BACKGROUND: Previous studies have demonstrated that cardiovascular risk is higher with increased lipoprotein(a) [Lp(a)]. Whether Lp(a) concentration is related to type 2 diabetes is unclear.
METHODS: In 26 746 healthy US women (mean age 54.6 years), we prospectively examined baseline Lp(a) concentrations and incident type 2 diabetes (n = 1670) for a follow-up period of 13 years. We confirmed our findings in 9652 Danish men and women with prevalent diabetes (n = 419). Analyses were adjusted for risk factors that included age, race, smoking, hormone use, family history, blood pressure, body mass index, hemoglobin A1c (Hb A1c), C-reactive protein, and lipids.
RESULTS: Lp(a) was inversely associated with incident diabetes, with fully adjusted hazard ratios (HRs) and 95% CIs for quintiles 2–5 vs quintile 1 of 0.87 (0.75–1.01), 0.80 (0.68–0.93), 0.88 (0.76–1.02), and 0.78 (0.67–0.91); P for trend 0.002. The association was stronger in nonfasting women, for whom respective HRs were 0.79 (0.58–1.09), 0.78 (0.57–1.08), 0.66 (0.46–0.93), and 0.56 (0.40–0.80); P for trend 0.001; P for interaction with fasting status 0.002. When we used Lp(a) ≥10 mg/L and Hb A1c <5% as reference values, the adjusted HRs were 1.62 (0.91–2.89) for Lp(a) <10 mg/L and Hb A1c <5%, 3.50 (3.06–4.01) for Lp(a)≥10 mg/L and Hb A1c 5%–<6.5%, and 5.36 (4.00–7.19) for Lp(a) <10 mg/L and Hb A1c 5%–<6.5%. Results were similar in nonfasting Danish men and women, for whom adjusted odds ratios were 0.75 (0.55–1.03), 0.64 (0.46–0.88), 0.74 (0.54–1.01), and 0.58 (0.42–0.79) for Lp(a) quintiles 2–5 vs quintile 1; P for trend 0.002.
CONCLUSIONS: Our results indicated that Lp(a) was associated inversely with risk of type 2 diabetes independently of risk factors, in contrast to prior findings of positive associations of Lp(a) with cardiovascular risk.
Lipoprotein(a) [Lp(a)],7 a subtype of LDL that carries apolipoprotein(a) [apo(a)], has been associated with risk of cardiovascular disease (CVD) (1), but the role of Lp(a) in type 2 diabetes is unclear. Since the discovery of Lp(a) by Berg in 1963, increased Lp(a) concentrations have been associated with a higher risk of CVD in most studies (2). Also, increased concentrations of Lp(a) have been associated with higher risk of CVD in diabetic patients (3–5). However, it is unclear if Lp(a) concentrations are related to risk of type 2 diabetes or insulin resistance (6). It has been suggested that hyperinsulinemia lowers Lp(a) concentrations (7,8), but results of prior case-control studies have been inconclusive (6). Some of these studies found no change in Lp(a) concentrations in patients with type 2 diabetes (9), whereas others found either higher or lower Lp(a) concentrations (10,11).
Case-control studies are susceptible to bias, because the disease (e.g., diabetes) may alter lipoprotein concentrations; thus, prospective studies are better for determining risk-factor associations. Therefore, we conducted the first prospective study of Lp(a) concentration and risk of type 2 diabetes in a cohort of healthy US women. Based on prior work involving this cohort, which suggested that nonfasting concentrations of certain lipids may be superior to fasting concentrations for risk prediction (12,13), we also examined whether fasting status modified the association of Lp(a) with type 2 diabetes. Finally, we replicated our findings in a general population of men and women from Denmark (14).
Materials and Methods
The Women's Health Study (WHS) is a completed randomized, double-blinded, placebo-controlled clinical trial of low-dose aspirin and vitamin E in US female health-care professionals (15). Eligible participants were apparently healthy women, ages 45 years or older, who were free of self-reported CVD or cancer at study entry (1992–1995). At the time of enrollment, participants gave written informed consent and completed questionnaires on demographics, medical history, medications, and lifestyle factors. They were also asked to provide a blood sample, if they were willing. Participants were requested, but not required, to have the sample drawn in the morning before eating, and sample donors reported the number of hours since their last meal before the blood draw. For the present analysis, we excluded women with prevalent diabetes (n = 770), baseline hemoglobin A1c (Hb A1c) ≥6.5% (n = 270), or missing lipid measurements (n = 237), resulting in 26 746 women for analysis. We also repeated the analyses after excluding the 164 women with Hb A1c ≥6.0% and <6.5%. The study was approved by the institutional review boards of the Brigham and Women's Hospital (Boston, MA). We replicated our findings in a general population of 9652 men and women [Copenhagen City Heart Study (CCHS)] (14) in relation to prevalent type 2 diabetes (n = 419).
