Defining type 2 diabetes polygenic risk scores through colocalization and network-based clustering of metabolic trait genetic associations

Background: Type 2 diabetes (T2D) is a heterogeneous and polygenic disease. Previous studies have leveraged the highly polygenic and pleiotropic nature of T2D variants to partition the heterogeneity of T2D, in order to stratify patient risk and gain mechanistic insight. We expanded on these approaches by performing colocalization across GWAS traits while assessing the causality and directionality of genetic associations. Methods: We applied colocalization between T2D and 20 related metabolic traits, across 243 loci, to obtain inferences of shared casual variants. Network-based unsupervised hierarchical clustering was performed on variant-trait associations. Partitioned polygenic risk scores (PRSs) were generated for each cluster using T2D summary statistics and validated in 21,742 individuals with T2D from 3 cohorts. Inferences of directionality and causality were obtained by applying Mendelian randomization Steiger’s Z-test and further validated in a pediatric cohort without diabetes (aged 9–12 years old, n = 3866). Results: We identified 146 T2D loci that colocalized with at least one metabolic trait locus. T2D variants within these loci were grouped into 5 clusters. The clusters corresponded to the following pathways: obesity, lipodystrophic insulin resistance, liver and lipid metabolism, hepatic glucose metabolism, and beta-cell dysfunction. We observed heterogeneity in associations between PRSs and metabolic measures across clusters. For instance, the lipodystrophic insulin resistance (Beta − 0.08 SD, 95% CI [− 0.10–0.07], p = 6.50 × 10−32) and beta-cell dysfunction (Beta − 0.10 SD, 95% CI [− 0.12, − 0.08], p = 1.46 × 10−47) PRSs were associated to lower BMI. Mendelian randomization Steiger analysis indicated that increased T2D risk in these pathways was causally associated to lower BMI. However, the obesity PRS was conversely associated with increased BMI (Beta 0.08 SD, 95% CI 0.06–0.10, p = 8.0 × 10−33). Analyses within a pediatric cohort supported this finding. Additionally, the lipodystrophic insulin resistance PRS was associated with a higher odds of chronic kidney disease (OR 1.29, 95% CI 1.02–1.62, p = 0.03). Conclusions: We successfully partitioned T2D genetic variants into phenotypic pathways using a colocalization first approach. Partitioned PRSs were associated to unique metabolic and clinical outcomes indicating successful partitioning of disease heterogeneity. Our work expands on previous approaches by providing stronger inferences of shared causal variants, causality, and directionality of GWAS variant-trait associations.</p

Defining type 2 diabetes polygenic risk scores through colocalization and network-based clustering of metabolic trait genetic associations

Background: Type 2 diabetes (T2D) is a heterogeneous and polygenic disease. Previous studies have leveraged the highly polygenic and pleiotropic nature of T2D variants to partition the heterogeneity of T2D, in order to stratify patient risk and gain mechanistic insight. We expanded on these approaches by performing colocalization across GWAS traits while assessing the causality and directionality of genetic associations. Methods: We applied colocalization between T2D and 20 related metabolic traits, across 243 loci, to obtain inferences of shared casual variants. Network-based unsupervised hierarchical clustering was performed on variant-trait associations. Partitioned polygenic risk scores (PRSs) were generated for each cluster using T2D summary statistics and validated in 21,742 individuals with T2D from 3 cohorts. Inferences of directionality and causality were obtained by applying Mendelian randomization Steiger’s Z-test and further validated in a pediatric cohort without diabetes (aged 9–12 years old, n = 3866). Results: We identified 146 T2D loci that colocalized with at least one metabolic trait locus. T2D variants within these loci were grouped into 5 clusters. The clusters corresponded to the following pathways: obesity, lipodystrophic insulin resistance, liver and lipid metabolism, hepatic glucose metabolism, and beta-cell dysfunction. We observed heterogeneity in associations between PRSs and metabolic measures across clusters. For instance, the lipodystrophic insulin resistance (Beta − 0.08 SD, 95% CI [− 0.10–0.07], p = 6.50 × 10−32) and beta-cell dysfunction (Beta − 0.10 SD, 95% CI [− 0.12, − 0.08], p = 1.46 × 10−47) PRSs were associated to lower BMI. Mendelian randomization Steiger analysis indicated that increased T2D risk in these pathways was causally associated to lower BMI. However, the obesity PRS was conversely associated with increased BMI (Beta 0.08 SD, 95% CI 0.06–0.10, p = 8.0 × 10−33). Analyses within a pediatric cohort supported this finding. Additionally, the lipodystrophic insulin resistance PRS was associated with a higher odds of chronic kidney disease (OR 1.29, 95% CI 1.02–1.62, p = 0.03). Conclusions: We successfully partitioned T2D genetic variants into phenotypic pathways using a colocalization first approach. Partitioned PRSs were associated to unique metabolic and clinical outcomes indicating successful partitioning of disease heterogeneity. Our work expands on previous approaches by providing stronger inferences of shared causal variants, causality, and directionality of GWAS variant-trait associations.</p

