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Retrospective observational research relies on databases that do not routinely record lines of therapy or reasons for treatment change. Standardized approaches to estimate lines of therapy were developed and evaluated in this study. A number of rules were developed, assumptions varied and macros developed to apply to large datasets. Results were investigated in an iterative process to refine line of therapy algorithms in three different cancers (lung, colorectal and gastric). Three primary factors were evaluated and included in the estimation of lines of therapy in oncology: defining a treatment regimen, addition/removal of drugs and gap periods. Algorithms and associated Statistical Analysis Software (SAS ® ) macros for line of therapy identification are provided to facilitate and standardize the use of real-world databases for oncology research.

Effective approaches for assessing mitochondrial DNA (mtDNA) variation are important to multiple scientific disciplines. Mitochondrial haplogroups characterize branch points in the phylogeny of mtDNA. Several tools exist for mitochondrial haplogroup classification. However, most require full or partial mtDNA sequence which is often cost prohibitive for studies with large sample sizes. The purpose of this study was to develop Hi-MC, a high-throughput method for mitochondrial haplogroup classification that is cost effective and applicable to large sample sizes making mitochondrial analysis more accessible in genetic studies. Using rigorous selection criteria, we defined and validated a custom panel of mtDNA single nucleotide polymorphisms that allows for accurate classification of European, African, and Native American mitochondrial haplogroups at broad resolution with minimal genotyping and cost. We demonstrate that Hi-MC performs well in samples of European, African, and Native American ancestries, and that Hi-MC performs comparably to a commonly used classifier. Implementation as a software package in R enables users to download and run the program locally, grants greater flexibility in the number of samples that can be run, and allows for easy expansion in future revisions. Hi-MC is available in the CRAN repository and the source code is freely available at https://github.com/vserch/himc., Competing Interests: The authors declare that they have no competing interests.

Objective: Pemetrexed plus carboplatin (PCb) is a frequently used first-line treatment in advanced non-small cell lung cancer (NSCLC). This study examined the characteristics and safety profile of a NSCLC population treated with PCb area under the concentration-time curve 5 (PCb5) or 6 mg/mL•min (PCb6) under real-world conditions., Research Design and Methods: A retrospective, observational, cohort study was conducted, utilizing data from the IMS Oncology US clinic-based, longitudinal, patient-level electronic medical records (EMR), including patients with NSCLC on PCb5 or PCb6 regimens initiated concomitantly on or after the diagnosis of lung cancer during 2004-2014. Patient characteristics and incidence of adverse events (AEs) were described for each cohort. Propensity scores were calculated based on baseline demographic and clinical factors. Propensity score stratification was used to further adjust for cohort differences., Results: In total, 636 NSCLC patients receiving PCb5 (37% aged ≥70 years) and 184 patients receiving PCb6 (34% aged ≥70 years) who met the inclusion criteria were identified in the EMR. Patients with more comorbidities were more likely to have received PCb5. Overall incidence rates (IRs) per 100 person-years were similar for neutropenia in both cohorts, were numerically higher for anemia (IR = 43.6 vs 101.0) and thrombocytopenia (IR = 1.5 vs 17.9), and were numerically lower for nausea (IR = 14.4 vs 9.9) in the PCb6 vs PCb5 cohort. Within the PCb6 cohort, the IR per 100 person-years was higher for neutropenia for ≥70 year-old patients (IR = 41.1) compared to <70 year-old patients (IR = 14.5). After propensity score stratification, adjusted IRs showed similar patterns., Limitations: Limitations included lack of power for AEs other than anemia, given the nature of EMR., Conclusions: Results from this real-world analysis add to existing evidence from randomized clinical trials about PCb safety profiles in the overall NSCLC population and in elderly patients. These results may guide physicians when making treatment decisions.

Common genetic risk variants for type 2 diabetes (T2D) have primarily been identified in populations of European and Asian ancestry. We tested whether the direction of association with 20 T2D risk variants generalizes across six major racial/ethnic groups in the U.S. as part of the Population Architecture using Genomics and Epidemiology Consortium (16,235 diabetes case and 46,122 control subjects of European American, African American, Hispanic, East Asian, American Indian, and Native Hawaiian ancestry). The percentage of positive (odds ratio [OR] >1 for putative risk allele) associations ranged from 69% in American Indians to 100% in European Americans. Of the nine variants where we observed significant heterogeneity of effect by racial/ethnic group (P(heterogeneity) < 0.05), eight were positively associated with risk (OR >1) in at least five groups. The marked directional consistency of association observed for most genetic variants across populations implies a shared functional common variant in each region. Fine-mapping of all loci will be required to reveal markers of risk that are important within and across populations. [ABSTRACT FROM AUTHOR]

Background: Several regions of the genome show pleiotropic associations with multiple cancers. We sought to evaluate whether 181 single-nucleotide polymorphisms previously associated with various cancers in genome-wide association studies were also associated with melanoma risk., Methods: We evaluated 2,131 melanoma cases and 20,353 controls from three studies in the Population Architecture using Genomics and Epidemiology (PAGE) study (EAGLE-BioVU, MEC, WHI) and two collaborating studies (HPFS, NHS). Overall and sex-stratified analyses were performed across studies., Results: We observed statistically significant associations with melanoma for two lung cancer SNPs in the TERT-CLPTM1L locus (Bonferroni-corrected p<2.8x10-4), replicating known pleiotropic effects at this locus. In sex-stratified analyses, we also observed a potential male-specific association between prostate cancer risk variant rs12418451 and melanoma risk (OR=1.22, p=8.0x10-4). No other variants in our study were associated with melanoma after multiple comparisons adjustment (p>2.8e-4)., Conclusions: We provide confirmatory evidence of pleiotropic associations with melanoma for two SNPs previously associated with lung cancer, and provide suggestive evidence for a male-specific association with melanoma for prostate cancer variant rs12418451. This SNP is located near TPCN2, an ion transport gene containing SNPs which have been previously associated with hair pigmentation but not melanoma risk. Previous evidence provides biological plausibility for this association, and suggests a complex interplay between ion transport, pigmentation, and melanoma risk that may vary by sex. If confirmed, these pleiotropic relationships may help elucidate shared molecular pathways between cancers and related phenotypes.

Substantial progress has been made in identifying susceptibility variants for age-related macular degeneration (AMD). The majority of research to identify genetic variants associated with AMD has focused on nuclear genetic variation. While there is some evidence that mitochondrial genetic variation contributes to AMD susceptibility, to date, these studies have been limited to populations of European descent resulting in a lack of data in diverse populations. A major goal of the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study is to describe the underlying genetic architecture of common, complex diseases across diverse populations. This present study sought to determine if mitochondrial genetic variation influences risk of AMD across diverse populations. We performed a genetic association study to investigate the contribution of mitochondrial DNA variation to AMD risk. We accessed samples from the National Health and Nutrition Examination Surveys, a U.S population-based, cross-sectional survey collected without regard to health status. AMD cases and controls were selected from the Third NHANES and NHANES 2007-2008 datasets which include non-Hispanic whites, non-Hispanic blacks, and Mexican Americans. AMD cases were defined as those > 60 years of age with early/late AMD, as determined by fundus photography. Targeted genotyping was performed for 63 mitochondrial SNPs and participants were then classified into mitochondrial haplogroups. We used logistic regression assuming a dominant genetic model adjusting for age, sex, body mass index, and smoking status (ever vs. never). Regressions and meta-analyses were performed for individual SNPs and mitochondrial haplogroups J, T, and U. We identified five SNPs associated with AMD in Mexican Americans at p < 0.05, including three located in the control region (mt16111, mt16362, and mt16319), one in MT-RNR2 (mt1736), and one in MT-ND4 (mt12007). No mitochondrial variant or haplogroup was significantly associated in non-Hispanic blacks or non- Hispanic whites in the final meta-analysis. This study provides further evidence that mitochondrial variation plays a role in susceptibility to AMD and contributes to the knowledge of the genetic architecture of AMD in Mexican Americans.

