The ADVANCE network: accelerating data value across a national community health center network

The ADVANCE (Accelerating Data Value Across a National Community Health Center Network) clinical data research network (CDRN) is led by the OCHIN Community Health Information Network in partnership with Health Choice Network and Fenway Health. The ADVANCE CDRN will ‘horizontally’ integrate outpatient electronic health record data for over one million federally qualified health center patients, and ‘vertically’ integrate hospital, health plan, and community data for these patients, often under-represented in research studies. Patient investigators, community investigators, and academic investigators with diverse expertise will work together to meet project goals related to data integration, patient engagement and recruitment, and the development of streamlined regulatory policies. By enhancing the data and research infrastructure of participating organizations, the ADVANCE CDRN will serve as a ‘community laboratory’ for including disadvantaged and vulnerable patients in patient-centered outcomes research that is aligned with the priorities of patients, clinics, and communities in our network

SNPs in Multi-Species Conserved Sequences (MCS) as useful markers in association studies: a practical approach

<p>Abstract</p> <p>Background</p> <p>Although genes play a key role in many complex diseases, the specific genes involved in most complex diseases remain largely unidentified. Their discovery will hinge on the identification of key sequence variants that are conclusively associated with disease. While much attention has been focused on variants in protein-coding DNA, variants in noncoding regions may also play many important roles in complex disease by altering gene regulation. Since the vast majority of noncoding genomic sequence is of unknown function, this increases the challenge of identifying "functional" variants that cause disease. However, evolutionary conservation can be used as a guide to indicate regions of noncoding or coding DNA that are likely to have biological function, and thus may be more likely to harbor SNP variants with functional consequences. To help bias marker selection in favor of such variants, we devised a process that prioritizes annotated SNPs for genotyping studies based on their location within Multi-species Conserved Sequences (MCSs) and used this process to select SNPs in a region of linkage to a complex disease. This allowed us to evaluate the utility of the chosen SNPs for further association studies. Previously, a region of chromosome 1q43 was linked to Multiple Sclerosis (MS) in a genome-wide screen. We chose annotated SNPs in the region based on location within MCSs (termed MCS-SNPs). We then obtained genotypes for 478 MCS-SNPs in 989 individuals from MS families.</p> <p>Results</p> <p>Analysis of our MCS-SNP genotypes from the 1q43 region and comparison to HapMap data confirmed that annotated SNPs in MCS regions are frequently polymorphic and show subtle signatures of selective pressure, consistent with previous reports of genome-wide variation in conserved regions. We also present an online tool that allows MCS data to be directly exported to the UCSC genome browser so that MCS-SNPs can be easily identified within genomic regions of interest.</p> <p>Conclusion</p> <p>Our results showed that MCS can easily be used to prioritize markers for follow-up and candidate gene association studies. We believe that this novel approach demonstrates a paradigm for expediting the search for genes contributing to complex diseases.</p

Surface reservoirs dominate dynamic gas-surface partitioning of many indoor air constituents

Human health is affected by indoor air quality. One distinctive aspect of the indoor environment is its very large surface area that acts as a poorly characterized sink and source of gas-phase chemicals. In this work, air-surface interactions of 19 common indoor air contaminants with diverse properties and sources were monitored in a house using fast-response, on-line mass spectrometric and spectroscopic methods. Enhanced-ventilation experiments demonstrate that most of the contaminants reside in the surface reservoirs and not, as expected, in the gas phase. They participate in rapid air-surface partitioning that is much faster than air exchange. Phase distribution calculations are consistent with the observations when assuming simultaneous equilibria between air and large weakly polar and polar absorptive surface reservoirs, with acid-base dissociation in the polar reservoir. Chemical exposure assessments must account for the finding that contaminants that are fully volatile under outdoor air conditions instead behave as semivolatile compounds indoors

Author Correction: A population-specific reference panel empowers genetic studies of Anabaptist populations.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper

