Decreased serum arylesterase activity in autism spectrum disorders.

The PON1 gene, previously found associated with autism spectrum disorders (ASDs), encodes a serum protein responsible for the detoxification of organophosphates (OPs) and able to exert several enzymatic activities. PON1 arylesterase, but not diazoxonase activity, was significantly decreased in 174 ASD patients compared to 175 first-degree relatives and 144 controls (P=2.65×10⁻¹6). First degree relatives displayed intermediate activities, closer to patient than to control levels. Differences between patients, first-degree relatives and controls were especially evident among 164 Italians compared to 329 Caucasian-Americans, because arylesterase activity was significantly higher in Italian controls, compared to Caucasian-American controls (P=2.84×10⁻¹6). Arylesterase activity and PON protein concentrations were not significantly correlated, supporting a functional inhibition of arylesterase activity in ASD patients over quantitative changes in protein amounts. Serum arylesterase activity, in combination with PON1 genotypes at two single nucleotide polymorphisms (SNPs) known to influence protein amounts (rs705379: C-108T) and substrate specificity (rs662: Q192R), was able to discriminate ASD patients from controls with elevated sensitivity and specificity, depending on genotype and ethnic group. Serum arylesterase activity and genotyping at these two SNPs could thus represent an informative biochemical/genetic test, able to aid clinicians in estimating autism risk in ethnic groups with higher baseline arylesterase activity levels.

Genetic control of individual differences in gene-specific methylation in human brain.

We have observed extensive interindividual differences in DNA methylation of 8590 CpG sites of 6229 genes in 153 human adult cerebellum samples, enriched in CpG island "shores" and at further distances from CpG islands. To search for genetic factors that regulate this variation, we performed a genome-wide association study (GWAS) mapping of methylation quantitative trait loci (mQTLs) for the 8590 testable CpG sites. cis association refers to correlation of methylation with SNPs within 1 Mb of a CpG site. 736 CpG sites showed phenotype-wide significant cis association with 2878 SNPs (after permutation correction for all tested markers and methylation phenotypes). In trans analysis of methylation, which tests for distant regulation effects, associations of 12 CpG sites and 38 SNPs remained significant after phenotype-wide correction. To examine the functional effects of mQTLs, we analyzed 85 genes that were with genetically regulated methylation we observed and for which we had quality gene expression data. Ten genes showed SNP-methylation-expression three-way associations-the same SNP simultaneously showed significant association with both DNA methylation and gene expression, while DNA methylation was significantly correlated with gene expression. Thus, we demonstrated that DNA methylation is frequently a heritable continuous quantitatively variable trait in human brain. Unlike allele-specific methylation, genetic polymorphisms mark both cis- and trans-regulatory genetic sites at measurable distances from their CpG sites. Some of the genetically regulated DNA methylation is directly connected with genetically regulated gene expression variation.

Cerebellar telomere length and psychiatric disorders.

We tested whether telomere length is altered in the brains of patients diagnosed with major depression (MD), bipolar disorder (BD) and schizophrenia (SZ) by measuring mean telomere length (mTL) with real-time PCR. The samples are cerebellar gray matter from 46 SZ, 46 BP, and 15 MD patients, and 48 healthy controls. We found no difference in mTL between SZ and controls, BD and controls, MD and controls, or all cases and controls; no correlation between mTL and age was observed, either. This suggests that brain gray matter is unlikely to be related to the telomere length shortening reported in blood of psychiatric patients. White matter deserves further investigation as it has been reported to have a different mTL dynamic from gray matter. Since mTL has been reported to be a heritable quantitative trait, we also carried out genome-wide mapping of genetic factors for mTL, treating mTL as a quantitative trait. No association survived correction of multiple testing for the number of SNPs studied. The previously reported rs2630578 (BICD1) association was not replicated. This suggests that telomere length of cerebellar gray matter is determined by multiple loci with "weak effects."

Identification of genetic variants using bar-coded multiplexed sequencing.

We developed a generalized framework for multiplexed resequencing of targeted human genome regions on the Illumina Genome Analyzer using degenerate indexed DNA bar codes ligated to fragmented DNA before sequencing. Using this method, we simultaneously sequenced the DNA of multiple HapMap individuals at several Encyclopedia of DNA Elements (ENCODE) regions. We then evaluated the use of Bayes factors for discovering and genotyping polymorphisms. For polymorphisms that were either previously identified within the Single Nucleotide Polymorphism database (dbSNP) or visually evident upon re-inspection of archived ENCODE traces, we observed a false positive rate of 11.3% using strict thresholds for predicting variants and 69.6% for lax thresholds. Conversely, false negative rates were 10.8-90.8%, with false negatives at stricter cut-offs occurring at lower coverage (<10 aligned reads). These results suggest that >90% of genetic variants are discoverable using multiplexed sequencing provided sufficient coverage at the polymorphic base.

Resolving individuals contributing trace amounts of DNA to highly complex mixtures using high-density SNP genotyping microarrays.

We use high-density single nucleotide polymorphism (SNP) genotyping microarrays to demonstrate the ability to accurately and robustly determine whether individuals are in a complex genomic DNA mixture. We first develop a theoretical framework for detecting an individual's presence within a mixture, then show, through simulations, the limits associated with our method, and finally demonstrate experimentally the identification of the presence of genomic DNA of specific individuals within a series of highly complex genomic mixtures, including mixtures where an individual contributes less than 0.1% of the total genomic DNA. These findings shift the perceived utility of SNPs for identifying individual trace contributors within a forensics mixture, and suggest future research efforts into assessing the viability of previously sub-optimal DNA sources due to sample contamination. These findings also suggest that composite statistics across cohorts, such as allele frequency or genotype counts, do not mask identity within genome-wide association studies. The implications of these findings are discussed.

Multimarker analysis and imputation of multiple platform pooling-based genome-wide association studies.

For many genome-wide association (GWA) studies individually genotyping one million or more SNPs provides a marginal increase in coverage at a substantial cost. Much of the information gained is redundant due to the correlation structure inherent in the human genome. Pooling-based GWA studies could benefit significantly by utilizing this redundancy to reduce noise, improve the accuracy of the observations and increase genomic coverage. We introduce a measure of correlation between individual genotyping and pooling, under the same framework that r(2) provides a measure of linkage disequilibrium (LD) between pairs of SNPs. We then report a new non-haplotype multimarker multi-loci method that leverages the correlation structure between SNPs in the human genome to increase the efficacy of pooling-based GWA studies. We first give a theoretical framework and derivation of our multimarker method. Next, we evaluate simulations using this multimarker approach in comparison to single marker analysis. Finally, we experimentally evaluate our method using different pools of HapMap individuals on the Illumina 450S Duo, Illumina 550K and Affymetrix 5.0 platforms for a combined total of 1 333 631 SNPs. Our results show that use of multimarker analysis reduces noise specific to pooling-based studies, allows for efficient integration of multiple microarray platforms and provides more accurate measures of significance than single marker analysis. Additionally, this approach can be extended to allow for imputing the association significance for SNPs not directly observed using neighboring SNPs in LD. This multimarker method can now be used to cost-effectively complete pooling-based GWA studies with multiple platforms across over one million SNPs and to impute neighboring SNPs weighted for the loss of information due to pooling.