Background: Multiple primary cancers account for approximately 16% of all incident cancers in the United States. Although genome-wide association studies (GWAS) have identified many common genetic variants associated with various cancer sites, no study has examined the association of these genetic variants with risk of multiple primary cancers (MPC)., Methods: As part of the National Human Genome Research Institute (NHGRI) Population Architecture using Genomics and Epidemiology (PAGE) study, we used data from the Multiethnic Cohort (MEC) and Women's Health Initiative (WHI). Incident MPC (IMPC) cases (n = 1,385) were defined as participants diagnosed with more than one incident cancer after cohort entry. Participants diagnosed with only one incident cancer after cohort entry with follow-up equal to or longer than IMPC cases served as controls (single-index cancer controls; n = 9,626). Fixed-effects meta-analyses of unconditional logistic regression analyses were used to evaluate the associations between 188 cancer risk variants and IMPC risk. To account for multiple comparisons, we used the false-positive report probability (FPRP) to determine statistical significance., Results: A nicotine dependence-associated and lung cancer variant, CHRNA3 rs578776 [OR, 1.16; 95% confidence interval (CI), 1.05-1.26; P = 0.004], and two breast cancer variants, EMBP1 rs11249433 and TOX3 rs3803662 (OR, 1.16; 95% CI, 1.04-1.28; P = 0.005 and OR, 1.13; 95% CI, 1.03-1.23; P = 0.006), were significantly associated with risk of IMPC. The associations for rs578776 and rs11249433 remained (P < 0.05) after removing subjects who had lung or breast cancers, respectively (P ≤ 0.046). These associations did not show significant heterogeneity by smoking status (Pheterogeneity ≥ 0.53)., Conclusions: Our study has identified rs578776 and rs11249433 as risk variants for IMPC., Impact: These findings may help to identify genetic regions associated with IMPC risk., (©2014 American Association for Cancer Research.)

Purpose: Cataract is the leading cause of blindness in the world, and in the United States accounts for approximately 60% of Medicare costs related to vision. The purpose of this study was to identify genetic markers for age-related cataract through a genome-wide association study (GWAS)., Methods: In the electronic medical records and genomics (eMERGE) network, we ran an electronic phenotyping algorithm on individuals in each of five sites with electronic medical records linked to DNA biobanks. We performed a GWAS using 530,101 SNPs from the Illumina 660W-Quad in a total of 7,397 individuals (5,503 cases and 1,894 controls). We also performed an age-at-diagnosis case-only analysis., Results: We identified several statistically significant associations with age-related cataract (45 SNPs) as well as age at diagnosis (44 SNPs). The 45 SNPs associated with cataract at p<1×10(-5) are in several interesting genes, including ALDOB, MAP3K1, and MEF2C. All have potential biologic relationships with cataracts., Conclusions: This is the first genome-wide association study of age-related cataract, and several regions of interest have been identified. The eMERGE network has pioneered the exploration of genomic associations in biobanks linked to electronic health records, and this study is another example of the utility of such resources. Explorations of age-related cataract including validation and replication of the association results identified herein are needed in future studies.

Background: Both environmental and genetic factors impact type 2 diabetes (T2D). To identify such modifiers, we genotyped 15 T2D-associated variants from genome-wide association studies (GWAS) in 6,414 non-Hispanic whites, 3,073 non-Hispanic blacks, and 3,633 Mexican American participants from the National Health and Nutrition Examination Surveys (NHANES) and evaluated interactions between these variants and carbohydrate intake and fiber intake., Results: We calculated a genetic risk score (GRS) with the 15 SNPs. The odds ratio for T2D with each GRS point was 1.10 (95% CI: 1.05-1.14) for non-Hispanic whites, 1.07 (95% CI: 1.02-1.13) for non-Hispanic blacks, and 1.11 (95% CI: 1.06-1.17) for Mexican Americans. We identified two gene-carbohydrate interactions (P < 0.05) in non-Hispanic whites (with CDKAL1 rs471253 and FTO rs8050136), two in non-Hispanic blacks (with IGFBP2 rs4402960 and THADA rs7578597), and two in Mexican Americans (with NOTCH2 rs1092398 and TSPAN8-LGRS rs7961581). We found three gene-fiber interactions in non-Hispanic whites (with ADAMT59 rs4607103, CDKN2A/2B rs1801282, and FTO rs8050136), two in non-Hispanic blacks (with ADAMT59 rs4607103 and THADA rs7578597), and two in Mexican Americans (with THADA rs7578597 and TSPAN8-LGRS rs796158) at the P < 0.05 level. Interactions between the GRS and nutrients failed to reach significance in all the racial/ethnic groups., Conclusion: Our results suggest that dietary carbohydrates and fiber may modify T2D-associated variants, highlighting the importance of dietary nutrients in predicting T2D risk.

Objective: Genome-wide association studies have identified a large number of single nucleotide polymorphisms (SNPs) associated with a wide array of cancer sites. Several of these variants demonstrate associations with multiple cancers, suggesting pleiotropic effects and shared biological mechanisms across some cancers. We hypothesised that SNPs previously associated with other cancers may additionally be associated with colorectal cancer. In a large-scale study, we examined 171 SNPs previously associated with 18 different cancers for their associations with colorectal cancer., Design: We examined 13 338 colorectal cancer cases and 40 967 controls from three consortia: Population Architecture using Genomics and Epidemiology (PAGE), Genetic Epidemiology of Colorectal Cancer (GECCO), and the Colon Cancer Family Registry (CCFR). Study-specific logistic regression results, adjusted for age, sex, principal components of genetic ancestry, and/or study specific factors (as relevant) were combined using fixed-effect meta-analyses to evaluate the association between each SNP and colorectal cancer risk. A Bonferroni-corrected p value of 2.92×10(-4) was used to determine statistical significance of the associations., Results: Two correlated SNPs--rs10090154 and rs4242382--in Region 1 of chromosome 8q24, a prostate cancer susceptibility region, demonstrated statistically significant associations with colorectal cancer risk. The most significant association was observed with rs4242382 (meta-analysis OR=1.12; 95% CI 1.07 to 1.18; p=1.74×10(-5)), which also demonstrated similar associations across racial/ethnic populations and anatomical sub-sites., Conclusions: This is the first study to clearly demonstrate Region 1 of chromosome 8q24 as a susceptibility locus for colorectal cancer; thus, adding colorectal cancer to the list of cancer sites linked to this particular multicancer risk region at 8q24.

Background: Mitochondria play a critical role in the cell and have DNA independent of the nuclear genome. There is much evidence that mitochondrial DNA (mtDNA) variation plays a role in human health and disease, however, this area of investigation has lagged behind research into the role of nuclear genetic variation on complex traits and phenotypic outcomes. Phenome-wide association studies (PheWAS) investigate the association between a wide range of traits and genetic variation. To date, this approach has not been used to investigate the relationship between mtDNA variants and phenotypic variation. Herein, we describe the development of a PheWAS framework for mtDNA variants (mt-PheWAS). Using the Metabochip custom genotyping array, nuclear and mitochondrial DNA variants were genotyped in 11,519 African Americans from the Vanderbilt University biorepository, BioVU. We employed both polygenic modeling and association testing with mitochondrial single nucleotide polymorphisms (mtSNPs) to explore the relationship between mtDNA variants and a group of eight cardiovascular-related traits obtained from de-identified electronic medical records within BioVU., Results: Using polygenic modeling we found evidence for an effect of mtDNA variation on total cholesterol and type 2 diabetes (T2D). After performing comprehensive mitochondrial single SNP associations, we identified an increased number of single mtSNP associations with total cholesterol and T2D compared to the other phenotypes examined, which did not have more significantly associated SNPs than would be expected by chance. Among the mtSNPs significantly associated with T2D we identified variant mt16189, an association previously reported only in Asian and European-descent populations., Conclusions: Our replication of previous findings and identification of novel associations from this initial study suggest that our mt-PheWAS approach is robust for investigating the relationship between mitochondrial genetic variation and a range of phenotypes, providing a framework for future mt-PheWAS.

