Publications

OBJECTIVES

We prospectively examined whether socioeconomic status (SES) predicts incident type II diabetes (diabetes), a cardiovascular risk equivalent and burgeoning public health epidemic among women.

METHODS

Participants include 23,992 women with Hb(A1c) levels <6% and no CVD or diabetes at baseline followed from February 1993 to March 2007. SES was measured by education and income while diabetes was self-reported.

RESULTS

Over 12.3 years of follow-up, 1,262 women developed diabetes. In age and race adjusted models, the relative risk of diabetes decreased with increasing education (<2 years of nursing, 2 to <4 years of nursing, bachelor's degree, master's degree, and doctorate: 1.0, 0.7 [95% Confidence Interval (CI), 0.6-0.8], 0.6 (95% CI, 0.5-0.7), 0.5 (95% CI, 0.4-0.6), 0.4 (95% CI, 0.3-0.5); p(trend)<0.001). Adjustment for traditional and non-traditional cardiovascular risk factors attenuated this relationship (education: p(trend) = 0.96). Similar associations were observed between income categories and diabetes.

CONCLUSION

Advanced education and increasing income were both inversely associated with incident diabetes even in this relatively well-educated cohort. This relationship was largely explained by behavioral factors, particularly body mass index.

The primary cause of poor outcome following allogeneic hematopoietic cell transplantation (HCT) for chronic lymphocytic leukemia (CLL) is disease recurrence. Detection of increasing minimal residual disease (MRD) following HCT may permit early intervention to prevent clinical relapse; however, MRD quantification remains an uncommon diagnostic test because of logistical and financial barriers to widespread use. Here we describe a method for quantifying CLL MRD using widely available consensus primers for amplification of all Ig heavy chain (IGH) genes in a mixture of peripheral blood mononuclear cells, followed by high-throughput sequencing (HTS) for disease-specific IGH sequence quantification. To achieve accurate MRD quantification, we developed a systematic bioinformatic methodology to aggregate cancer clone sequence variants arising from systematic and random artifacts occurring during IGH-HTS. We then compared the sensitivity of IGH-HTS, flow cytometry, and allele-specific oligonucleotide PCR for MRD quantification in 28 samples collected from 6 CLL patients following allogeneic HCT. Using amplimer libraries generated with consensus primers from patient blood samples, we demonstrate the sensitivity of IGH-HTS with 454 pyrosequencing to be 10(-5), with a high correlation between quantification by allele-specific oligonucleotide PCR and IGH-HTS (r = 0.85). From the same dataset used to quantify MRD, IGH-HTS also allowed us to profile IGH repertoire reconstitution after HCT-information not provided by the other MRD methods. IGH-HTS using consensus primers will broaden the availability of MRD quantification in CLL and other B cell malignancies, and this approach has potential for quantitative evaluation of immune diversification following transplant and nontransplant therapies.