mapMECFS: a portal to enhance data discovery across biological disciplines and collaborative sites.

BACKGROUND: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating disease which involves multiple body systems (e.g., immune, nervous, digestive, circulatory) and research domains (e.g., immunology, metabolomics, the gut microbiome, genomics, neurology). Despite several decades of research, there are no established ME/CFS biomarkers available to diagnose and treat ME/CFS. Sharing data and integrating findings across these domains is essential to advance understanding of this complex disease by revealing diagnostic biomarkers and facilitating discovery of novel effective therapies. METHODS: The National Institutes of Health funded the development of a data sharing portal to support collaborative efforts among an initial group of three funded research centers. This was subsequently expanded to include the global ME/CFS research community. Using the open-source comprehensive knowledge archive network (CKAN) framework as the base, the ME/CFS Data Management and Coordinating Center developed an online portal with metadata collection, smart search capabilities, and domain-agnostic data integration to support data findability and reusability while reducing the barriers to sustainable data sharing. RESULTS: We designed the mapMECFS data portal to facilitate data sharing and integration by allowing ME/CFS researchers to browse, share, compare, and download molecular datasets from within one data repository. At the time of publication, mapMECFS contains data curated from public data repositories, peer-reviewed publications, and current ME/CFS Research Network members. CONCLUSIONS: mapMECFS is a disease-specific data portal to improve data sharing and collaboration among ME/CFS researchers around the world. mapMECFS is accessible to the broader research community with registration. Further development is ongoing to include novel systems biology and data integration methods.

Omega-3 Fatty Acids and Genome-Wide Interaction Analyses Reveal DPP10-Pulmonary Function Association.

RATIONALE: Omega-3 polyunsaturated fatty acids (n-3 PUFAs) have anti-inflammatory properties that could benefit adults with comprised pulmonary health. OBJECTIVE: To investigate n-3 PUFA associations with spirometric measures of pulmonary function tests (PFTs) and determine underlying genetic susceptibility. METHODS: Associations of n-3 PUFA biomarkers (α-linolenic acid, eicosapentaenoic acid, docosapentaenoic acid [DPA], and docosahexaenoic acid [DHA]) were evaluated with PFTs (FEV1, FVC, and FEV1/FVC) in meta-analyses across seven cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (N = 16,134 of European or African ancestry). PFT-associated n-3 PUFAs were carried forward to genome-wide interaction analyses in the four largest cohorts (N = 11,962) and replicated in one cohort (N = 1,687). Cohort-specific results were combined using joint 2 degree-of-freedom (2df) meta-analyses of SNP associations and their interactions with n-3 PUFAs. RESULTS: DPA and DHA were positively associated with FEV1 and FVC (P < 0.025), with evidence for effect modification by smoking and by sex. Genome-wide analyses identified a novel association of rs11693320-an intronic DPP10 SNP-with FVC when incorporating an interaction with DHA, and the finding was replicated (P2df = 9.4 × 10-9 across discovery and replication cohorts). The rs11693320-A allele (frequency, ∼80%) was associated with lower FVC (PSNP = 2.1 × 10-9; ßSNP = -161.0 ml), and the association was attenuated by higher DHA levels (PSNP×DHA interaction = 2.1 × 10-7; ßSNP×DHA interaction = 36.2 ml). CONCLUSIONS: We corroborated beneficial effects of n-3 PUFAs on pulmonary function. By modeling genome-wide n-3 PUFA interactions, we identified a novel DPP10 SNP association with FVC that was not detectable in much larger studies ignoring this interaction.

Mutation of NRAS but not KRAS significantly reduces myeloma sensitivity to single-agent bortezomib therapy.

Various translocations and mutations have been identified in myeloma, and certain aberrations, such as t(4;14) and del17, are linked with disease prognosis. To investigate mutational prevalence in myeloma and associations between mutations and patient outcomes, we tested a panel of 41 known oncogenes and tumor suppressor genes in tumor samples from 133 relapsed myeloma patients participating in phase 2 or 3 clinical trials of bortezomib. DNA mutations were identified in 14 genes. BRAF as well as RAS genes were mutated in a large proportion of cases (45.9%) and these mutations were mutually exclusive. New recurrent mutations were also identified, including in the PDGFRA and JAK3 genes. NRAS mutations were associated with a significantly lower response rate to single-agent bortezomib (7% vs 53% in patients with mutant vs wild-type NRAS, P = .00116, Bonferroni-corrected P = .016), as well as shorter time to progression in bortezomib-treated patients (P = .0058, Bonferroni-corrected P = .012). However, NRAS mutation did not impact outcome in patients treated with high-dose dexamethasone. KRAS mutation did not reduce sensitivity to bortezomib or dexamethasone. These findings identify a significant clinical impact of NRAS mutation in myeloma and demonstrate a clear example of functional differences between the KRAS and NRAS oncogenes.

