OMICmAge: An integrative multi-omics approach to quantify biological age with electronic medical records

Biological aging is a multifactorial process involving complex interactions of cellular and biochemical processes that is reflected in omic profiles. Using common clinical laboratory measures in ~30,000 individuals from the MGB-Biobank, we developed a robust, predictive biological aging phenotype, EMRAge, that balances clinical biomarkers with overall mortality risk and can be broadly recapitulated across EMRs. We then applied elastic-net regression to model EMRAge with DNA-methylation (DNAm) and multiple omics, generating DNAmEMRAge and OMICmAge, respectively. Both biomarkers demonstrated strong associations with chronic diseases and mortality that outperform current biomarkers across our discovery (MGB-ABC, n=3,451) and validation (TruDiagnostic, n=12,666) cohorts. Through the use of epigenetic biomarker proxies, OMICmAge has the unique advantage of expanding the predictive search space to include epigenomic, proteomic, metabolomic, and clinical data while distilling this in a measure with DNAm alone, providing opportunities to identify clinically-relevant interconnections central to the aging process.

Patterns of Growth and Decline in Lung Function in Persistent Childhood Asthma

BACKGROUND

Tracking longitudinal measurements of growth and decline in lung function in patients with persistent childhood asthma may reveal links between asthma and subsequent chronic airflow obstruction.

METHODS

We classified children with asthma according to four characteristic patterns of lung-function growth and decline on the basis of graphs showing forced expiratory volume in 1 second (FEV1), representing spirometric measurements performed from childhood into adulthood. Risk factors associated with abnormal patterns were also examined. To define normal values, we used FEV1 values from participants in the National Health and Nutrition Examination Survey who did not have asthma.

RESULTS

Of the 684 study participants, 170 (25%) had a normal pattern of lung-function growth without early decline, and 514 (75%) had abnormal patterns: 176 (26%) had reduced growth and an early decline, 160 (23%) had reduced growth only, and 178 (26%) had normal growth and an early decline. Lower baseline values for FEV1, smaller bronchodilator response, airway hyperresponsiveness at baseline, and male sex were associated with reduced growth (P<0.001 for all comparisons). At the last spirometric measurement (mean [±SD] age, 26.0±1.8 years), 73 participants (11%) met Global Initiative for Chronic Obstructive Lung Disease spirometric criteria for lung-function impairment that was consistent with chronic obstructive pulmonary disease (COPD); these participants were more likely to have a reduced pattern of growth than a normal pattern (18% vs. 3%, P<0.001).

CONCLUSIONS

Childhood impairment of lung function and male sex were the most significant predictors of abnormal longitudinal patterns of lung-function growth and decline. Children with persistent asthma and reduced growth of lung function are at increased risk for fixed airflow obstruction and possibly COPD in early adulthood. (Funded by the Parker B. Francis Foundation and others; ClinicalTrials.gov number, NCT00000575.).

A polymorphism in HLA-G modifies statin benefit in asthma

Several reports have shown that statin treatment benefits patients with asthma, however inconsistent effects have been observed. The mir-152 family (148a, 148b and 152) has been implicated in asthma. These microRNAs suppress HLA-G expression, and rs1063320, a common SNP in the HLA-G 3’UTR which is associated with asthma risk, modulates miRNA binding. We report that statins up-regulate mir-148b and 152, and affect HLA-G expression in an rs1063320 dependent fashion. In addition, we found that individuals who carried the G minor allele of rs1063320 had reduced asthma related exacerbations (emergency department visits, hospitalizations or oral steroid use) compared to non-carriers (p=0.03) in statin users ascertained in the Personalized Medicine Research Project at the Marshfield Clinic (n=421). These findings support the hypothesis that rs1063320 modifies the effect of statin benefit in asthma, and thus may contribute to variation in statin efficacy for the management of this disease.

Predicting inhaled corticosteroid response in asthma with two associated SNPs

Inhaled corticosteroids are the most commonly used controller medications prescribed for asthma. Two single-nucleotide polymorphisms (SNPs), rs1876828 in CRHR1 and rs37973 in GLCCI1, have previously been associated with corticosteroid efficacy. We studied data from four existing clinical trials of asthmatics who received inhaled corticosteroids and had lung function measured by forced expiratory volume in one second (FEV1) before and after the period of such treatment. We combined the two SNPs rs37973 and rs1876828 into a predictive test of FEV1 change using a Bayesian model, which identified patients with good or poor steroid response (highest or lowest quartile, respectively) with predictive performance of 65.7% (p = 0.039 vs. random) area under the receiver-operator characteristic curve in the training population and 65.9% (p = 0.025 vs. random) in the test population. These findings show that two genetic variants can be combined into a predictive test that achieves similar accuracy and superior replicability compared with single SNP predictors.