Differential Role of Type 2 Diabetes as a Risk Factor for Tuberculosis in the Elderly versus Younger Adults.
Blanca I RestrepoJulia M ScordoGénesis P Aguillón-DuránDoris AyalaAna Paulina Quirino-CerrilloRaúl Loera-SalazarAmerica Cruz-GonzálezJose A CasoMateo Joya-AyalaEsperanza Milagros García-OropesaAlejandra B SalinasLeonardo MartinezLarry S SchlesingerJordi B TorrellesJoanne TurnerPublished in: Pathogens (Basel, Switzerland) (2022)
The elderly are understudied despite their high risk of tuberculosis (TB). We sought to identify factors underlying the lack of an association between TB and type 2 diabetes (T2D) in the elderly, but not adults. We conducted a case-control study in elderly (≥65 years old; ELD) vs. younger adults (young/middle-aged adults (18-44/45-64 years old; YA|MAA) stratified by TB and T2D, using a research study population (n = 1160) and TB surveillance data (n = 8783). In the research study population the adjusted odds ratio (AOR) of TB in T2D was highest in young adults (AOR 6.48) but waned with age becoming non-significant in the elderly. Findings were validated using TB surveillance data. T2D in the elderly (vs. T2D in younger individuals) was characterized by better glucose control (e.g., lower hyperglycemia or HbA1c), lower insulin resistance, more sulphonylureas use, and features of less inflammation (e.g., lower obesity, neutrophils, platelets, anti-inflammatory use). We posit that differences underlying glucose dysregulation and inflammation in elderly vs. younger adults with T2D, contribute to their differential association with TB. Studies in the elderly provide valuable insights into TB-T2D pathogenesis, e.g., here we identified insulin resistance as a novel candidate mechanism by which T2D may increase active TB risk.
Keyphrases
- middle aged
- mycobacterium tuberculosis
- type diabetes
- insulin resistance
- community dwelling
- young adults
- metabolic syndrome
- public health
- adipose tissue
- pulmonary tuberculosis
- glycemic control
- skeletal muscle
- physical activity
- emergency department
- machine learning
- cardiovascular disease
- weight loss
- high fat diet induced
- hiv aids
- human immunodeficiency virus