Combinatorial Mismatch Scan (CMS) for loci associated with dementia in the Amish

BACKGROUND: Population heterogeneity may be a significant confounding factor hampering detection and verification of late onset Alzheimer's disease (LOAD) susceptibility genes. The Amish communities located in Indiana and Ohio are relatively isolated populations that may have increased power to detect disease susceptibility genes. METHODS: We recently performed a genome scan of dementia in this population that detected several potential loci. However, analyses of these data are complicated by the highly consanguineous nature of these Amish pedigrees. Therefore we applied the Combinatorial Mismatch Scanning (CMS) method that compares identity by state (IBS) (under the presumption of identity by descent (IBD)) sharing in distantly related individuals from such populations where standard linkage and association analyses are difficult to implement. CMS compares allele sharing between individuals in affected and unaffected groups from founder populations. Comparisons between cases and controls were done using two Fisher's exact tests, one testing for excess in IBS allele frequency and the other testing for excess in IBS genotype frequency for 407 microsatellite markers. RESULTS: In all, 13 dementia cases and 14 normal controls were identified who were not related at least through the grandparental generation. The examination of allele frequencies identified 24 markers (6%) nominally (p ≤ 0.05) associated with dementia; the most interesting (empiric p ≤ 0.005) markers were D3S1262, D5S211, and D19S1165. The examination of genotype frequencies identified 21 markers (5%) nominally (p ≤ 0.05) associated with dementia; the most significant markers were both located on chromosome 5 (D5S1480 and D5S211). Notably, one of these markers (D5S211) demonstrated differences (empiric p ≤ 0.005) under both tests. CONCLUSION: Our results provide the initial groundwork for identifying genes involved in late-onset Alzheimer's disease within the Amish community. Genes identified within this isolated population will likely play a role in a subset of late-onset AD cases across more general populations. Regions highlighted by markers demonstrating suggestive allelic and/or genotypic differences will be the focus of more detailed examination to characterize their involvement in dementia

An X chromosome-wide association study in autism families identifies TBL1X as a novel autism spectrum disorder candidate gene in males

<p>Abstract</p> <p>Background</p> <p>Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with a strong genetic component. The skewed prevalence toward males and evidence suggestive of linkage to the X chromosome in some studies suggest the presence of X-linked susceptibility genes in people with ASD.</p> <p>Methods</p> <p>We analyzed genome-wide association study (GWAS) data on the X chromosome in three independent autism GWAS data sets: two family data sets and one case-control data set. We performed meta- and joint analyses on the combined family and case-control data sets. In addition to the meta- and joint analyses, we performed replication analysis by using the two family data sets as a discovery data set and the case-control data set as a validation data set.</p> <p>Results</p> <p>One SNP, rs17321050, in the transducin β-like 1X-linked (<it>TBL1X</it>) gene [OMIM:300196] showed chromosome-wide significance in the meta-analysis (<it>P </it>value = 4.86 × 10^-6) and joint analysis (<it>P </it>value = 4.53 × 10^-6) in males. The SNP was also close to the replication threshold of 0.0025 in the discovery data set (<it>P </it>= 5.89 × 10^-3) and passed the replication threshold in the validation data set (<it>P </it>= 2.56 × 10^-4). Two other SNPs in the same gene in linkage disequilibrium with rs17321050 also showed significance close to the chromosome-wide threshold in the meta-analysis.</p> <p>Conclusions</p> <p><it>TBL1X </it>is in the Wnt signaling pathway, which has previously been implicated as having a role in autism. Deletions in the Xp22.2 to Xp22.3 region containing <it>TBL1X </it>and surrounding genes are associated with several genetic syndromes that include intellectual disability and autistic features. Our results, based on meta-analysis, joint analysis and replication analysis, suggest that <it>TBL1X </it>may play a role in ASD risk.</p

Targeted massively parallel sequencing of autism spectrum disorder-associated genes in a case control cohort reveals rare loss-of-function risk variants

