Bone is a dynamic tissue which undergoes constant remodeling throughout the life span. Bone turnover is balanced with coupling of bone formation and resorption at various rates leading to continuous remodeling of bone. A study of bone turnover markers (BTMs) provides an insight of the dynamics of bone turnover in many metabolic bone disorders. An increase in bone turnover seen with aging and pathological states such as osteoporosis leads to deterioration of bone microarchitecture and thus contributes to an increase in the risk of fracture independent of low bone mineral density (BMD). These microarchitectural alterations affecting the bone quality can be assessed by BTMs and thus may serve as a complementary tool to BMD in the assessment of fracture risk. A systematic search of literature regarding BTMs was carried out using the PubMed database for the purpose of this review. Various reliable, rapid, and cost-effective automated assays of BTMs with good sensitivity are available for the management of osteoporosis. However, BTMs are subjected to various preanalytical and analytical variations necessitating strict sample collection and assays methods along with utilizing ethnicity-based reference standards for different populations. Estimation of fracture risk and monitoring the adherence and response to therapy, which is a challenge in a chronic, asymptomatic disease such as osteoporosis, are the most important applications of measuring BTMs. This review describes the physiology of bone remodeling, various conventional and novel BTMs, and BTM assays and their role in the assessment of fracture risk and monitoring response to treatment with antiresorptive or anabolic agents.

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Cardiometabolic disorders are frequently observed among those who have obesity as measured by body mass index (BMI). However, there is limited data available on the cardiometabolic profile of those who are non-obese by BMI but with a high body fat percentage (BFP), a phenotype frequently observed in the Indian population. We examined the prevalence of individuals with normal weight obesity (NWO) and the cardiometabolic profile of NWO individuals at high risk for type 2 diabetes(T2D) in a south Asian population. In the Kerala Diabetes Prevention Program, individuals aged between 30 to 60 years were screened using the Indian Diabetes Risk Score(IDRS) in 60 rural communities in the Indian state of Kerala. We used data from the baseline survey of this trial for this analysis which included 1147 eligible high diabetes risk individuals(IDRS >60). NWO was defined as BMI within the normal range and a high BFP (as per Asia-pacific ethnicity based cut-off); Non-obese (NO) as normal BMI and BFP and overtly obese (OB) as BMI ≥25 kg/m² irrespective of the BFP. Data on demographic, clinical and biochemical characteristics were collected using standardized questionnaires and protocols. Body fat percentage was assessed using TANITA body composition analyser (model SC330), based on bioelectrical impedance. The mean age of participants was 47.3 ± 7.5 years and 46% were women. The proportion with NWO was 32% (n = 364; 95% CI: 29.1 to 34.5%), NO was 17% (n = 200) and OB was 51% (n = 583). Among those with NWO, 19.7% had T2D, compared to 18.7% of those who were OB (p value = 0.45) and 8% with NO (p value = 0.003). Among those with NWO, mean systolic and diastolic blood pressure were 129 ± 20; 78 ± 12 mmHg, compared to 127 ± 17; 78±11 mmHg among those with OB (p value = 0.12;0.94) and 120 ± 16; 71±10 mmHg among with NO (p value<0.001; 0.001), respectively. A similar pattern of association was observed for LDL cholesterol and triglycerides. After adjusting for other risk factors, the odds of having diabetes (OR:2.72[95% CI:1.46–5.08]) and dyslipidemia (2.37[1.55–3.64]) was significantly more in individuals with NWO as compared to non-obese individuals. Almost one-third of this South Asian population, at high risk for T2D, had normal weight obesity. The significantly higher cardiometabolic risk associated with increased adiposity even in lower BMI individuals has important implications for recognition in clinical practice.

The South Asian population is rapidly ageing and sarcopenia is likely to become a huge burden in this region if proper action is not taken in time. Several sarcopenia guidelines are available, from the western world and from East Asia. However, these guidelines are not fully relevant for the South Asian healthcare ecosystem. South Asia is ethnically, culturally, and phenotypically unique. Additionally, the region is seeing an increase in non-communicable lifestyle disease and obesity. Both these conditions can lead to sarcopenia. However, secondary sarcopenia and sarcopenic obesity are either not dealt with in detail or are missing in other guidelines. Hence, we present a consensus on the screening, diagnosis and management of sarcopenia, which addresses the gaps in the current guidelines. This South Asian consensus gives equal importance to muscle function, muscle strength, and muscle mass; provides cost-effective clinical and easy to implement solutions; highlights secondary sarcopenia and sarcopenic obesity; lists commonly used biomarkers; reminds us that osteo-arthro-muscular triad should be seen as a single entity to address sarcopenia; stresses on prevention over treatment; and prioritizes non-pharmacological over pharmacological management. As literature is scarce from this region, the authors call for more South Asian research guided interventions.

Areal bone mineral density (aBMD) is currently the gold standard for the diagnosis of osteoporosis, however, it has its own pitfalls. Trabecular bone score (TBS), a novel tool in the evaluation of osteoporosis is an indirect indicator of bone microarchitecture. It is a textural index that evaluates pixel gray-level variations in the lumbar spine DXA (dual energy X-ray absorptiometry) image. Both cross-sectional and longitudinal studies have demonstrated that TBS may independently predict fragility fractures. TBS can also be used to adjust FRAX probabilities of fracture, though data available till date doesn't support any additional benefit. TBS also shows an improving trend with anti-osteoporotic treatment; however, the least significant change (LSC) is high that it takes more than 2 years for the change to manifest. TBS is also used in the evaluation of bone strength in cases of secondary osteoporosis. Though TBS predicts fracture risk independently in both genders, with the currently available data, it cannot be recommended as a standalone tool for decision regarding treatment of osteoporosis. TBS can be used as a tool to complement BMD in assessment of bone health. Additional studies are needed to assess its utility in clinical practice.