Lipoprotein(a) and incident type-2 diabetes: results from the prospective Bruneck study and a meta-analysis of published literature

Abstract

Aims: We aimed to (1) assess the association between lipoprotein(a) [Lp(a)] concentration and incident type-2 diabetes in the Bruneck study, a prospective population-based study, and (2) combine findings with evidence from published studies in a literature-based meta-analysis.

Methods: We used Cox proportional hazards models to calculate hazard ratios (HR) for incident type-2 diabetes over 20 years of follow-up in 815 participants of the Bruneck study according to their long-term average Lp(a) concentration. For the meta-analysis, we searched Medline, Embase and Web of Science for relevant prospective cohort studies published up to October 2016.

Results: In the Bruneck study, there was a 12% higher risk of type-2 diabetes for a one standard deviation lower concentration of log Lp(a) (HR = 1.12 [95% CI 0.95-1.32]; P = 0.171), after adjustment for age, sex, alcohol consumption, body mass index, smoking status, socioeconomic status, physical activity, systolic blood pressure, HDL cholesterol, log high-sensitivity C-reactive protein and waist-hip ratio. In a meta-analysis involving four prospective cohorts with a total of 74,575 participants and 4514 incident events, the risk of type-2 diabetes was higher in the lowest two quintiles of Lp(a) concentrations (weighted mean Lp(a) = 3.3 and 7.0 mg/dL, respectively) compared to the highest quintile (62.9 mg/dL), with the highest risk of type-2 diabetes seen in quintile 1 (HR = 1.28 [1.14-1.43]; P < 0.001).

Conclusions: The current available evidence from prospective studies suggests that there is an inverse association between Lp(a) concentration and risk of type-2 diabetes, with a higher risk of type-2 diabetes at low Lp(a) concentrations (approximately <7 mg/dL).

Keywords: Diabetes; Lipoprotein(a); Meta-analysis; Prospective study.

Fig. 1

Change in the hazards ratios (95% CI) per SD lower log lipoprotein(a) for incident diabetes mellitus by follow-up time in the Bruneck Study. CI confidence intervals. Hazard ratios are shown for Model 3, adjusted for age, sex, alcohol consumption, BMI, smoking status, socioeconomic status, physical activity, systolic blood pressure, HDL cholesterol, log hsCRP and waist–hip ratio

Fig. 2

Sensitivity analyses showing the hazards ratios (HR) and 95% confidence intervals for the risk of incident type 2 diabetes per SD lower log lipoprotein(a) in the Bruneck Study. HbA1c hemoglobin A1c, LDL-C low-density lipoprotein cholesterol, Lp(a) lipoprotein(a). Hazard ratios are per quintile increase of standardized log lipoprotein(a). Model 3 was adjusted for age, sex, alcohol consumption, body mass index, smoking status, socioeconomic status, physical activity, systolic blood pressure, HDL cholesterol, log high sensitivity c-reactive protein and waist–hip ratio. Sensitivity analyses models as shown

Fig. 3

Meta-analysis of reported risk ratios for incident type-2 diabetes per quintile of Lp(a) concentration. Based on a fixed-effect meta-analysis of data from: the Bruneck study (Model 3, adjusted for age, sex, alcohol consumption, body mass index, smoking status, socioeconomic status, physical activity, systolic blood pressure, HDL cholesterol, log hsCRP and waist–hip ratio); the Copenhagen City Heart Study and the Copenhagen General Population Study (results adjusted for: age, sex, total cholesterol, HDL cholesterol, triglyceride concentrations, systolic blood pressure, body mass index, smoking status, lipid lowering therapy, and postmenopausal status and hormone replacement therapy among women); the European Prospective Investigation of Cancer-Norfolk study (results adjusted for: age, sex, body mass index, alcohol, smoking status, diastolic and systolic blood pressure, family history of diabetes, physical activity, education, total cholesterol, LDL cholesterol, prevalent cancer, CHD or stroke, antihypertension medication, lipid-lowering drugs, and CRP); and the Women’s Health Study (results adjusted for: age, race, RCT assignment, smoking status, menopausal status, postmenopausal hormone use, family history of diabetes, blood pressure, body mass index, hemoglobin A1c). Studies are weighted using the inverse variance method. Mean Lp(a) concentrations in each quintile were estimated by taking the average of the median Lp(a) concentrations in each quintile across studies, weighted by the number of participants, excluding the Women’s Health Study which did not report median Lp(a) concentrations by quintile