EDTA blood samples were obtained from WHS participants at the time of enrollment and stored in vapor-phase liquid nitrogen (−170 °C). Samples from participants whose last meal was 8 h or more before their blood draw comprised the fasting sample (n = 19 292), and samples from those who had eaten within 8 h comprised the nonfasting sample (n = 6100). In a laboratory (N. Rifai) certified by the National Heart, Lung and Blood Institute/Centers for Disease Control and Prevention Lipid Standardization program, baseline Lp(a) was measured by using a commercially available immunoturbidimetric assay that is not affected by the number of kringle-IV type-2 repeats (16), with reagents and calibrators from Denka Seiken. There was no interference of this Lp(a) assay with triglycerides. The CVs at Lp(a) concentrations of 176 and 581 mg/L were 3.6% and 1.5%, respectively. Total, LDL, and HDL cholesterol were assayed directly. Hb A1c was measured with turbidimetric immunoinhibition using hemolyzed whole blood or packed red cells (Roche Diagnostics). High-sensitivity C-reactive protein (hsCRP) was measured by using a high-sensitivity immunoturbidimetric assay with reagents and calibrators from Denka Seiken.
For CCHS participants, Lp(a) concentrations were measured at the 1991–1994 examination with a well-characterized inhouse immunoturbidimetric assay using a Technicon Axon autoanalyser (Miles), rabbit antihuman lipoprotein polyclonal antibodies (Q023, Dako), and a human serum lipoprotein calibrator (Dako) (14). There was no interference from triglycerides up to 8 mmol/L (708 mg/dL). Samples with a concentration of Lp(a) above 850 mg/L or of triglycerides above 8 mmol/L were diluted 1:5. The CVs at Lp(a) concentrations of 90, 300, 420, 660, 1000, and 1270 mg/L and at triglyceride concentrations of 1–2 mmol/L were 11%, 3%, 2%, 2%, 5%, and 4%, respectively. Enzymatic assays were used to measure total and HDL cholesterol and triglycerides. LDL cholesterol was measured directly at triglycerides >400 mg/dL (4.52 mmol/L) and otherwise calculated according to Friedewald. hsCRP was measured by using a high-sensitivity immunoturbidimetric assay (Dako).
ASCERTAINMENT OF TYPE 2 DIABETES
Incident type 2 diabetes in WHS participants was ascertained by self-report on annual follow-up questionnaires through March 2008 as previously described (17,18). Screening rates for diabetes were high (85%–90%). All self-reported cases of type 2 diabetes were validated by using a supplemental questionnaire based on diagnostic criteria recommended by the American Diabetes Association, additional information from the participants obtained by telephone interview, or review of medical records, with a positive predictive value for incident type 2 diabetes validation of 91% (17). Only confirmed cases of incident type 2 diabetes were included in this analysis.
In the CCHS, prevalent type 2 diabetes was ascertained by self-report at the 1991–1994 examination, use of hypoglycemic drugs, or a nonfasting plasma glucose >200 mg/dL (11.1 mmol/L).
Statistical analyses were performed using STATA version 10.1 (STATA Corporation).
For WHS analyses, statistical comparisons were obtained from Student t-tests for continuous variables expressed as means, from Kruskal–Wallis tests for variables expressed as medians, and χ2 tests for categorical variables. We calculated Pearson correlation coefficients for Lp(a) with select covariates in fasting and nonfasting participants. Following guidelines from the Department of Health and Human Services, Lp(a) concentrations were divided into quintiles based on the distribution among women not taking hormone replacement. Quintile cutpoints were defined separately for the fasting and nonfasting groups.
Next, cumulative probabilities of incident type 2 diabetes were calculated for WHS participants stratified by baseline Lp(a) quintiles and fasting status. Cox proportional hazard regression models were used to calculate the hazard ratios (HRs) and 95% CIs according to these quintiles. Incidence rates and regression models were examined for thresholds. To examine the extent to which Lp(a) was associated with incident events, we considered 3 levels of adjustment: (a) age, race, and randomized treatment assignment; (b) covariates in model 1 plus baseline smoking status, menopausal status, postmenopausal hormone use, family history of diabetes, blood pressure, body mass index (BMI), and baseline Hb A1c; (c) covariates in model 2 plus hsCRP, LDL cholesterol, HDL cholesterol, and triglycerides. Further adjustment for exercise, alcohol use, and education level, as well as adjustment for time of blood draw resulted in almost identical findings. The P value for trend was obtained by using quintile number as a predictor. All P values were 2-tailed. Statistical tests for interaction between fasting status and Lp(a) concentration in relation to incident type 2 diabetes were obtained by using likelihood ratio tests.
