HIV-related diabetes: a complex interaction between liver damage, body mass and genetics?

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An American case-control study of type II diabetes in HIV-positive patients has found that liver damage, as measured by ALT levels, appears to be a unique factor in HIV-associated diabetes mellitus, suggesting that underlying liver pathology may be a marker for, or a predisposing factor of, diabetes. The study, which also found that body weight relative to height and genetic factors were also linked with diabetes, as in the general population, is published in the December 1st issue of the Journal of Acquired Immune Deficiency Syndrome.

Diabetes has been reported in 2 to 10% of people taking anti-HIV therapy, with prevalence growing as time on therapy increases. Recent studies have found that the risk of diabetes is four to five times greater in HIV-positive men on HAART compared with HIV-negative men, three times greater in HIV-positive women on HAART compared with HIV-negative women, and that co-infection with hepatitis C appears to further increase the risk of diabetes in HIV-positive people.

Researchers reviewed the medical records of HIV-positive patients receiving care between 1991 and 2000 at two New York clinics to find patients who fit the WHO criteria for diabetes: glucose greater than 200mg/dL or fasting glucose greater than 126 mg/dL on two separate occasions and/or receiving treatment for diabetes. They then matched two controls per case based on age, ethnicity, gender and length of clinic follow-up (the “matched” control group), and a further four controls per case based only on length of clinic follow-up (the “unmatched” control group) to determine if age, ethnicity or gender were associated with diabetes.

Glossary

diabetes

A group of diseases characterized by high levels of blood sugar (glucose). Type 1 diabetes occurs when the body fails to produce insulin, which is a hormone that regulates blood sugar. Type 2 diabetes occurs when the body either does not produce enough insulin or does not use insulin normally (insulin resistance). Common symptoms of diabetes include frequent urination, unusual thirst and extreme hunger. Some antiretroviral drugs may increase the risk of type 2 diabetes.

p-value

The result of a statistical test which tells us whether the results of a study are likely to be due to chance and would not be confirmed if the study was repeated. All p-values are between 0 and 1; the most reliable studies have p-values very close to 0. A p-value of 0.001 means that there is a 1 in 1000 probability that the results are due to chance and do not reflect a real difference. A p-value of 0.05 means there is a 1 in 20 probability that the results are due to chance. When a p-value is 0.05 or below, the result is considered to be ‘statistically significant’. Confidence intervals give similar information to p-values but are easier to interpret. 

matched

In a case-control study, a process to make the cases and the controls comparable with respect to extraneous factors. For example, each case is matched individually with a control subject on variables such as age, sex and HIV status. 

triglycerides

A blood fat (lipid). High levels are associated with atherosclerosis and are a risk factor for heart disease.

 

body mass index (BMI)

Body mass index, or BMI, is a measure of body size. It combines a person's weight with their height. The BMI gives an idea of whether a person has the correct weight for their height. Below 18.5 is considered underweight; between 18.5 and 25 is normal; between 25 and 30 is overweight; and over 30 is obese. Many BMI calculators can be found on the internet.

Over eight and a half years, 62 new cases of diabetes were identified, although 12 cases were excluded from this study due to the patients’ use of medications (specifically, growth hormone or megestrol acetate) associated with diabetes; another patient was excluded due to lack of a matched control case.

When comparing the patients with diabetes to unmatched controls, no statistically significant differences in age, gender or ethnicity were seen, although diabetes patients tended to be older, female and Hispanic.

In univariate analysis with matched controls, the patients with diabetes had a higher mean body mass index (BMI; 30 vs. 25.3kg/m2; p

  • BMI (Odds Ratio = 1.13/kg/m2; p=0.012)
  • family history (OR = 5.55; p=0.014)
  • and ALT (OR = 1.16 per 10U/L; p=0.012)

were associated with diabetes.

Although not statistically significant, hepatitis C co-infection was found to be more common in the patients with diabetes than in matched controls (51% vs.37%; p=0.066) and there was also greater protease inhibitor use amongst the diabetes patients than their matched controls (71% vs.58%; p=0.072). Although median triglyceride levels were found to be significant in univariate analysis (262 vs.145mg/dL; p=0.001), only half of the patients in the study had triglyceride levels available, and triglyceride levels did not remain significant in multivariate analysis.

The authors were unable to assess the impact of lipodystrophy on diabetes development due to the retrospective nature of the study, and the frequent lack of documentation. However, they suggest several steps that can be taken to assess and potentially reduce the risk of diabetes:

  • A routine family history in order to ascertain if any first-degree relatives have diabetes.
  • Individuals who are overweight should receive advice and support on how to lose weight.
  • Individuals with lipodystrophy, HCV co-infection, hepatic steatosis (fatty liver), and/or high triglycerides should be very closely monitored, and ideally, avoid PI-based HAART, or use PIs with a more favourable metabolic profile.
  • An oral glucose tolerance test may be a useful tool to assess at-risk patients without symptoms of diabetes.

They conclude that since they have found that family history, higher body mass index and reduced liver function are associated with diabetes, this “suggests a complex interrelation among genetic host factors, treatment-related metabolic changes, and liver injury in the pathogenesis of diabetes mellitus,” and call for larger, prospective studies to ascertain the relative contribution of each factor.

References

Yoon C et al. Case-control study of diabetes mellitus in HIV-infected patients. JAIDS 37 (4); 1464-1469, 2004.