Genome-wide association studies (GWAS) have identified many variants that influence high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and/or triglycerides. However, environmental modifiers, such as smoking, of these known genotype-phenotype associations are just recently emerging in the literature. We have tested for interactions between smoking and 49 GWAS-identified variants in over 41,000 racially/ethnically diverse samples with lipid levels from the Population Architecture Using Genomics and Epidemiology (PAGE) study. Despite their biological plausibility, we were unable to detect significant SNP × smoking interactions.

Numerous common genetic variants that influence plasma high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), and triglyceride distributions have been identified via genome-wide association studies (GWAS). However, whether or not these associations are age-dependent has largely been overlooked. We conducted an association study and meta-analysis in more than 22,000 European Americans between 49 previously identified GWAS variants and the three lipid traits, stratified by age (males: <50 or ≥50 years of age; females: pre- or postmenopausal). For each variant, a test of heterogeneity was performed between the two age strata and significant Phet values were used as evidence of age-specific genetic effects. We identified seven associations in females and eight in males that displayed suggestive heterogeneity by age (Phet < 0.05). The association between rs174547 (FADS1) and LDL-C in males displayed the most evidence for heterogeneity between age groups (Phet = 1.74E-03, I(2) = 89.8), with a significant association in older males (P = 1.39E-06) but not younger males (P = 0.99). However, none of the suggestive modifying effects survived adjustment for multiple testing, highlighting the challenges of identifying modifiers of modest SNP-trait associations despite large sample sizes., (© 2013 John Wiley & Sons Ltd/University College London.)

Common obesity risk variants have been associated with macronutrient intake; however, these associations' generalizability across populations has not been demonstrated. We investigated the associations between 6 obesity risk variants in (or near) the NEGR1, TMEM18, BDNF, FTO, MC4R, and KCTD15 genes and macronutrient intake (carbohydrate, protein, ethanol, and fat) in 3 Population Architecture using Genomics and Epidemiology (PAGE) studies: the Multiethnic Cohort Study (1993-2006) (n = 19,529), the Atherosclerosis Risk in Communities Study (1987-1989) (n = 11,114), and the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) Study, which accesses data from the Third National Health and Nutrition Examination Survey (1991-1994) (n = 6,347). We used linear regression, with adjustment for age, sex, and ethnicity, to estimate the associations between obesity risk genotypes and macronutrient intake. A fixed-effects meta-analysis model showed that the FTO rs8050136 A allele (n = 36,973) was positively associated with percentage of calories derived from fat (βmeta = 0.2244 (standard error, 0.0548); P = 4 × 10(-5)) and inversely associated with percentage of calories derived from carbohydrate (βmeta = -0.2796 (standard error, 0.0709); P = 8 × 10(-5)). In the Multiethnic Cohort Study, percentage of calories from fat assessed at baseline was a partial mediator of the rs8050136 effect on body mass index (weight (kg)/height (m)(2)) obtained at 10 years of follow-up (mediation of effect = 0.0823 kg/m(2), 95% confidence interval: 0.0559, 0.1128). Our data provide additional evidence that the association of FTO with obesity is partially mediated by dietary intake.

Genetic association studies thus far have used detailed diagnoses of alcoholism to identify loci associated with risk. This proof-of-concept analysis examined whether population data of lifetime heaviest alcohol consumption may be used to identify genetic loci that modulate risk. We conducted a genetic association study in European Americans between variants in approximately 2100 genes and alcohol consumption as part of the Candidate gene Association Resource project. We defined cases as individuals with a history of drinking 5 or more drinks per day almost every day of the week and controls as current light drinkers (1-5 drinks per week). We cross-validated identified single nucleotide polymorphisms in a meta-analysis of 2 cohorts of unrelated individuals--Atherosclerosis Risk in Communities (ARIC) and Cardiovascular Health Study (CHS)--and in a separate cohort of related individuals--Framingham Heart Study (FHS). The most significant variant in the meta-analysis of ARIC and CHS was rs6933598 in methylenetetrahydrofolate dehydrogenase (P = 7.46 × 10(-05)) with a P value in FHS of 0.042. The top variants in FHS were rs12249562 in cubulin (P = 3.03 × 10(-05)) and rs9839267 near cholecystokinin (P = 3.05 × 10(-05)) with a P value of 0.019 for rs9839267 in CHS. We have here shown feasibility in evaluating lifetime incidence of heavy alcohol drinking from population-based studies for the purpose of conducting genetic association analyses.

To date, most genetic association studies of tobacco use have been conducted in European American subjects using the phenotype of smoking quantity (cigarettes per day). However, smoking quantity is a very imprecise measure of exposure to tobacco smoke constituents. Analyses of alternate phenotypes and populations may improve our understanding of tobacco addiction genetics. Cotinine is the major metabolite of nicotine, and measuring serum cotinine levels in smokers provides a more objective measure of nicotine dose than smoking quantity. Previous genetic association studies of serum cotinine have focused on individual genes. We conducted a genetic association study of the biomarker in African American (N=365) and European American (N=315) subjects from the Coronary Artery Risk Development in Young Adults study using a chip containing densely-spaced tag SNPs in ∼2100 genes. We found that rs11187065, located in the non-coding region (intron 1) of insulin-degrading enzyme (IDE), was the most strongly associated SNP (p=8.91 × 10(-6)) in the African American cohort, whereas rs11763963, located on chromosome 7 outside of a gene transcript, was the most strongly associated SNP in European Americans (p=1.53 × 10(-6)). We then evaluated how the top variant association in each population performed in the other group. We found that the association of rs11187065 in IDE was also associated with the phenotype in European Americans (p=0.044). Our top SNP association in European Americans, rs11763963 was non-polymorphic in our African American sample. It has been previously shown that psychostimulant self-administration is reduced in animals with lower insulin because of interference with dopamine transmission in the brain reward centers. Our finding provides a platform for further investigation of this, or additional mechanisms, involving the relationship between insulin and self-administered nicotine dose.

To date, most genetic association analyses of smoking behaviors have been conducted in populations of European ancestry and many of these studies focused on the phenotype that measures smoking quantity, that is, cigarettes per day. Additional association studies in diverse populations with different linkage disequilibrium patterns and an alternate phenotype, such as total tobacco exposure which accounts for intermittent periods of smoking cessation within a larger smoking period as measured in large cardiovascular risk studies, can aid the search for variants relevant to smoking behavior. For these reasons, we undertook an association analysis by using a genotyping array that includes 2,100 genes to analyze smoking persistence in unrelated African American participants from the Atherosclerosis Risk in Communities study. A locus located approximately 4 kb downstream from the 3'-UTR of the brain-derived neurotrophic factor (BDNF) significantly influenced smoking persistence. In addition, independent variants rs12915366 and rs12914385 in the cluster of genes encoding nicotinic acetylcholine receptor subunits (CHRNA5-CHRNA3-CHRNB4) on 15q25.1 were also associated with the phenotype in this sample of African American subjects. To our knowledge, this is the first study to more extensively evaluate the genome in the African American population, as a limited number of previous studies of smoking behavior in this population included evaluations of only single genomic regions.

Rationale: Obstructive sleep apnea (OSA) is hypothesized to be influenced by genes within pathways involved with obesity, craniofacial development, inflammation, and ventilatory control., Objectives: We conducted the first candidate gene study of OSA using family data from European Americans and African Americans, selecting biologically plausible genes from within these pathways., Methods: A total of 1,080 single nucleotide polymorphisms (SNPs) were genotyped in 729 African Americans and 505 SNPs were genotyped in 694 European Americans. Coding for SNPs additively, association testing on the apnea-hypopnea index (AHI) as a continuous trait, and OSA as a dichotomous trait (AHI ≥15) was conducted using methods that account for familial correlations in models adjusted for age, age-squared, and sex, with and without body mass index., Measurements and Main Results: In European Americans, variants within C-reactive protein (CRP) and glial cell line-derived neurotrophic factor (GDNF) were associated with AHI (CRP: β = 4.6; SE = 1.1; P = 0.0000402) (GDNF: β = 4.3; SE = 1; P = 0.0000201) and with the dichotomous OSA trait (CRP: odds ratio = 2.4; 95% confidence interval, 1.5-3.9; P = 0.000170) (GDNF: odds ratio = 2; 95% confidence interval, 1.4-2.89; P = 0.0000433). In African Americans, rs9526240 within serotonin receptor 2a (HTR2A: odds ratio = 2.1; 95% confidence interval, 1.5-2.9; P = 0.00005233) was associated with OSA., Conclusions: This candidate gene analysis identified the potential role of genes operating through intermediate disease pathways to influence sleep apnea phenotypes, providing a framework for focusing future replication studies.

