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Background: Obstructive sleep apnea (OSA) is defined by frequent episodes of reduced or complete cessation of airflow during sleep and is linked to negative health outcomes. Understanding the genetic factors influencing expression of OSA may lead to new treatment strategies. Electronic health records (EHRs) can be leveraged to both validate previously reported OSA-associated genomic variation and detect novel relationships between these variants and comorbidities., Methods: We identified candidate single nucleotide polymorphisms (SNPs) via systematic literature review of existing research. Using datasets available at Geisinger (n = 39,407) and Vanderbilt University Medical Center (n = 24,084), we evaluated associations between 40 previously implicated SNPs and OSA diagnosis, defined using clinical codes. We also evaluated associations between these SNPs and OSA severity measures obtained from sleep reports at Geisinger (n = 6571). Finally, we used a phenome-wide association study approach to help reveal pleiotropic genetic effects between OSA candidate SNPs and other clinical codes and laboratory values available in the EHR., Results: Most previously reported OSA candidate SNPs showed minimal to no evidence for associations with OSA diagnosis or severity in the EHR-derived datasets. Three SNPs in LEPR, MMP-9, and GABBR1 validated for an association with OSA diagnosis in European Americans; the SNP in GABBR1 was associated following meta-analysis of results from both clinical populations. The GABBR1 and LEPR SNPs, and one additional SNP, were associated with OSA severity measures in European Americans from Geisinger. Three additional candidate OSA SNPs were not associated with OSA-related traits but instead with hyperlipidemia and autoimmune diseases of the thyroid., Conclusions: To our knowledge, this is one of the largest candidate gene studies and one of the first phenome-wide association studies of OSA genomic variation. Results validate genetic associates with OSA in the LEPR, MMP-9 and GABBR1 genes, but suggest that the majority of previously identified genetic associations with OSA may be false positives. Phenome-wide analyses provide evidence of mediated pleiotropy. Future well-powered genome-wide association analyses of OSA risk and severity across populations with diverse ancestral backgrounds are needed. The comprehensive nature of the analyses represents a platform for informing future work focused on understanding how genetic data can be useful to informing treatment of OSA and related comorbidities.

Importance: While numerous genetic susceptibility loci have been identified for clinical Alzheimer disease (AD), it is important to establish whether these variants are risk factors for the underlying disease pathology, including neuritic plaques., Objectives: To investigate whether AD susceptibility loci from genome-wide association studies affect neuritic plaque pathology and to additionally identify novel risk loci for this trait., Design, Setting, and Participants: Candidate analysis of single-nucleotide polymorphisms and genome-wide association study in a joint clinicopathologic cohort, including 725 deceased subjects from the Religious Orders Study and the Rush Memory and Aging Project (2 prospective, community-based studies), followed by targeted validation in an independent neuroimaging cohort, including 114 subjects from multiple clinical and research centers., Main Outcomes and Measures: A quantitative measure of neuritic plaque pathologic burden, based on assessments of silver-stained tissue averaged from multiple brain regions. Validation based on β-amyloid load by immunocytochemistry, and replication with fibrillar β-amyloid positron emission tomographic imaging with Pittsburgh Compound B or florbetapir., Results: Besides the previously reported APOE and CR1 loci, we found that the ABCA7 (rs3764650; P = .02) and CD2AP (rs9349407; P = .03) AD susceptibility loci are associated with neuritic plaque burden. In addition, among the top results of our genome-wide association study, we discovered a novel variant near the amyloid precursor protein gene (APP, rs2829887) that is associated with neuritic plaques (P = 3.3 × 10-6). This polymorphism was associated with postmortem β-amyloid load as well as fibrillar β-amyloid in 2 independent cohorts of adults with normal cognition., Conclusions and Relevance: These findings enhance understanding of AD risk factors by relating validated susceptibility alleles to increased neuritic plaque pathology and implicate common genetic variation at the APP locus in the earliest, presymptomatic stages of AD.