Two rare AKAP9 variants are associated with Alzheimer's disease in African Americans.

BACKGROUND: Less is known about the genetic basis of Alzheimer's disease (AD) in African Americans (AAs) than in non-Hispanic whites. METHODS: Whole exome sequencing (WES) was performed on seven AA AD cases. Disease association with potentially AD-related variants from WES was assessed in an AA discovery cohort of 422 cases and 394 controls. Replication was sought in an AA sample of 1037 cases and 1869 controls from the Alzheimer Disease Genetics Consortium (ADGC). RESULTS: Forty-four single nucleotide polymorphisms (SNPs) from WES passed filtering criteria and were successfully genotyped. Nominally significant (P < .05) association to AD was observed with two African-descent specific AKAP9 SNPs in tight linkage disequilibrium: rs144662445 (P = .014) and rs149979685 (P = .037). These associations were replicated in the ADGC sample (rs144662445: P = .0022, odds ratio [OR] = 2.75; rs149979685: P = .0022, OR = 3.61). CONCLUSIONS: Because AKAP9 was not previously linked to AD risk, this study indicates a potential new disease mechanism.

From Clinical Phenotype to Genotypic Modelling: Incidence and Prevalence of Recessive Dystrophic Epidermolysis Bullosa (RDEB).

BACKGROUND: Recessive dystrophic epidermolysis bullosa (RDEB) is an inherited genetic disorder characterized by recurrent and chronic open wounds with significant morbidity, impaired quality of life, and early mortality. RDEB patients demonstrate reduction or structural alteration type VII collagen (C7) owing to mutations in the gene COL7A1, the main component of anchoring fibrils (AF) necessary to maintain epidermal-dermal cohesion. While over 700 alterations in COL7A1 have been reported to cause dystrophic epidermolysis bullosa (DEB), which may be inherited in an autosomal dominant (DDEB) or autosomal recessive pattern (RDEB), the incidence and prevalence of RDEB is not well defined. To date, the widely estimated incidence (0.2-6.65 per million births) and prevalence (3.5-20.4 per million people) of RDEB has been primarily characterized by limited analyses of clinical databases or registries. METHODS: Using a genetic modelling approach, we use whole exome and genome sequencing data to estimate the allele frequency of pathogenic variants. Through the ClinVar and NCBI database of human genome variants and phenotypes, DEB Register, and analyzing premature COL7A1 termination variants we built a model to predict the pathogenicity of previously unclassified variants. We applied the model to publicly available sequences from the Exome Aggregation Consortium (ExAC) and Genome Aggregation Database (gnomAD) and identified variants which were classified as pathogenic for RDEB from which we estimate disease incidence and prevalence. RESULTS: Genetic modelling applied to the whole exome and genome sequencing data resulted in the identification of predicted RDEB pathogenic alleles, from which our estimate of the incidence of RDEB is 95 per million live births, 30 times the 3.05 per million live birth incidence estimated by the National Epidermolysis Bullosa Registry (NEBR). Using a simulation approach, we estimate a mean of approximately 3,850 patients in the US who may benefit from COL7A1-mediated treatments in the US. CONCLUSION: We conclude that genetic allele frequency estimation may enhance the underdiagnosis of rare genetic diseases generally, and RDEB specifically, which may improve incidence and prevalence estimates of patients who may benefit from treatment.

Development of a Drug-Response Modeling Framework to Identify Cell Line Derived Translational Biomarkers That Can Predict Treatment Outcome to Erlotinib or Sorafenib.