Metabolic syndrome, by definition, is the manifestation of multiple, correlated metabolic impairments. It is known to have both strong environmental and genetic contributions. However, isolating genetic variants predisposing to such a complex trait has limitations. Using pedigree data, when available, may well lead to increased ability to detect variants associated with such complex traits. The ability to incorporate multiple correlated traits into a joint analysis may also allow increased detection of associated genes. Therefore, to demonstrate the utility of both univariate and multivariate family-based association analysis and to identify possible genetic variants associated with metabolic syndrome, we performed a scan of the Affymetrix 50 k Human Gene Panel data using 1) each of the traits comprising metabolic syndrome: triglycerides, high-density lipoprotein, systolic blood pressure, diastolic blood pressure, blood glucose, and body mass index, and 2) a composite trait including all of the above, jointly. Two single-nucleotide polymorphisms within the cholesterol ester transfer protein (CETP) gene remained significant even after correcting for multiple testing in both the univariate (p < 5 x 10-7) and multivariate (p < 5 x 10-9) association analysis. Three genes met significance for multiple traits after correction for multiple testing in the univariate analysis, while five genes remained significant in the multivariate association. We conclude that while both univariate and multivariate family-based association analysis can identify genes of interest, our multivariate approach is less affected by multiple testing correction and yields more significant results.

Background: By 2020, obstructive sleep apnea (OSA), a prevalent respiratory disorder, had affected 26.6–43.2% of males and 8.7–27.8% of females worldwide. OSA is associated with conditions such as hypertension, diabetes, and tumor progression; however, the precise underlying pathways remain elusive. This study aims to identify genetic markers and molecular mechanisms of OSA to improve understanding and treatment strategies. Methods: The GSE135917 dataset related to OSA was obtained from the GEO database. Differentially expressed genes (DEGs) were subsequently identified. Weighted gene co-expression network analysis (WGCNA) was conducted to pinpoint disease-associated genes. The intersection of these data enabled the identification of potential diagnostic DEGs. Further analyses included Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment studies, exploration of protein–protein interactions based on these genes, and an examination of immune infiltration. Mendelian randomization was employed to validate core genes against the Genome-Wide Association Study database. Results: A total of 194 DEGs were identified in this study. WGCNA network analysis highlighted 2,502 DEGs associated with OSA. By intersecting these datasets, 53 diagnostic DEGs primarily involved in metabolic pathways were identified. Significant alterations were observed in immune cell populations, including memory B cells, plasma cells, naive CD4 T cells, M0 macrophages, and activated dendritic cells. CETN3, EEF1E1, PMM2, GTF2A2, and RRM2 emerged as hub genes implicated in the pathogenesis. A line graph model provides diagnostic insights. Mendelian randomization analysis confirmed a causal link between CETN3 and GTF2A2 with OSA. Conclusion: Through WGCNA, this analysis uncovered significant genetic foundations of OSA, identifying 2,502 DEGs and 194 genes associated with the disorder. Among these, CETN3 and GTF2A2 were found to have causal relationships with OSA. [ABSTRACT FROM AUTHOR]

Objective: The concept of lines of therapy (LOT) in cancer treatment is often considered for decision making in tumor boards and clinical management, but lacks a common definition across medical specialties. The complexity and heterogeneity of malignancies and treatment modalities contribute to an inconsistent understanding of LOT among physicians. This study assesses the heterogeneity of understandings of the LOT concept, its major dimensions, and criteria from the perspective of physicians of different specialties with an oncological focus in Germany. Semi-structured expert interviews with nine physicians were conducted and evaluated using qualitative content analysis. Results: Most interviewees agreed that there is no single definition for LOT and found it difficult to explicate their understanding. A majority of experts stated that they had already encountered misunderstandings with colleagues regarding LOT and that they had problems with deciphering LOT from the medical records of their patients. Disagreement emerged about the roles of the following within the LOT concept: maintenance therapy, treatment intention, different therapy modalities, changing pharmaceutical agents, and therapy breaks. Respondents predominantly considered the same criteria as decisive for the definition of LOT as for a change in LOT (e.g., the occurrence of a progression event or tumor recurrence). [ABSTRACT FROM AUTHOR]

Background: Immune checkpoint inhibitor (ICI) treatment has been linked to a variety of immune-related adverse events (irAEs), which can affect any organ system. The incidence and risk factors of irAEs have not been adequately evaluated among older adults with NSCLC. Methods: A cohort study was conducted using 1999–2019 SEER-Medicare data among beneficiaries aged ≥65 years with a diagnosis of NSCLC who received nivolumab, pembrolizumab, or atezolizumab. Incident irAEs were identified post-ICI initiation. Demographic, cancer-related characteristics, and clinical history risk factors of irAEs were evaluated with competing events considered. Results: A total of 8175 older NSCLC patients were included (with 46.8% experiencing irAEs). Pneumonitis (16.5%), hypothyroidism (10.5%), arrhythmia (11.18%), and acute kidney injury (AKI) (5.8%) were the most common irAEs. The median time to first irAE was 82days (IQR: 29–182days). The earliest onset of irAE occurrence was for hematologic irAEs, while the latest were gastrointestinal, dermatologic, and musculoskeletal irAEs. Fine–Gray regression modeling revealed significantly greater hazards of irAE occurrence in patients who received pembrolizumab at index, did not have CNS metastases, had a history of autoimmune disorder, and had chemotherapy in combination with ICI. Race, socioeconomic status, previous radiation therapy, and comorbidity burden were found to be associated with the occurrence of certain type of irAEs. Conclusion: A significant proportion of older patients with NSCLC develop an irAE after receiving ICI treatment. Factors related to cancer and treatment as well as demographics contribute to the increased risk of irAEs. Close monitoring and prediction of irAE among older patients receiving ICI is warranted. [ABSTRACT FROM AUTHOR]

Metabolic syndrome (MetS) is a cluster of cardiometabolic risk factors that includes central obesity, hyperglycemia, hypertension, and dyslipidemias and whose inter-related occurrence may increase the odds of developing type 2 diabetes and cardiovascular diseases. MetS has become one of the most studied conditions, nevertheless, due to its complex etiology, this has not been fully elucidated. Recent evidence describes that both genetic and environmental factors play an important role on its development. With the advent of genomic-wide association studies, single nucleotide polymorphisms (SNPs) have gained special importance. In this review, we present an update of the genetics surrounding MetS as a single entity as well as its corresponding risk factors, considering SNPs and gene–diet interactions related to cardiometabolic markers. In this study, we focus on the conceptual aspects, diagnostic criteria, as well as the role of genetics, particularly on SNPs and polygenic risk scores (PRS) for interindividual analysis. In addition, this review highlights future perspectives of personalized nutrition with regard to the approach of MetS and how individualized multiomics approaches could improve the current outlook. [ABSTRACT FROM AUTHOR]