Objective: We developed rheumatoid arthritis (RA) risk models based on validated environmental factors (E), genetic risk scores (GRS), and gene-environment interactions (GEI) to identify factors that can improve accuracy and reclassification., Methods: Models including E, GRS, and GEI were developed among 317 white seropositive RA cases and 551 controls from the Nurses' Health Studies (NHS) and validated in 987 white anti-citrullinated protein antibody-positive cases and 958 controls from the Swedish Epidemiologic Investigation of Rheumatoid Arthritis (EIRA), stratified by sex. Primary analyses included age, smoking, alcohol, parity, weighted GRS using 31 non-HLA alleles and 8 HLA-DRB1 alleles, and the HLA × smoking interaction. Expanded models included reproductive, geographic, and occupational factors and additional GEI terms. Hierarchical models were compared for discriminative accuracy using the area under the receiver operating characteristic curve (AUC) and reclassification using the integrated discrimination improvement (IDI) and the continuous net reclassification improvement., Results: The mean age at RA diagnosis was 56 years in the NHS and 51 years in the EIRA. Primary models produced AUCs of 0.716 in the NHS, 0.716 in women in the EIRA, and 0.756 in men in the EIRA. Expanded models produced improvements in discrimination with AUCs of 0.738 in the NHS, 0.724 in women in the EIRA, and 0.769 in men in the EIRA. Models including genetic factors (G) or G + GEI improved reclassification over E models; the full E + G + GEI model provided the optimal predictive ability by IDI analyses., Conclusion: We have developed comprehensive RA risk models incorporating E, G, and GEI that have improved the discriminative accuracy for RA. Further work developing and assessing highly specific prediction models in prospective cohorts is still needed to inform primary RA prevention trials., (Copyright © 2013 by the American College of Rheumatology.)

Background: Recent genetic studies of stroke and related risk factors have identified a growing number of susceptibility loci; however, the relationship of these alleles to ischemic stroke is unknown. The challenge in finding reproducible loci of ischemic stroke susceptibility may be in part related to the etiologic heterogeneity in clinically defined stroke subtypes. In this study, we tested whether known single nucleotide polymorphisms (SNPs) associated with stroke or putative stroke risk factors are associated with neuropathologically defined micro- or macroscopic infarcts and with arteriolosclerosis., Methods: Measures of neuropathology and genotyping were available from 755 deceased participants from the Religious Orders Study and the Rush Memory and Aging Project. All donated brains were examined by a board-certified neuropathologist using standardized protocol for the presence of microscopic infarct, macroscopic infarct and arteriolosclerosis (lipohyalinosis). In primary analysis, 74 candidate SNPs previously associated (p < 5 × 10(-8)) with ischemic stroke or known risk factors, including atrial fibrillation (AF), hypertension, diabetes, low-density lipoprotein (LDL) level and carotid artery stenosis, were evaluated for association with neuropathologic endpoints. We performed a secondary exploratory analysis to include 93 additional SNPs associated with putative ischemic stroke risk factors including SNPs associated with high-density lipoprotein (HDL), triglyceride serum levels, myocardial infarction (MI), coronary artery disease and cerebral white matter disease. Regression models relating SNPs to cerebrovascular neuropathology were adjusted for age at death, gender and cohort membership., Results: The strongest associations seen for both macroscopic and microscopic infarcts were risk variants associated with diabetes. The diabetes risk variant rs7578326 located near the IRS1 locus was associated with both macroscopic (OR = 0.73, p = 0.011) and microscopic (OR = 0.71, p = 0.009) infarct pathology. Another diabetes susceptibility locus (rs12779790) located between the calcium/calmodulin-dependent protein kinase ID (CAMK1D) and cell division cycle 123 homolog (CDC123) genes is also associated with both macroscopic (OR = 1.40, p = 0.0292) and microscopic infarcts (OR = 1.43, p = 0.0285). The diabetes risk variant rs864745 within JAZF1 was associated with arteriolosclerosis (OR = 0.80, p = 0.014). We observed suggestive associations with the diabetes risk variant rs7961581 (p = 0.038; between TSPAN8 and LGR5) and rs5215 (p = 0.043; KCNJ11), the LDL risk variant rs11206510 (p = 0.045; PCSK9), as well as the AF risk locus ZFHX3. The CDKN2A/B locus (rs2383207, 9p21), identified initially as a susceptibility allele for MI and recently implicated in large vessel stroke, was associated with macroscopic infarct pathology in our autopsy cohort (OR = 1.26, p = 0.031)., Conclusion: Our results suggest replication of the candidate CDKN2A/B stroke susceptibility locus with directly measured macroscopic stroke neuropathology, and further implicate several diabetes and other risk variants with secondary, pleiotropic associations to stroke-related pathology in our autopsy cohort. When coupled with larger sample sizes, cerebrovascular neuropathologic phenotypes will likely be powerful tools for the genetic dissection of susceptibility for ischemic stroke., (© 2013 S. Karger AG, Basel.)

