We examined common variation in asthma risk by conducting a meta-analysis of worldwide asthma genome-wide association studies (23,948 cases, 118,538 controls) from ethnically-diverse populations. We identified five new asthma loci, uncovered two additional novel associations at two known asthma loci, established asthma associations at two loci implicated previously in comorbidity of asthma plus hay fever, and confirmed nine known loci. Investigation of pleiotropy showed large overlaps in genetic variants with autoimmune and inflammatory diseases. Enrichment of asthma risk loci in enhancer marks, especially in immune cells, suggests a major role of these loci in the regulation of immune-related mechanisms.

Age is the dominant risk factor for most chronic human diseases; yet the mechanisms by which aging confers this risk are largely unknown. 1 Recently, the age-related acquisition of somatic mutations in regenerating hematopoietic stem cell populations leading to clonal expansion was associated with both hematologic cancer 2 – 4 and coronary heart disease 5 , a phenomenon termed ‘Clonal Hematopoiesis of Indeterminate Potential’ (CHIP). 6 Simultaneous germline and somatic whole genome sequence analysis now provides the opportunity to identify root causes of CHIP. Here, we analyze high-coverage whole genome sequences from 97,691 participants of diverse ancestries in the NHLBI TOPMed program and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid, and inflammatory traits specific to different CHIP genes. Association of a genome-wide set of germline genetic variants identified three genetic loci associated with CHIP status, including one locus at TET2 that was African ancestry specific. In silico -informed in vitro evaluation of the TET2 germline locus identified a causal variant that disrupts a TET2 distal enhancer resulting in increased hematopoietic stem cell self-renewal. Overall, we observe that germline genetic variation shapes hematopoietic stem cell function leading to CHIP through mechanisms that are both specific to clonal hematopoiesis and shared mechanisms leading to somatic mutations across tissues.

We used a deeply sequenced dataset of 910 individuals, all of African descent, to construct a set of DNA sequences present in these individuals but missing from the reference human genome. We aligned 1.19 trillion reads from the 910 individuals to the reference genome (GRCh38), collected all reads that failed to align, and assembled these reads into contiguous sequences (contigs). We then compared all contigs to one another to identify a set of unique sequences representing regions of the African pan-genome missing from the reference genome. Our analysis revealed 296,485,284 bp in 125,715 distinct contigs present in the African-descended populations, demonstrating that the African pan-genome contains ~10% more DNA than the current human reference genome. Although the functional significance of nearly all of this sequence is unknown, 387 of the novel contigs fall within 315 distinct protein-coding genes while the rest appear to be intergenic.

OBJECTIVE -Although poor medication adherence may contribute to inadequate diabetes control, ways to feasibly measure adherence in routine clinical practice have yet to be established. The present study was conducted to determine whether pharmacy claims-based measures of medication adherence are associated with clinical outcomes in patients with diabetes.RESEARCH DESIGN AND METHODS -The study setting was a large, integrated delivery and financial system serving the residents of southeastern Michigan. The study population consisted of 677 randomly selected patients aged Ն18 years with a diagnosis of diabetes, hypercholesterolemia, and hypertension and who filled at least one prescription for either an antidiabetic, lipid-lowering, or antihypertensive drug in each of the 3 study years (1999 -2001). The main outcome measures were HbA 1c , LDL cholesterol levels, and blood pressure.RESULTS -Nonadherent patients had both statistically and clinically worse outcomes than adherent patients. Even after adjusting for demographic and clinical characteristics, nonadherence was significantly associated with HbA 1c and LDL cholesterol levels. A 10% increase in nonadherence to metformin and statins was associated with an increase of 0.14% in HbA 1c and an increase of 4.9 mg/dl in LDL cholesterol levels. Nonadherence to ACE inhibitors was not significantly associated with blood pressure.CONCLUSIONS -Claims-based measures of medication adherence are associated with clinical outcomes in patients with diabetes and may therefore prove to be useful in clinical practice. More research is needed on methods to introduce claims-based adherence measurements into routine clinical practice and how to use these measurements to effectively improve adherence and health outcomes in chronic care management. Diabetes Care 27:2800 -2805, 2004N onadherence to medications is a common problem in clinical practice, especially among patients with asymptomatic chronic conditions such as diabetes, hypertension, and hypercholesterolemia (1-4). A recent meta-analysis has showed that the average adherence in patients with diabetes is 67.5%, which is lower than that found among many conditions (5). Also, recently, a specific systematic review on adherence to medications for diabetes showed that average adherence to oral hypoglycemic agents ranged from 36 to 93% (6). In general, poor adherence to medications has been shown to be associated with the development of complications, disease progression, avoidable hospitalizations, premature disability, and death. In total, the costs associated with poor medication adherence are estimated to approach $100 billion per year (7). Despite these known consequences, adherence rates have remained unchanged since the 1970s (1,8).Nonadherence is the result of a complex interaction among the social environment, the patient, and the health providers (9). Adherence to medications is not routinely measured in clinical practice, and a gold standard that can be easily implemented, even for research purposes, does not exist (1,5,...