Background: Trastuzumab in combination with chemotherapy is the standard first-line (1L) treatment for HER2+ metastatic gastric cancer (mGC) in the USA. Objective: This study characterizes the real-world treatment patterns, healthcare resource use (HRU), and costs in patients with HER2+ mGC post-1L trastuzumab before approval of fam-trastuzumab deruxtecan-nxki. Patients and methods: This retrospective study used the IQVIA PharMetrics® Plus Database (October 2014–September 2019) to identify adults with HER2+ mGC who discontinued trastuzumab-based regimens in 1L. Patient characteristics, second-line (2L) treatment patterns, and treatment duration were summarized. HRU and costs before and after discontinuation of 1L trastuzumab-based regimens as well as during 2L treatment were described. Results: Of the 190 HER2+mGC patients who discontinued 1L trastuzumab-based regimens, 136 (71.58%) initiated 2L treatments. Trastuzumab-based regimens were the most common in 2L (50.74%), followed by ramucirumab + paclitaxel (19.85%). The median time to 2L discontinuation was 2.37 months. During a mean follow-up of 9.8 months, mean per-patient-per-month (PPPM) healthcare costs post-1L trastuzumab-based regimens were higher in patients receiving 2L treatment than those without subsequent treatment (US$25,178 vs. US$14,812). The mean PPPM cost during 2L treatment was US$30,838, primarily driven by outpatient infusion costs (US$22,262). Conclusions: The short duration of 2L treatment observed in this study is consistent with a lack of effective treatments post-1L trastuzumab prior to 2020. Re-use of trastuzumab treatment was common despite its limited efficacy and high treatment cost. The findings highlight the unmet medical needs and substantial burden faced by patients with HER2 +mGC previously treated with trastuzumab. [ABSTRACT FROM AUTHOR]

The importance of chemoreflex function for cardiovascular health is increasingly recognized in clinical practice. The physiological function of the chemoreflex is to constantly adjust ventilation and circulatory control to match respiratory gases to metabolism. This is achieved in a highly integrated fashion with the baroreflex and the ergoreflex. The functionality of chemoreceptors is altered in cardiovascular diseases, causing unstable ventilation and apnoeas and promoting sympathovagal imbalance, and it is associated with arrhythmias and fatal cardiorespiratory events. In the last few years, opportunities to desensitize hyperactive chemoreceptors have emerged as potential options for treatment of hypertension and heart failure. This review summarizes up to date evidence of chemoreflex physiology/pathophysiology, highlighting the clinical significance of chemoreflex dysfunction, and lists the latest proof of concept studies based on modulation of the chemoreflex as a novel target in cardiovascular diseases. [ABSTRACT FROM AUTHOR]

Objective: To evaluate how pediatric indications for tonsillectomy or adenotonsillectomy relate to gender, race/ethnicity, and age. Methods: Included consecutive pediatric patients who underwent tonsillectomy or adenotonsillectomy from a single tertiary academic institution between 2012 and 2019. Logistic regression analysis was used to measure association between the indication for tonsillectomy and the demographic variables gender, race/ethnicity, and age. Results: Of the 1106 children included in this study, 53% were male and 47% were female. Half of the children were White, 40% were African American, 6% were Hispanic and 4% were other. The most common indication for surgery was upper airway obstruction alone (66%), followed by obstruction and infection (22%), and recurrent infections (12%). We found that male gender (OR 1.59, 95% CI 1.24–2.04), African American race (OR 2.76, 95% CI 2.08–3.65), and younger age were associated with greater odds of presenting with upper airway obstruction as the indication for tonsillectomy. Conversely, male gender (OR 0.63, 95% CI 0.44–0.92), African American race (OR 0.4, 95% CI 0.26–0.61), and younger age were associated with lower odds of presenting with recurrent infection as the indication for tonsillectomy. Conclusions: Male gender, African American race, and young age are risk factors for tonsillar surgery due to airway obstruction. Female gender, White race, and older age are risk factors for tonsillar surgery due to recurrent throat infections. Level of Evidence: 3 [ABSTRACT FROM AUTHOR]

Genetic association studies of many heritable traits resulting from physiological testing often have modest sample sizes due to the cost and burden of the required phenotyping. This reduces statistical power and limits discovery of multiple genetic associations. We present a strategy to leverage pleiotropy between traits to both discover new loci and to provide mechanistic hypotheses of the underlying pathophysiology. Specifically, we combine a colocalization test with a locus-level test of pleiotropy. In simulations, we show that this approach is highly selective for identifying true pleiotropy driven by the same causative variant, thereby improves the chance to replicate the associations in underpowered validation cohorts and leads to higher interpretability. Here, as an exemplar, we use Obstructive Sleep Apnea (OSA), a common disorder diagnosed using overnight multi-channel physiological testing. We leverage pleiotropy with relevant cellular and cardio-metabolic phenotypes and gene expression traits to map new risk loci in an underpowered OSA GWAS. We identify several pleiotropic loci harboring suggestive associations to OSA and genome-wide significant associations to other traits, and show that their OSA association replicates in independent cohorts of diverse ancestries. By investigating pleiotropic loci, our strategy allows proposing new hypotheses about OSA pathobiology across many physiological layers. For example, we identify and replicate the pleiotropy across the plateletcrit, OSA and an eQTL of DNA primase subunit 1 (PRIM1) in immune cells. We find suggestive links between OSA, a measure of lung function (FEV1/FVC), and an eQTL of matrix metallopeptidase 15 (MMP15) in lung tissue. We also link a previously known genome-wide significant peak for OSA in the hexokinase 1 (HK1) locus to hematocrit and other red blood cell related traits. Thus, the analysis of pleiotropic associations has the potential to assemble diverse phenotypes into a chain of mechanistic hypotheses that provide insight into the pathogenesis of complex human diseases. Author summary: Large genetic studies with hundreds of thousands of patients have been successful at finding genetic variants that associate with disease traits in humans. However, smaller-scale studies can often have inadequate power to discover new genetic associations. Here, we use a small genetic study of Obstructive Sleep Apnea (OSA), to introduce a strategy that both helps find genetic associations and proposes biological hypotheses for the mechanisms behind those associations. To achieve this, we use large genetic studies carried out on traits that are related to OSA, and look for genetic variants that affect both OSA in our small study and the trait in question in the large study. By linking two or more traits at select loci, we were able to, among other results, find a locus that affects the expression of a gene in immune cells (DNA primase subunit 1), a marker of thrombotic and inflammatory processes (plateletcrit) and OSA. This results in a novel genetic association to OSA and a corresponding biological hypothesis behind its effect on OSA. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is the most common neurodegenerative disorder in humans and presents a major health problem throughout the world. The etiology of AD is complex, and many factors are implicated, including mitochondria. Mitochondrial alteration has been proposed as a possible cause of AD. Therefore, several studies have focused on finding an association between inherited mitochondrial DNA variants and AD onset. Methods: In this study, we looked, for the first time, for a potential association between mitochondrial haplogroups or polymorphisms and AD in the Tunisian population. We also evaluated the distribution of the major genetic risk factor for AD, the apolipoprotein E epsilon 4 (APOE ε4), in this population. In total, 159 single-nucleotide polymorphisms (SNPs) of mitochondrial DNA haplogroups were genotyped in 254 individuals (58 patients and 196 controls). An additional genotyping of APOE ε4 was performed. Results: No significant association between mitochondrial haplogroups and AD was found. However, two individual SNPs, A5656G (p = 0.03821, OR = 10.46) and A13759G (p = 0.03719, OR = 10.78), showed a significant association with AD. APOE 4 was confirmed as a risk factor for AD (p = 0.000014). Conclusion: Our findings may confirm the absence of a relation between mitochondrial haplogroups and AD and support the possible involvement of some inherited variants in the pathogenicity of AD. [ABSTRACT FROM AUTHOR]

Background: The researches on the associations between different candidate genes and obstructive sleep apnea (OSA) are inconsistent. Here, we performed a comprehensive qualitative and quantitative analysis to estimate the contribution of variants from candidate genes to the risk of OSA. Methods: Qualitative analysis was conducted to find the relationships for all included genes. Then, quantitative analysis of both allele models and genotype models was applied to evaluate the risk variants for OSA. Furthermore, a similar analysis was performed in different ethnic groups. Results: We included 152 publications containing 75 genes for qualitative analysis. Among them, we included 93 articles containing 28 variants from 16 genes for quantitative analysis. Through allele models, we found 10 risk variants for OSA (rs1801133 of MTHFR, ɛ4 of ApoE, −1438G/A of 5‐HT2A, −308G/A of TNF‐α, Pro1019Pro of LEPR, rs1130864 and rs2794521 of CRP, D/I of ACE, LPR and VNTR of 5‐HTT) with the ORs of 1.21–2.07 in global population. We found that the variant of ɛ2 of ApoE could uniquely decrease the risk of OSA in the East Asian subgroup, while the other 6 variants, including ɛ4 in ApoE, −308G/A in TNF‐α, Pro1019Pro in LEPR, D/I in ACE, LPR and VNTR in 5‐HTT, could increase the risk of OSA. As for the European subpopulation, we only found that −308G/A in TNF‐α could increase the risk for OSA. Conclusions: Eleven variants from the candidate genes are associated with the risk of OSA, which also show ethnicity differences in East Asian and European subgroups. [ABSTRACT FROM AUTHOR]