BACKGROUND: Autism spectrum disorder (ASD) is highly heritable, yet genome-wide association studies (GWAS), copy number variation screens, and candidate gene association studies have found no single factor accounting for a large percentage of genetic risk. ASD trio exome sequencing studies have revealed genes with recurrent de novo loss-of-function variants as strong risk factors, but there are relatively few recurrently affected genes while as many as 1000 genes are predicted to play a role. As such, it is critical to identify the remaining rare and low-frequency variants contributing to ASD. METHODS: We have utilized an approach of prioritization of genes by GWAS and follow-up with massively parallel sequencing in a case-control cohort. Using a previously reported ASD noise reduction GWAS analyses, we prioritized 837 RefSeq genes for custom targeting and sequencing. We sequenced the coding regions of those genes in 2071 ASD cases and 904 controls of European white ancestry. We applied comprehensive annotation to identify single variants which could confer ASD risk and also gene-based association analysis to identify sets of rare variants associated with ASD. RESULTS: We identified a significant over-representation of rare loss-of-function variants in genes previously associated with ASD, including a de novo premature stop variant in the well-established ASD candidate gene RBFOX1. Furthermore, ASD cases were more likely to have two damaging missense variants in candidate genes than controls. Finally, gene-based rare variant association implicates genes functioning in excitatory neurotransmission and neurite outgrowth and guidance pathways including CACNAD2, KCNH7, and NRXN1. CONCLUSIONS: We find suggestive evidence that rare variants in synaptic genes are associated with ASD and that loss-of-function mutations in ASD candidate genes are a major risk factor, and we implicate damaging mutations in glutamate signaling receptors and neuronal adhesion and guidance molecules. Furthermore, the role of de novo mutations in ASD remains to be fully investigated as we identified the first reported protein-truncating variant in RBFOX1 in ASD. Overall, this work, combined with others in the field, suggests a convergence of genes and molecular pathways underlying ASD etiology. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13229-015-0034-z) contains supplementary material, which is available to authorized users

A comparative analysis of the information content in long and short SAGE libraries

BACKGROUND: Serial Analysis of Gene Expression (SAGE) is a powerful tool to determine gene expression profiles. Two types of SAGE libraries, ShortSAGE and LongSAGE, are classified based on the length of the SAGE tag (10 vs. 17 basepairs). LongSAGE libraries are thought to be more useful than ShortSAGE libraries, but their information content has not been widely compared. To dissect the differences between these two types of libraries, we utilized four libraries (two LongSAGE and two ShortSAGE libraries) generated from the hippocampus of Alzheimer and control samples. In addition, we generated two additional short SAGE libraries, the truncated long SAGE libraries (tSAGE), from LongSAGE libraries by deleting seven 5' basepairs from each LongSAGE tag. RESULTS: One problem that occurred in the SAGE study is that individual tags may have matched to multiple different genes – due to the short length of a tag. We found that the LongSAGE tag maps up to 15 UniGene clusters, while the ShortSAGE and tSAGE tags map up to 279 UniGene clusters. Both long and short SAGE libraries exhibit a large number of orphan tags (no gene information in UniGene), implying the limitation of the UniGene database. Among 100 orphan LongSAGE tags, the complete sequences (17 basepairs) of nine orphan tags match to 17 genomic sequences; four of the orphan tags match to a single genomic sequence. Our data show the potential to resolve 4–9% of orphan LongSAGE tags. Finally, among 400 tSAGE tags showing significant differential expression between AD and control, 79 tags (19.8%) were derived from multiple non-significant LongSAGE tags, implying the false positive results. CONCLUSION: Our data show that LongSAGE tags have high specificity in gene mapping compared to ShortSAGE tags. LongSAGE tags show an advantage over ShortSAGE in identifying novel genes by BLAST analysis. Most importantly, the chances of obtaining false positive results are higher for ShortSAGE than LongSAGE libraries due to their specificity in gene mapping. Therefore, it is recommended that the number of corresponding UniGene clusters (gene or ESTs) of a tag for prioritizing the significant results be considered

Copy Number Variants in Extended Autism Spectrum Disorder Families Reveal Candidates Potentially Involved in Autism Risk

Copy number variations (CNVs) are a major cause of genetic disruption in the human genome with far more nucleotides being altered by duplications and deletions than by single nucleotide polymorphisms (SNPs). In the multifaceted etiology of autism spectrum disorders (ASDs), CNVs appear to contribute significantly to our understanding of the pathogenesis of this complex disease. A unique resource of 42 extended ASD families was genotyped for over 1 million SNPs to detect CNVs that may contribute to ASD susceptibility. Each family has at least one avuncular or cousin pair with ASD. Families were then evaluated for co-segregation of CNVs in ASD patients. We identified a total of five deletions and seven duplications in eleven families that co-segregated with ASD. Two of the CNVs overlap with regions on 7p21.3 and 15q24.1 that have been previously reported in ASD individuals and two additional CNVs on 3p26.3 and 12q24.32 occur near regions associated with schizophrenia. These findings provide further evidence for the involvement of ICA1 and NXPH1 on 7p21.3 in ASD susceptibility and highlight novel ASD candidates, including CHL1, FGFBP3 and POUF41. These studies highlight the power of using extended families for gene discovery in traits with a complex etiology