tested whether African ancestry is associated with FEV(1) and FVC using linear regression. Multivariate models were adjusted for indicators of socioeconomic status and health care and selected environmental/lifestyle exposures.

RESULTS

After adjustment for household income and other covariates, each 20% increment in African ancestry was significantly associated with lower prebronchodilator FEV(1) (-105 mL; 95% CI, -159 to -51 mL; P< .001) and FVC (-133 mL; 95% CI, -197 to -69 mL; P< .001) and postbronchodilator FEV(1) (-152 mL; 95% CI, -210 to -94 mL; P< .001) and FVC (-145 mL; 95% CI, -211 to -79 mL; P< .001) in children with asthma. Similar but weaker associations were found for prebronchodilator and postbronchodilator FEV(1) (change for each 20% increment in African ancestry, -78 mL; 95% CI, -131 to -25 mL; P= .004) and for postbronchodilator FVC among children without asthma.

CONCLUSIONS

Genetic factors, environmental/lifestyle factors, or both correlated with African ancestry might influence childhood lung function in Puerto Rican subjects.

Amino acid position 11 of HLA-DRβ1 is a major determinant of chromosome 6p association with ulcerative colitis

The major histocompatibility complex (MHC) on chromosome 6p is an established risk locus for ulcerative colitis (UC) and Crohn's disease (CD). We aimed to better define MHC association signals in UC and CD by combining data from dense single-nucleotide polymorphism (SNP) genotyping and from imputation of classical human leukocyte antigen (HLA) types, their constituent SNPs and corresponding amino acids in 562 UC, 611 CD and 1428 control subjects. Univariate and multivariate association analyses were performed, controlling for ancestry. In univariate analyses, absence of the rs9269955 C allele was strongly associated with risk for UC (P = 2.67 × 10(-13)). rs9269955 is a SNP in the codon for amino acid position 11 of HLA-DRβ1, located in the P6 pocket of the HLA-DR antigen binding cleft. This amino acid position was also the most significantly UC-associated amino acid in omnibus tests (P = 2.68 × 10(-13)). Multivariate modeling identified rs9269955-C and 13 other variants in best predicting UC vs control status. In contrast, there was only suggestive association evidence between the MHC and CD. Taken together, these data demonstrate that variation at HLA-DRβ1, amino acid 11 in the P6 pocket of the HLA-DR complex antigen binding cleft is a major determinant of chromosome 6p association with UC.

Genetic analysis of vertebral trabecular bone density and cross-sectional area in older men

We investigated 383 bone candidate genes for associations between single nucleotide polymorphisms and vertebral trabecular volumetric bone mineral density (vBMD) and cross-sectional area (CSA) in 2,018 Caucasian men aged ≥ 65 years. SNPs in TGFBR3, SOST, KL, CALCR, LEP, CSF1R, PTN, GNRH2, FGFR2, and MEPE were associated with vBMD and SNPs in CYP11B1, DVL2, DLX5, WNT4, and PAX7 were associated with CSA in independent study samples (p < 0.005).

INRODUCTION

Vertebral bone mineral density and cross-sectional area are important determinants of vertebral bone strength. Little is known about the specific genetic variants that influence these phenotypes in humans.

METHODS

We investigated the potential genetic variants associated with vertebral trabecular volumetric BMD and CSA measured by quantitative computed tomography. We initially tested for association between these phenotypes and 4608 tagging and potentially functional single nucleotide polymorphisms (SNPs) in 383 candidate genes in 862 community-dwelling Caucasian men aged ≥ 65 years in the Osteoporotic Fractures in Men Study.

RESULTS

SNP associations were then validated by genotyping an additional 1,156 randomly sampled men from the same cohort. We identified 11 SNPs in 10 genes (TGFBR3, SOST, KL, CALCR, LEP, CSF1R, PTN, GNRH2, FGFR2, and MEPE) that were consistently associated with trabecular vBMD and five SNPs in five genes (CYP11B1, DVL2, DLX5, WNT4, and PAX7) that were consistently associated with CSA in both samples (p < 0.005).

CONCLUSION

None of the SNPs associated with trabecular vBMD were associated with CSA. Our findings raise the possibility that at least some of the loci for vertebral trabecular BMD and bone size may be distinct.

Using ancestry matching to combine family-based and unrelated samples for genome-wide association studies

We propose a method to analyze family-based samples together with unrelated cases and controls. The method builds on the idea of matched case-control analysis using conditional logistic regression (CLR). For each trio within the family, a case (the proband) and matched pseudo-controls are constructed, based upon the transmitted and untransmitted alleles. Unrelated controls, matched by genetic ancestry, supplement the sample of pseudo-controls; likewise unrelated cases are also paired with genetically matched controls. Within each matched stratum, the case genotype is contrasted with control/pseudo-control genotypes via CLR, using a method we call matched-CLR (mCLR). Eigenanalysis of numerous SNP genotypes provides a tool for mapping genetic ancestry. The result of such an analysis can be thought of as a multidimensional map, or eigenmap, in which the relative genetic similarities and differences amongst individuals is encoded in the map. Once constructed, new individuals can be projected onto the ancestry map based on their genotypes. Successful differentiation of individuals of distinct ancestry depends on having a diverse, yet representative sample from which to construct the ancestry map. Once samples are well-matched, mCLR yields comparable power to competing methods while ensuring excellent control over Type I error.