BACKGROUND Self-identified race or ethnic group is used to determine normal reference standards in the prediction of pulmonary function. We conducted a study to determine whether the genetically determined percentage of African ancestry is associated with lung function and whether its use could improve predictions of lung function among persons who identified themselves as African American. METHODS We assessed the ancestry of 777 participants self-identified as African American in the Coronary Artery Risk Development in Young Adults (CARDIA) study and evaluated the relation between pulmonary function and ancestry by means of linear regression. We performed similar analyses of data for two independent cohorts of subjects identifying themselves as African American: 813 participants in the Health, Aging, and Body Composition (HABC) study and 579 participants in the Cardiovascular Health Study (CHS). We compared the fit of two types of models to lung-function measurements: models based on the covariates used in standard prediction equations and models incorporating ancestry. We also evaluated the effect of the ancestry-based models on the classification of disease severity in two asthma-study populations. RESULTS African ancestry was inversely related to forced expiratory volume in 1 second (FEV1) and forced vital capacity in the CARDIA cohort. These relations were also seen in the HABC and CHS cohorts. In predicting lung function, the ancestry-based model fit the data better than standard models. Ancestry-based models resulted in the reclassification of asthma severity (based on the percentage of the predicted FEV1) in 4 to 5% of participants. CONCLUSIONS Current predictive equations, which rely on self-identified race alone, may misestimate lung function among subjects who identify themselves as African American. Incorporating ancestry into normative equations may improve lung-function estimates and more accurately categorize disease severity. (Funded by the National Institutes of Health and others.)

Background Asthma is an inflammatory condition often punctuated by episodic symptomatic worsening, and accordingly, individuals with asthma may have waxing and waning adherence to controller therapy. Objective To measure changes in inhaled corticosteroid (ICS) adherence over time, and to estimate the effect of this changing pattern of use on asthma exacerbations. Methods ICS adherence was estimated from electronic prescription and fill information for 298 participants in the Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-ethnicity (SAPPHIRE). For each individual we calculated a moving average of ICS adherence for each day of follow-up. Asthma exacerbations were defined as the need for oral corticosteroids, an asthma-related emergency department visit, or an asthma-related hospitalization. Proportional hazard models were used to assess the relationship between ICS medication adherence and asthma exacerbations. Results Adherence to ICS medications began to increase prior to the first asthma exacerbation and continued afterward. Adherence was associated with a reduction in exacerbations, but was only statistically significant among individuals whose adherence was >75% of the prescribed dose (hazard ratio [HR] 0.61; 95% confidence interval [CI] 0.41–0.90) when compared with individuals whose adherence was ≤25%. This pattern was largely confined to individuals whose asthma was not well controlled initially. An estimated 24% of asthma exacerbations were attributable to ICS medication non-adherence. Conclusions Inhaled corticosteroid adherence varies in the time period leading up to and following an asthma exacerbation, and non-adherence likely contributes to a large number of these exacerbations. High levels of adherence are likely required to prevent these events. [ClinicalTrials.gov number NCT01142947]

Genome-wide association studies (GWAS) have identified 36 loci associated with body mass index (BMI), predominantly in populations of European ancestry. We conducted a meta-analysis to examine the association of >3.2 million SNPs with BMI in 39,144 men and women of African ancestry, and followed up the most significant associations in an additional 32,268 individuals of African ancestry. We identified one novel locus at 5q33 (GALNT10, rs7708584, p=3.4×10−11) and another at 7p15 when combined with data from the Giant consortium (MIR148A/NFE2L3, rs10261878, p=1.2×10−10). We also found suggestive evidence of an association at a third locus at 6q16 in the African ancestry sample (KLHL32, rs974417, p=6.9×10−8). Thirty-two of the 36 previously established BMI variants displayed directionally consistent effect estimates in our GWAS (binomial p=9.7×10−7), of which five reached genome-wide significance. These findings provide strong support for shared BMI loci across populations as well as for the utility of studying ancestrally diverse populations.

Genetic association studies have identified 21 loci associated with atopic dermatitis risk predominantly in populations of European ancestry. To identify further susceptibility loci for this common complex skin disease, we performed a meta-analysis of >15 million genetic variants in 21,399 cases and 95,464 controls from populations of European, African, Japanese and Latino ancestry, followed by replication in 32,059 cases and 228,628 controls from 18 studies. We identified 10 novel risk loci, bringing the total number of known atopic dermatitis risk loci to 31 (with novel secondary signals at 4 of these). Notably, the new loci include candidate genes with roles in regulation of innate host defenses and T-cell function, underscoring the important contribution of (auto-)immune mechanisms to atopic dermatitis pathogenesis.