NK cells play an important role in innate immunity. A previous genome-wide association study demonstrated an association between a 17q12 allele (rs9916629(C)) and lower frequency of CD3(-)CD56(+) NK cells in peripheral blood. We performed an analysis that not only replicates the original result of the genome-wide association study (p = 0.036) but also defines the specific cell subpopulations and functions that are modulated by the rs9916629 polymorphism in a cohort of 96 healthy adult subjects using targeted multiparameter flow cytometric profiling of NK cell phenotypes and functions. We found that rs9916629(C) is associated with alterations in specific NK cell subsets, including lower frequency of predominantly cytotoxic CD56(dim) NK cells (p = 0.011), higher frequency of predominantly regulatory CD56(bright) NK cells (p = 0.019), and a higher proportion of NK cells expressing the inhibitory NKG2A receptor (p = 0.0002). Functionally, rs9916629(C) is associated with decreased secretion of macrophage inflammatory protein-1β by NK cells in the context of Ab-dependent cell-mediated cytotoxicity (p = 0.039) and increased degranulation in response to MHC class I-deficient B cells (p = 0.017). Transcriptional profiling of NK cells suggests that rs9916629 influences the expression of transcription factors such as TBX21, which has a role in NK cell differentiation, offering a possible mechanism for the phenotypic and functional differences between the different alleles. The rs9916629(C) allele therefore has a validated effect on the proportion of NK cells in peripheral blood and skews NK cells toward a specific phenotypic and functional profile, potentially influencing the impact that these innate immune cells have on infection and autoimmunity.

We have leveraged a Drosophila model relevant to Alzheimer disease (AD) for functional screening of findings from a genome-wide scan for loci associated with a quantitative measure of AD pathology in humans. In six of the 15 genomic regions evaluated, we successfully identified a causal gene for the association, on the basis of in vivo interactions with the neurotoxicity of Tau, which forms neurofibrillary tangles in AD. Among the top results, rs10845990 within SLC2A14, encoding a glucose transporter, showed evidence of replication for association with AD pathology, and gain and loss of function in glut1, the Drosophila ortholog, was associated with suppression and enhancement of Tau toxicity, respectively. Our strategy of coupling genome-wide association in humans with functional screening in a model organism is likely to be a powerful approach for gene discovery in AD and other complex genetic disorders., (Copyright © 2011 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Background: Recent discoveries of risk alleles have made it possible to define genetic risk profiles for patients with rheumatoid arthritis (RA). This study examined whether a cumulative score based on 22 validated genetic risk alleles for seropositive RA would identify high-risk, asymptomatic individuals who might benefit from preventive interventions., Methods: Eight human leucocyte antigen (HLA) alleles and 14 single-nucleotide polymorphisms representing 13 validated RA risk loci were genotyped among 289 white seropositive cases and 481 controls from the US Nurses' Health Studies (NHS) and 629 white cyclic-citrullinated peptide antibody-positive cases and 623 controls from the Swedish Epidemiologic Investigation of Rheumatoid Arthritis (EIRA). A weighted genetic risk score (GRS) was created, in which the weight for each risk allele is the log of the published odds ratio (OR). Logistic regression was used to study associations with incident RA. Area under the curve (AUC) statistics were compared from a clinical-only model and clinical plus genetic model in each cohort., Results: Patients with GRS >1.25 SD of the mean had a significantly higher OR of seropositive RA in both NHS (OR=2.9, 95%CI 1.8 to 4.6) and EIRA (OR 3.4, 95% CI 2.3 to 5.0) referent to the population average. In NHS, the AUC for a clinical model was 0.57 and for a clinical plus genetic model was 0.66, and in EIRA was 0.63 and 0.75, respectively., Conclusion: The combination of 22 risk alleles into a weighted GRS significantly stratifies individuals for RA risk beyond clinical risk factors alone. Given the low incidence of RA, the clinical utility of a weighted GRS is limited in the general population.