Background: Mitochondrial haplogroup assignment is an important tool for forensics and evolutionary genetics. African populations are known to display a high diversity of mitochondrial haplogroups. In this research we explored mitochondrial haplogroup assignment in African populations using commonly used genome-wide SNP arrays. Results: We show that, from eight commonly used SNP arrays, two SNP arrays outperform the other arrays when it comes to the correct assignment of African mitochondrial haplogroups. One array enables the recognition of 81% of the African mitochondrial haplogroups from our compiled dataset of full mitochondrial sequences. Other SNP arrays were able to assign 4–62% of the African mitochondrial haplogroups present in our dataset. We also assessed the performance of available software for assigning mitochondrial haplogroups from SNP array data. Conclusions: These results provide the first cross-checked quantification of mitochondrial haplogroup assignment performance from SNP array data. Mitochondrial haplogroup frequencies inferred from most common SNP arrays used for human population analysis should be considered with caution. [ABSTRACT FROM AUTHOR]

Background: Variation in mitochondrial DNA (mtDNA) identified by genotyping microarrays or by sequencing only the hypervariable regions of the genome may be insufficient to reliably assign mitochondrial genomes to phylogenetic lineages or haplogroups. This lack of resolution can limit functional and clinical interpretation of a substantial body of existing mtDNA data. To address this limitation, we developed and evaluated a large, curated reference alignment of complete mtDNA sequences as part of a pipeline for imputing missing mtDNA single nucleotide variants (mtSNVs). We call our reference alignment and pipeline MitoImpute. Results: We aligned the sequences of 36,960 complete human mitochondrial genomes downloaded from GenBank, filtered and controlled for quality. These sequences were reformatted for use in imputation software, IMPUTE2. We assessed the imputation accuracy of MitoImpute by measuring haplogroup and genotype concordance in data from the 1000 Genomes Project and the Alzheimer's Disease Neuroimaging Initiative (ADNI). The mean improvement of haplogroup assignment in the 1000 Genomes samples was 42.7% (Matthew's correlation coefficient = 0.64). In the ADNI cohort, we imputed missing single nucleotide variants. Conclusion: These results show that our reference alignment and panel can be used to impute missing mtSNVs in existing data obtained from using microarrays, thereby broadening the scope of functional and clinical investigation of mtDNA. This improvement may be particularly useful in studies where participants have been recruited over time and mtDNA data obtained using different methods, enabling better integration of early data collected using less accurate methods with more recent sequence data. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of the present study was to determine the relationship between infertility and the polymorphisms of mitochondrial NADH dehydrogenase subunit 4 (MTND4) by spermatozoa analysis in fertile and subfertile men. Methods: Samples were divided into 68 subfertile men (case group) and 44 fertile men (control group). After semen analysis, samples were purified. The whole genome was extracted using a QIAamp DNA Mini Kit and the mitochondrial DNA was amplified by using the REPLI-g Mitochondrial DNA Kit. Polymerase chain reaction (PCR) was used to amplify the MT-ND4 gene. Then, samples were purified and sequenced using the Sanger method. Results: Twenty-five single-nucleotide polymorphisms (SNPs) were identified in the MTND4 gene. The genotype frequencies of the study population showed a statistically significant association between rs2853495 G>A (Gly320Gly) and male infertility (P = 0.0351). Similarly, the allele frequency test showed that rs2853495 G>A (Gly320Gly) and rs869096886 A>G (Leu164Leu) were significantly associated with male infertility (adjusted OR = 2.616, 95% CI = 1.374–4.983, P = 0.002; adjusted OR = 2.237, 95% CI = 1.245–4.017, P = 0.007, respectively). Conclusion: In conclusion, our findings suggested that male infertility was correlated with rs2853495 and rs869096886 SNPs in MTND4. [ABSTRACT FROM AUTHOR]

Assumptions are made about the genetic model of single nucleotide polymorphisms (SNPs) when choosing a traditional genetic encoding: additive, dominant, and recessive. Furthermore, SNPs across the genome are unlikely to demonstrate identical genetic models. However, running SNP-SNP interaction analyses with every combination of encodings raises the multiple testing burden. Here, we present a novel and flexible encoding for genetic interactions, the elastic data-driven genetic encoding (EDGE), in which SNPs are assigned a heterozygous value based on the genetic model they demonstrate in a dataset prior to interaction testing. We assessed the power of EDGE to detect genetic interactions using 29 combinations of simulated genetic models and found it outperformed the traditional encoding methods across 10%, 30%, and 50% minor allele frequencies (MAFs). Further, EDGE maintained a low false-positive rate, while additive and dominant encodings demonstrated inflation. We evaluated EDGE and the traditional encodings with genetic data from the Electronic Medical Records and Genomics (eMERGE) Network for five phenotypes: age-related macular degeneration (AMD), age-related cataract, glaucoma, type 2 diabetes (T2D), and resistant hypertension. A multi-encoding genome-wide association study (GWAS) for each phenotype was performed using the traditional encodings, and the top results of the multi-encoding GWAS were considered for SNP-SNP interaction using the traditional encodings and EDGE. EDGE identified a novel SNP-SNP interaction for age-related cataract that no other method identified: rs7787286 (MAF: 0.041; intergenic region of chromosome 7)–rs4695885 (MAF: 0.34; intergenic region of chromosome 4) with a Bonferroni LRT p of 0.018. A SNP-SNP interaction was found in data from the UK Biobank within 25 kb of these SNPs using the recessive encoding: rs60374751 (MAF: 0.030) and rs6843594 (MAF: 0.34) (Bonferroni LRT p: 0.026). We recommend using EDGE to flexibly detect interactions between SNPs exhibiting diverse action. Author summary: Although traditional genetic encodings are widely implemented in genetics research, including in genome-wide association studies (GWAS) and epistasis, each method makes assumptions that may not reflect the underlying etiology. Here, we introduce a novel encoding method that estimates and assigns an individualized data-driven encoding for each single nucleotide polymorphism (SNP): the elastic data-driven genetic encoding (EDGE). With simulations, we demonstrate that this novel method is more accurate and robust than traditional encoding methods in estimating heterozygous genotype values, reducing the type I error, and detecting SNP-SNP interactions. We further applied the traditional encodings and EDGE to biomedical data from the Electronic Medical Records and Genomics (eMERGE) Network for five phenotypes, and EDGE identified a novel interaction for age-related cataract not detected by traditional methods, which replicated in data from the UK Biobank. EDGE provides an alternative approach to understanding and modeling diverse SNP models and is recommended for studying complex genetics in common human phenotypes. [ABSTRACT FROM AUTHOR]

While the Arabian population has a high prevalence of metabolic disorders, it has not been included in global studies that identify genetic risk loci for metabolic traits. Determining the transferability of such largely Euro-centric established risk loci is essential to transfer the research tools/resources, and drug targets generated by global studies to a broad range of ethnic populations. Further, consideration of populations such as Arabs, that are characterized by consanguinity and a high level of inbreeding, can lead to identification of novel risk loci. We imputed published GWAS data from two Kuwaiti Arab cohorts (n = 1434 and 1298) to the 1000 Genomes Project haplotypes and performed meta-analysis for associations with 13 metabolic traits. We compared the observed association signals with those established for metabolic traits. Our study highlighted 70 variants from 9 different genes, some of which have established links to metabolic disorders. By relaxing the genome-wide significance threshold, we identified 'novel' risk variants from 11 genes for metabolic traits. Many novel risk variant association signals were observed at or borderline to genome-wide significance. Furthermore, 349 previously established variants from 187 genes were validated in our study. Pleiotropic effect of risk variants on multiple metabolic traits were observed. Fine-mapping illuminated rs7838666/CSMD1 rs1864163/CETP and rs112861901/[INTS10,LPL] as candidate causal variants influencing fasting plasma glucose and high-density lipoprotein levels. Computational functional analysis identified a variety of gene regulatory signals around several variants. This study enlarges the population ancestry diversity of available GWAS and elucidates new variants in an ethnic group burdened with metabolic disorders. [ABSTRACT FROM AUTHOR]