We repeated the analyses after we excluded the 164 women with Hb A1c ≥6.0% and <6.5%. Given prior reports of modification of Lp(a)-related CVD risk in the presence of high LDL cholesterol concentrations, we also examined this phemonenon in relation to diabetes. We also repeated the analyses according to time of diabetes diagnosis (<6 and ≥6 years) to assess for potential confounding by participants who may have had subclinical preexisting diabetes at baseline. We analyzed risk of type 2 diabetes in participants based on baseline concentrations of Lp(a) and Hb A1c to examine additive effects of these 2 biomarkers. Finally, we repeated the analysis in women according to baseline hormones use.
For CCHS analyses, Lp(a) concentrations were divided into quintiles and logistic-regression models were used to calculate odds ratios (ORs) and 95% CIs according to these quintiles. Three levels of adjustment were considered, as described for the WHS.
Baseline characteristics of participants according to diabetes are shown in Table 1. Lp(a) concentrations in the WHS and CCHS were significantly lower in diabetes patients compared with individuals without diabetes, although the medians differed according to study population (WHS 95 vs 107 mg/L, P < 0.001; CCHS 157 vs 174 mg/L, P = 0.006). As reflected in their risk factors, the WHS participants were generally healthier and at lower risk than the CCHS population, because they were selected after we excluded baseline CVD, cancer, and diabetes, unlike the CCHS population, which was a general Danish population.
Pearson correlation coefficients showed low correlation of Lp(a) with other risk factors for diabetes in the WHS, including blood pressure, BMI, lipids, Hb A1c and hsCRP (data not shown). Although some correlations were statistically significant given the large sample size, the magnitude of the correlation was small (all coefficients <0.2).
Cumulative event probabilities for incident diabetes in WHS during a median follow-up of 13.3 years (interquartile range 12.3–13.8 years) analyzed according to baseline Lp(a) quintiles demonstrated a significant inverse association overall as well as by fasting status (Fig. 1). Associations of Lp(a) concentrations with incident type 2 diabetes were examined by fasting status in the WHS (Fig. 1 and Table 2). Incidence rates were significantly lower in quintiles 2–5 compared with quintile 1. In fasting participants, there was a threshold effect of approximately 20% lower relative risk in quintiles 2–5 compared to quintile 1. In nonfasting participants, there was a more linear effect, with up to 50% lower relative risk in quintile 5 compared with quintile 1. Notably, the inverse association of Lp(a) with diabetes remained significant and minimally attenuated after full adjustment for covariates, including LDL cholesterol, triglycerides, and Hb A1c. Overall, nonfasting Lp(a) concentrations were more strongly associated with risk of incident diabetes (P for interaction 0.002) compared with fasting.
We repeated our analyses and adjusting additionally for time of blood draw, with no change in results. Almost identical results were also obtained when we added exercise, alcohol use, and education to the models. We also examined the association of Lp(a) with diabetes in the WHS participants who were not taking hormones at baseline (n = 14 825). Similar results were obtained for participants who did not use hormones. For example, the fully adjusted HRs and 95% CIs for quintiles 2–5 vs quintile 1 in non–hormone users were: 0.90 (0.74–1.10), 0.86 (0.70–1.05), 0.91 (0.75–1.11), and 0.76 (0.61–0.93); P for trend 0.02.
The association of Lp(a) with diabetes was also similar in participants stratified by LDL cholesterol [below or above median, 121 mg/dL (3.13 mmol/L)] or by year of study follow-up (<6 or ≥6 years). The results were essentially unchanged when we additionally excluded the 164 women with baseline Hb A1c ≥6.0%.
We further investigated the threshold effect of Lp(a) on incident diabetes that was suggested for the lowest quintile concentration (<40 mg/L), using lower cutpoints of 30, 20, and 10 mg/L (Table 3). The incidence rates increased by approximately 1.5- to 2-fold for Lp(a) concentrations <10 mg/L compared with higher cutpoints. With Lp(a) ≥10 mg/L used as the reference, the age- and treatment-adjusted HR for Lp(a) <10 mg/L was 1.74 (95% CI 1.37–2.21), and the fully adjusted HR was 1.57 (95% CI 1.23–2.01), P < 0.001 for both.