Development of drug responsive biomarkers from pre-clinical data is a critical step in drug discovery, as it enables patient stratification in clinical trial design. Such translational biomarkers can be validated in early clinical trial phases and utilized as a patient inclusion parameter in later stage trials. Here we present a study on building accurate and selective drug sensitivity models for Erlotinib or Sorafenib from pre-clinical in vitro data, followed by validation of individual models on corresponding treatment arms from patient data generated in the BATTLE clinical trial. A Partial Least Squares Regression (PLSR) based modeling framework was designed and implemented, using a special splitting strategy and canonical pathways to capture robust information for model building. Erlotinib and Sorafenib predictive models could be used to identify a sub-group of patients that respond better to the corresponding treatment, and these models are specific to the corresponding drugs. The model derived signature genes reflect each drug's known mechanism of action. Also, the models predict each drug's potential cancer indications consistent with clinical trial results from a selection of globally normalized GEO expression datasets.

Search for age-related macular degeneration risk variants in Alzheimer disease genes and pathways.

Several lines of inquiry point to overlapping molecular mechanisms between late-onset Alzheimer disease (AD) and age-related macular degeneration (AMD). We evaluated summarized results from large genome-wide association studies for AD and AMD to test the hypothesis that AD susceptibility loci are also associated with AMD. We observed association of both disorders with genes in a region of chromosome 7, including PILRA and ZCWPW1 (peak AMD SNP rs7792525, minor allele frequency [MAF] = 19%, odds ratio [OR] = 1.14, p = 2.34 × 10(-6)), and with ABCA7 (peak AMD SNP rs3752228, MAF = 0.054, OR = 1.22, p = 0.00012). Next, we evaluated association of AMD with genes in AD-related pathways identified by canonical pathway analysis of AD-associated genes. Significant associations were observed with multiple previously identified AMD risk loci and 2 novel genes: HGS (peak SNP rs8070488, MAF = 0.23, OR = 0.91, p = 7.52 × 10(-5)), which plays a role in the clathrin-mediated endocytosis signaling pathway, and TNF (peak SNP rs2071590, MAF = 0.34, OR = 0.89, p = 1.17 × 10(-5)), which is a member of the atherosclerosis signaling and the LXR/RXR activation pathways. Our results suggest that AMD and AD share genetic mechanisms.

Seven new loci associated with age-related macular degeneration.

Age-related macular degeneration (AMD) is a common cause of blindness in older individuals. To accelerate the understanding of AMD biology and help design new therapies, we executed a collaborative genome-wide association study, including >17,100 advanced AMD cases and >60,000 controls of European and Asian ancestry. We identified 19 loci associated at P < 5 × 10(-8). These loci show enrichment for genes involved in the regulation of complement activity, lipid metabolism, extracellular matrix remodeling and angiogenesis. Our results include seven loci with associations reaching P < 5 × 10(-8) for the first time, near the genes COL8A1-FILIP1L, IER3-DDR1, SLC16A8, TGFBR1, RAD51B, ADAMTS9 and B3GALTL. A genetic risk score combining SNP genotypes from all loci showed similar ability to distinguish cases and controls in all samples examined. Our findings provide new directions for biological, genetic and therapeutic studies of AMD.

A comprehensive genetic association study of Alzheimer disease in African Americans.

OBJECTIVES: To evaluate the association of genetic variation with late-onset Alzheimer disease (AD) in African Americans, including genes implicated in recent genome-wide association studies of whites. DESIGN: We analyzed a genome-wide set of 2.5 million imputed markers to evaluate the genetic basis of AD in an African American population. SUBJECTS: Five hundred thirteen well-characterized African American AD cases and 496 cognitively normal African American control subjects. SETTING: Data were collected from multiple sites as part of the Multi-Institutional Research on Alzheimer Genetic Epidemiology (MIRAGE) Study and the Henry Ford Health System as part of the Genetic and Environmental Risk Factors for Alzheimer Disease Among African Americans (GenerAAtions) Study. RESULTS: Several significant single-nucleotide polymorphisms (SNPs) were observed in the region of the apolipoprotein E gene (APOE). After adjusting for the confounding effects of APOE genotype, one of these SNPs, rs6859 in PVRL2, remained significantly associated with AD (P = .0087). Association was also observed with SNPs in CLU, PICALM, BIN1, EPHA1, MS4A, ABCA7, and CD33, although the effect direction for some SNPs and the most significant SNPs differed from findings in data sets consisting of whites. Finally, using the African American genome-wide association study data set as a discovery sample, we obtained suggestive evidence of association with SNPs for several novel candidate genes. CONCLUSIONS: Some genes contribute to AD pathogenesis in both white and African American cohorts, although it is unclear whether the causal variants are the same. A larger African American sample will be needed to confirm novel gene associations, which may be population specific.