There is increasing evidence that pleiotropy, the association of multiple traits with the same genetic variants/loci, is a very common phenomenon. Cross-phenotype association tests are often used to jointly analyze multiple traits from a genome-wide association study (GWAS). The underlying methods, however, are often designed to test the global null hypothesis that there is no association of a genetic variant with any of the traits, the rejection of which does not implicate pleiotropy. In this article, we propose a new statistical approach, PLACO, for specifically detecting pleiotropic loci between two traits by considering an underlying composite null hypothesis that a variant is associated with none or only one of the traits. We propose testing the null hypothesis based on the product of the Z-statistics of the genetic variants across two studies and derive a null distribution of the test statistic in the form of a mixture distribution that allows for fractions of variants to be associated with none or only one of the traits. We borrow approaches from the statistical literature on mediation analysis that allow asymptotic approximation of the null distribution avoiding estimation of nuisance parameters related to mixture proportions and variance components. Simulation studies demonstrate that the proposed method can maintain type I error and can achieve major power gain over alternative simpler methods that are typically used for testing pleiotropy. PLACO allows correlation in summary statistics between studies that may arise due to sharing of controls between disease traits. Application of PLACO to publicly available summary data from two large case-control GWAS of Type 2 Diabetes and of Prostate Cancer implicated a number of novel shared genetic regions: 3q23 (ZBTB38), 6q25.3 (RGS17), 9p22.1 (HAUS6), 9p13.3 (UBAP2), 11p11.2 (RAPSN), 14q12 (AKAP6), 15q15 (KNL1) and 18q23 (ZNF236). Author summary: We propose a new approach PLACO that uses aggregate-level genotype-phenotype association statistics—commonly referred to as GWAS summary statistics—to identify genetic variants that influence risk of two traits or diseases. It allows correlation in summary statistics between studies that may arise due to sharing of controls between disease traits. We demonstrate that PLACO can achieve major power gain over alternative methods that are typically used. We applied PLACO to Type 2 Diabetes and Prostate Cancer summary data from two large case-control studies. Many previous studies have reported an inverse association of these two chronic diseases suggesting shared risk factors; however, shared genetic mechanisms underlying this association is poorly understood. PLACO identified a number of novel shared genetic regions that are not detected by individual trait analysis. Many of the loci implicated by PLACO increase risk for one disease while decreasing risk for the other. PLACO can similarly be used on other traits to shed light on shared genetic risk factors. [ABSTRACT FROM AUTHOR]

A growing number of genetic loci have been shown to influence individual predisposition to type 2 diabetes (T2D). Despite longstanding interest in understanding whether nonlinear interactions between these risk variants additionally influence T2D risk, the ability to detect significant gene-gene interaction (GGI) effects has been limited to date. To increase power to detect GGI effects, we combined recent advances in the fine-mapping of causal T2D risk variants with the increased sample size available within UK Biobank (375,736 unrelated European participants, including 16,430 with T2D). In addition to conventional single variant-based analysis, we used a complementary polygenic score-based approach, which included partitioned T2D risk scores that capture biological processes relevant to T2D pathophysiology. Nevertheless, we found no evidence in support of GGI effects influencing T2D risk. The current study was powered to detect interactions between common variants with odds ratios >1.2, so these findings place limits on the contribution of GGIs to the overall heritability of T2D. [ABSTRACT FROM AUTHOR]

Objective: This study investigated survival in selected Chinese patients with advanced lung adenocarcinoma who received initial chemotherapy with pemetrexed. We also explored the relationship between genetic biomarkers and pemetrexed efficacy. Methods: We retrospectively collected patients (n = 1,047) enrolled in the Chinese Patient Assistance Program from multiple centers who received pemetrexed alone or combined with platinum as initial chemotherapy and continued pemetrexed maintenance therapy for advanced lung adenocarcinoma from November 2014 to June 2017. The outcomes were duration of treatment (DOT) and overall survival (OS). Clinical features were analyzed for their influence on the treatment effect and prognosis. Next-generation sequencing (NGS) was performed to identify genetic biomarkers associated with the efficacy of pemetrexed. Results: The median DOT was 9.1 months (95% CI: 8.5–9.8), and the median OS was 26.2 months (95% CI: 24.2–28.1). OS was positively correlated with DOT (r = 0.403, P < 0.001). Multivariable analysis showed that smoking status and Eastern Cooperative Oncology Group (ECOG) performance status (PS) were independently associated with DOT; smoking status, ECOG PS, targeted therapy, and EGFR/ALK/ROS1 status were independently associated with OS. NGS in 22 patients with available samples showed genes with high mutation rates were: TP53 (54.5%), EGFR (50.0%), MYC (18.2%), and PIK3CA (13.6%). When grouped based on progression-free survival (PFS) reported in the PARAMOUNT study, the DOT > 6.9 months set was associated with PIK3CA, ALK, BRINP3, CDKN2A, CSMD3, EPHA3, KRAS , and RB1 mutations, while ERBB2 mutation was observed only in the DOT ≤ 6.9 months set. Conclusion: This study shows that initial chemotherapy with pemetrexed is an effective regimen for advanced lung adenocarcinoma in selected Chinese patients. There is no specific genetic profile predicting the benefit of pemetrexed found by NGS. Biomarkers predicting the efficacy of pemetrexed need further exploration. [ABSTRACT FROM AUTHOR]

Objective: Standard approaches for large scale phenotypic screens using electronic health record (EHR) data apply thresholds, such as ≥2 diagnosis codes, to define subjects as having a phenotype. However, the variation in the accuracy of diagnosis codes can impair the power of such screens. Our objective was to develop and evaluate an approach which converts diagnosis codes into a probability of a phenotype (PheProb). We hypothesized that this alternate approach for defining phenotypes would improve power for genetic association studies.Methods: The PheProb approach employs unsupervised clustering to separate patients into 2 groups based on diagnosis codes. Subjects are assigned a probability of having the phenotype based on the number of diagnosis codes. This approach was developed using simulated EHR data and tested in a real world EHR cohort. In the latter, we tested the association between low density lipoprotein cholesterol (LDL-C) genetic risk alleles known for association with hyperlipidemia and hyperlipidemia codes (ICD-9 272.x). PheProb and thresholding approaches were compared.Results: Among n = 1462 subjects in the real world EHR cohort, the threshold-based p-values for association between the genetic risk score (GRS) and hyperlipidemia were 0.126 (≥1 code), 0.123 (≥2 codes), and 0.142 (≥3 codes). The PheProb approach produced the expected significant association between the GRS and hyperlipidemia: p = .001.Conclusions: PheProb improves statistical power for association studies relative to standard thresholding approaches by leveraging information about the phenotype in the billing code counts. The PheProb approach has direct applications where efficient approaches are required, such as in Phenome-Wide Association Studies. [ABSTRACT FROM AUTHOR]

Obstructive sleep apnea (OSA) results from a combination of several factors leading to the obstruction of the upper respiratory tract (URT). OSA represents a systemic pathophysiological entity and leads to many comorbidities such as hypertension, coronary ischemia, and stroke. Patients with this pathophysiological entity experience also an increased risk of postoperative complications. Obesity is certainly the main cause of developing OSA. However, many other predisposing factors influence the genesis of obstructive apnea. It is important to understand the complexity of the interactions between predisposing factors to understand the relationship between weight loss following obesity surgery and the improvement in the severity of OSA. In this narrative review, we expose the seven major categories of predisposing factors that interact to generate obstructive apneas in patients, namely the anatomic abnormalities of the URT, the mechanical and the metabolic responses of the upper airway musculature, the loop gain, the arousal threshold, and the hormonal abnormalities. The genesis of apnea is the result of a complex dynamic interaction between the anatomical risk factors and the compensatory neuromuscular reflexes. All of these points are integrally part of the perioperative care of the obese patients. Finally, we will discuss different options for weight reduction. [ABSTRACT FROM AUTHOR]