Next, we examined whether baseline Lp(a) concentrations <10 and ≥10 mg/L provided additive risk information to Hb A1c concentrations within the reference interval (<5% and 5% to <6.5%, Fig. 2). With the use of the reference group of Lp(a) ≥10 mg/L and Hb A1c <5%, participants with Lp(a) <10 mg/L and Hb A1c <5% had a fully adjusted HR (95% CI) of 1.62 (0.91–2.89), whereas those with Lp(a) ≥10 mg/L and Hb A1c 5 to <6.5% had an adjusted HR of 3.50 (3.06–4.01), and those with Lp(a) <10 mg/L and Hb A1c 5 to <6.5% had an adjusted HR of 5.36 (4.00–7.19); P for trend <0.001.
As a final step, we replicated our findings in 2 settings. First, we internally validated the findings in a case-control analysis of 797 WHS women with baseline prevalent diabetes or Hb A1c ≥6.5% (cases) who were excluded from the prospective WHS study. We used as controls the 25 076 women who remained free of diabetes during the 13-year follow-up period. With the Lp(a) quintile 1 used as the reference, the adjusted ORs (95% CIs) for quintiles 2–5 were 0.75 (0.59–0.94), 0.67 (0.52–0.85), 0.72 (0.56–0.91), and 0.74 (0.58–0.93), respectively; P for trend 0.01. Lp(a) <10 vs ≥10 mg/L was associated with an adjusted OR of 2.29 (1.59–3.28); P < 0.001.
Second, we externally validated the findings in relation to prevalent type 2 diabetes in 9652 nonfasting men and women enrolled in the CCHS (Table 4) with adjusted ORs of 0.75 (0.55–1.03), 0.64 (0.46–0.88), 0.74 (0.54–1.01), and 0.58 (0.42–0.79), respectively, for quintiles 2–5 vs 1; P for trend 0.002. Lp(a) <10 mg/L (vs ≥10 mg/L) was associated with an adjusted OR of 1.54 (1.14–2.08); P = 0.005. When stratified by sex, risk estimates appeared stronger in men. However, tests for interaction of sex and Lp(a) concentration in relation to diabetes were nonsignificant.
In this prospective study of 26 746 initially healthy US women with 13-year follow-up, we found an inverse association of Lp(a) with risk of type 2 diabetes, with approximately 20%–50% lower relative risk in quintiles 2–5 compared with quintile 1. Lp(a) concentrations showed low correlation with other risk factors, and full adjustment for these risk factors resulted in almost no attenuation of the association. We externally validated these findings in a general population of 9652 Danish men and women with prevalent diabetes, confirming the inverse association of Lp(a) with diabetes with nearly identical results.
To our knowledge, this is the first prospective study that examines the association of Lp(a) with type 2 diabetes. Predicting risk of diabetes has focused largely on glycemic factors (19), with fewer studies on lipoprotein factors. Our finding of an inverse association between Lp(a) concentration and risk of incident diabetes stands in marked contrast to prior studies that have shown a positive association of Lp(a) with CVD (2), including prior findings from the same 2 cohorts in this study (14,20). Risk factors for diabetes may differ from those for CVD (21). For example, LDL cholesterol is a strong risk factor for CVD and atherosclerosis, but most prior studies have shown no independent association for LDL cholesterol with diabetes (21).
Although increased concentrations of Lp(a), in particular >300 mg/L, have been associated with higher risk of CVD (20), little is known about the association of Lp(a) with diabetes in the absence of CVD. Small case-control studies examining Lp(a) with type 2 diabetes have shown mixed results (6). In 1 small case-control study of Mexican-American individuals, lower concentrations of Lp(a) were found in diabetic patients compared with controls (11). The present finding of an inverse association of Lp(a) with diabetes after adjustment for other risk factors deserves investigation in other prospective study populations for replication of findings and determination of potential clinical utility.
The physiological function and exact mechanisms that may underlie the role of Lp(a) in CVD remain unclear, and even less is known about the role of Lp(a) in diabetes. The independence from known risk factors of the association of Lp(a) with diabetes suggests another mechanism. It is possible that low Lp(a) concentrations may be markers of insulin resistance. However, we adjusted for correlates of insulin resistance, such as triglycerides, HDL cholesterol, Hb A1c and hsCRP, as well as BMI and family history of diabetes, although we did not have insulin concentrations or more sophisticated measures of insulin resistance. Lp(a) has been associated inversely with insulin and 2-h glucose (7), consistent with our finding of an inverse association with diabetes. Insulin suppressed apo(a) function in hepatocytes at the posttranscriptional level of apo(a) (8), which may account for lower concentrations of Lp(a) found in type 2 diabetes (hyperinsulinemia and insulin resistance) and higher concentrations in type 1 diabetes (insulin deficiency). In addition, there is hormonal regulation of Lp(a), including lowering of Lp(a) by testosterone (22) and insulinlike growth factor 1 (23), and a stimulatory effect of growth hormone (24), all of which may be implicated in glucose and lipid metabolism (25). The role of Lp(a) in insulin resistance and glucose metabolism deserves further investigation for clarification of mechanisms.
It is unclear whether the relative deficiency of Lp(a) promotes the development of diabetes or whether increased concentrations of Lp(a) may be protective. The increase in incidence rates at an Lp(a) concentration cutpoint of <10 mg/L compared to higher cutpoints suggests that the relative deficiency of Lp(a) may be involved in risk. Although Lp(a) concentrations <10 mg/L had the highest relative risk, concentrations <40 mg/L were associated with approximately 20% to 50% higher relative risk in both study populations. The WHS and CCHS participants differed with respect to Lp(a) concentrations (higher in CCHS) and other risk factors, but the association of Lp(a) with diabetes was consistent and similar in magnitude in the 2 studies. Moreover, Lp(a) concentrations <40 mg/L represented the bottom quintile of both populations. Lp(a) was better for predicting incident diabetes when measured in nonfasting samples, consistent with prior data from the WHS in relation to certain lipids, in particular triglycerides, and incident cardiovascular events (12,13).
A potential limitation of this study was that ascertainment of type 2 diabetes was by self-report. However, all self-reports were confirmed, and this approach has been demonstrated to be valid in these female healthcare professionals (17). Lp(a) measurements were available only once at baseline and results could not be corrected for potential regression dilution bias. Although we measured standard and emerging risk factors for diabetes, including BMI, triglycerides, Hb A1c and hsCRP, we did not have a more specific measure of insulin resistance. Strengths of the present study include the large sample size of both cohorts, the prospective design of the WHS cohort, confirmation of the WHS findings in a second population of Danish men and women, and replication of the findings by using 2 different Lp(a) assays, including the use in WHS of a previously validated immunoassay that is independent of kringle-IV type-2 repeats (16). Finally, the finding that Lp(a) concentration predicted incident diabetes similarly both early (years <6) and late (years ≥6) in follow-up makes reverse causality seem an unlikely explanation for our findings.
In summary, we found an inverse association for Lp(a) with risk of incident type 2 diabetes in women, with external confirmation of this finding in a general population of Danish men and women with respect to prevalent diabetes. Lp(a) was associated with diabetes independent of other risk factors, including BMI, Hb A1c, or triglycerides, a finding that deserves further investigation.
↵7 Nonstandard abbreviations:
- cardiovascular disease;
- Women's Health Study;
- Hb A1c,
- hemoglobin A1c;
- Copenhagen City Heart Study;
- high-sensitivity C-reactive protein;
- body mass index;
- hazard ratio;
- odds ratio.
Author Contributions: All authors confirmed they have contributed to the intellectual content of this paper and have met the following 3 requirements: (a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; and (c) final approval of the published article.
Authors' Disclosures of Potential Conflicts of Interest: Upon manuscript submission, all authors completed the Disclosures of Potential Conflict of Interest form. Potential conflicts of interest:
Employment or Leadership: None declared.
Consultant or Advisory Role: None declared.
Stock Ownership: None declared.
Honoraria: None declared.
Research Funding: S. Mora, National Heart, Lung, and Blood Institute (grant K08 HL094375). The Women's Health Study is supported by grants HL 43851, HL 080467, and CA 47988 from the National Heart, Lung, and Blood Institute and the National Cancer Insitute, the Donald W. Reynolds Foundation (Las Vegas, NV), and Leducq Foundation (Paris, France). The Copenhagen City Heart Study is supported by grants from The Danish Heart Foundation.
Expert Testimony: None declared.
Role of Sponsor: The funding organizations played no role in the design of study, choice of enrolled patients, review and interpretation of data, or preparation or approval of manuscript.
- Received for publication March 10, 2010.
- Accepted for publication April 26, 2010.
- © 2010 The American Association for Clinical Chemistry