Background: Previous studies have indicated that variants of the high sensitive C-reactive protein (CRP), Interleukin (IL)-6 and leptin receptor (LEPR) genes are associated with the presence of obstructive sleep apnea (OSA) but not in non-alcoholic fatty liver disease (NAFLD) in Asian Indians. The study was conducted to investigate the association of CRP rs1130864 (1444), IL-6 rs1800795 (-174) and LEPR rs1137101 (Q223) genes with OSA and NAFLD in Asian Indians residing in North India. Methods: 240 overweight/ obese subjects [body mass index (BMI>23kg/m2)], 124 with OSA and with NAFLD (group 1), 47 with OSA without NAFLD (group 2), 44 without OSA and with NAFLD (group 3) and 25 without OSA and without NAFLD (group 4) were recruited in this study. The severity of NAFLD was based on abdomen liver ultrasound and of OSA on overnight polysomnography. Clinical details, anthropometry profile, body composition, biochemical parameters and inflammatory markers were measured. Polymerase chain reaction and restriction fragment length polymorphism of CRP, IL-6 and LEPR gene was performed. The associations of these polymorphisms with clinical, anthropometric and biochemical profiles were investigated. The genotypes were confirmed by DNA sequencing analysis. Results: The , and alleles of IL-6, CRP and LEPR genes was more frequent in OSA and NAFLD subjects and significantly correlated with higher protein levels. The prevalence of variant genotypes of CRP, of IL-6 and of LEPR genes was significantly higher in OSA subjects as compared to non OSA subjects. Further, genotype of IL-6 (), T/T of CRP ) and genotype of LEPR () was associated with significantly higher BMI, fat mass (kg), % body fat, waist circumference, serum triglycerides, total cholesterol, alkaline phosphate, aspartate transaminase and fasting insulin levels in OSA and NAFLD subjects. Using a multivariate analysis, the combined effect of three polymorphisms of CRP, IL-6 and LEPR gene variants on OSA and NAFLD risk was evaluated. Odds ratio for OSA and NAFLD with the combination of the three gene polymorphisms increased to 2.84 (95% CI: 1.08–6.54; p = 0.04) even when adjusted for sex, age and BMI. Conclusion: Polymorphisms of pro-inflammatory cytokine genes were associated with increased risk of OSA and NAFLD in Asian Indians. [ABSTRACT FROM AUTHOR]

Introduction: Obstructive sleep apnea (OSA) is a serious and prevalent medical condition with major consequences for health and safety. Excessive daytime sleepiness (EDS) is a common—but not universal—accompanying symptom. The purpose of this literature analysis is to understand whether the presence/absence of EDS is associated with different physiopathologic, prognostic, and therapeutic outcomes in OSA patients. Methods: Articles in English published in PubMed, Medline, and EMBASE between January 2000 and June 2017, focusing on no-EDS OSA patients, were critically reviewed. Results: A relevant percentage of OSA patients do not complain of EDS. EDS is a significant and independent predictor of incident cardiovascular disease (CVD) and is associated with all-cause mortality and an increased risk of metabolic syndrome and diabetes. Male gender, younger age, high body mass index, are predictors of EDS. The positive effects of nasal continuous positive airway pressure (CPAP) therapy on blood pressure, insulin resistance, fatal and non-fatal CVD, and endothelial dysfunction risk factors have been demonstrated in EDS-OSA patients, but results are inconsistent in no-EDS patients. The most sustainable cause of EDS is nocturnal hypoxemia and alterations of sleep architecture, including sleep fragmentation. These changes are less evident in no-EDS patients that seem less susceptible to the cortical effects of apneas. Conclusions: There is no consensus if we should consider OSA as a single disease with different phenotypes with or without EDS, or if there are different diseases with different genetic/epigenetic determinants, pathogenic mechanisms, prognosis, and treatment.The small number of studies focused on this issue indicates the need for further research in this area. Clinicians must carefully assess the presence or absence of EDS and decide accordingly the treatment. This approach could improve combination therapy targeted to a patient's specific pathology to enhance both efficacy and long-term adherence to OSA treatment and significantly reduce the social, economic, and health negative impact of OSA. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: Gene-macronutrient interactions may contribute to the development of type 2 diabetes but research evidence to date is inconclusive. We aimed to increase our understanding of the aetiology of type 2 diabetes by investigating potential interactions between genes and macronutrient intake and their association with the incidence of type 2 diabetes.Methods: We investigated the influence of interactions between genetic risk scores (GRSs) for type 2 diabetes, insulin resistance and BMI and macronutrient intake on the development of type 2 diabetes in the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct, a prospective case-cohort study across eight European countries (N = 21,900 with 9742 incident type 2 diabetes cases). Macronutrient intake was estimated from diets reported in questionnaires, including proportion of energy derived from total carbohydrate, protein, fat, plant and animal protein, saturated, monounsaturated and polyunsaturated fat and dietary fibre. Using multivariable-adjusted Cox regression, we estimated country-specific interaction results on the multiplicative scale, using random-effects meta-analysis. Secondary analysis used isocaloric macronutrient substitution.Results: No interactions were identified between any of the three GRSs and any macronutrient intake, with low-to-moderate heterogeneity between countries (I2 range 0-51.6%). Results were similar using isocaloric macronutrient substitution analyses and when weighted and unweighted GRSs and individual SNPs were examined.Conclusions/interpretation: Genetic susceptibility to type 2 diabetes, insulin resistance and BMI did not modify the association between macronutrient intake and incident type 2 diabetes. This suggests that macronutrient intake recommendations to prevent type 2 diabetes do not need to account for differences in genetic predisposition to these three metabolic conditions. [ABSTRACT FROM AUTHOR]

Backgrounds/Aims: MicroRNAs (miRs) often contribute to the progression of non-small cell lung cancer (NSCLC) via regulation of mRNAs that are involved in lung homeostasis. We conducted a study aimed at exploring the roles of miR-183 in the proliferation, epithelial-mesenchymal transition (EMT), invasion and migration of human NSCLC cells via targeting MTA1. Methods: NSCLC and adjacent normal tissues were collected from 194 patients with NSCLC. Positive expression of MTA1 protein was detected by immunohistochemistry. The highest levels of expression of miR-183 were detected using RT-qPCR in SPC-A-1 cells, which were selected and assigned to the following groups: blank, negative control (NC), miR-183 mimic, miR-183 inhibitor, siRNA-MTA1, and miR-183 inhibitor + siRNA-MTA1. The expression of miR-183 and the mRNA and protein expression of MTA1, E-cadherin, Vimentin, Snail, PCNA, Bax and Bcl-2 in tissues and transfected cells were measured using RT-qPCR and western blot analysis. Cell proliferation, apoptosis, migration and invasion were evaluated by CCK-8, flow cytometry, scratch tests and Transwell assays. Tumor xenografts were conducted in nude mice to determine tumor growth. Results: SPC-A-1 cells with the highest levels of miR-183 expression were selected. Compared with adjacent normal tissues, the expression of miR-183 and the mRNA and protein expression of E-cadherin and Bax were decreased in NSCLC tissues, while mRNA and protein expression of MTA1, Vimentin, snail, PCNA and Bcl-2 were increased. MiR-183 was over-expressed in the miR-183 mimic group and under-expressed in the miR-183 inhibitor and miR-183 inhibitor + siRNA-MTA1 groups. In the miR-183 mimic and siRNA-MTA1 groups, the mRNA and protein expression of E-cadherin and Bax, as well as cell apoptosis, were enhanced, while the expression levels of MTA1, Vimentin, snail, PCNA and Bcl-2 mRNA and protein, cell proliferation, migration, invasion and tumor growth were reduced relative to the blank and NC groups. The miR-183 inhibitor group exhibited an opposite trend. Conclusion: Our study indicates that miR-183 down-regulates MTA1 to inhibit the proliferation, EMT, migration and invasion of human NSCLC cells. [ABSTRACT FROM AUTHOR]