Bone mineral density and the risk of incident dementia:A meta-analysis

Background: It is not known whether bone mineral density (BMD) measured at baseline or as the rate of decline prior to baseline (prior bone loss) is a stronger predictor of incident dementia or Alzheimer's disease (AD). Methods:We performed a meta-analysis of three longitudinal studies, the Framingham Heart Study (FHS), the Rotterdam Study (RS), and the Rush Memory and Aging Project (MAP), modeling the time to diagnosis of dementia as a function of BMD measures accounting for covariates. We included individuals with one or two BMD assessments, aged ≥60 years, and free of dementia at baseline with follow-up available. BMD was measured at the hip femoral neck using dual-energy X-ray absorptiometry (DXA), or at the heel calcaneus using quantitative ultrasound to calculate estimated BMD (eBMD). BMD at study baseline (“baseline BMD”) and annualized percentage change in BMD prior to baseline (“prior bone loss”) were included as continuous measures. The primary outcome was incident dementia diagnosis within 10 years of baseline, and incident AD was a secondary outcome. Baseline covariates included age, sex, body mass index, ApoE4 genotype, and education. Results: The combined sample size across all three studies was 4431 with 606 incident dementia diagnoses, 498 of which were AD. A meta-analysis of baseline BMD across three studies showed higher BMD to have a significant protective association with incident dementia with a hazard ratio of 0.47 (95% CI: 0.23–0.96; p = 0.038) per increase in g/cm2, or 0.91 (95% CI: 0.84–0.995) per standard deviation increase. We observed a significant association between prior bone loss and incident dementia with a hazard ratio of 1.30 (95% CI: 1.12–1.51; p &lt; 0.001) per percent increase in prior bone loss only in the FHS cohort. Conclusions: Baseline BMD but not prior bone loss was associated with incident dementia in a meta-analysis across three studies.</p

Type 2 Diabetes Mellitus and Vertebral Fracture Risk

Purpose of Review: The purpose of this review is to summarize the recently published evidence concerning vertebral fracture risk in individuals with diabetes mellitus. Recent Findings: Vertebral fracture risk is increased in individuals with T2DM. The presence of vertebral fractures in T2DM is associated with increased non-vertebral fracture risk and mortality. TBS could be helpful to estimate vertebral fracture risk in individuals with T2DM. An increased amount of bone marrow fat has been implicated in bone fragility in T2DM. Results from two recent studies show that both teriparatide and denosumab are effective in reducing vertebral fracture risk also in individuals with T2DM. Summary: Individuals with T2DM could benefit from systematic screening in the clinic for presence of vertebral fractures

The treatment gap in osteoporosis

Worldwide, there are millions of people who have been diagnosed with osteoporosis, a bone disease that increases the risk of fracture due to low bone mineral density and deterioration of bone architecture. In the US alone, there are approximately ten million men and women diagnosed with osteoporosis and this number is still growing. Diagnosis is made by measuring bone mineral density. Medications used for the treatment of osteoporosis are bisphosphonates, denosumab, raloxifene, and teriparatide. Recently, romosozumab has been added as well. In recent years, a number of advances have been made in the field of diagnostic m

Type 2 Diabetes Mellitus and Vertebral Fracture Risk

Purpose of Review: The purpose of this review is to summarize the recently published evidence concerning vertebral fracture risk in individuals with diabetes mellitus. Recent Findings: Vertebral fracture risk is increased in individuals with T2DM. The presence of vertebral fractures in T2DM is associated with increased non-vertebral fracture risk and mortality. TBS could be helpful to estimate vertebral fracture risk in individuals with T2DM. An increased amount of bone marrow fat has been implicated in bone fragility in T2DM. Results from two recent studies show that both teriparatide and denosumab are effective in reducing vertebral fracture risk also in individuals with T2DM. Summary: Individuals with T2DM could benefit from systematic screening in the clinic for presence of vertebral fractures

Microvascular Disease Associates with Larger Osteocyte Lacunae in Cortical Bone in Type 2 Diabetes Mellitus

ABSTRACT Clinical studies indicate that microvascular disease (MVD) affects bone microstructure and decreases bone strength in type 2 diabetes mellitus (T2D). Osteocytes are housed in small voids within the bone matrix and lacunae and act as sensors of mechanical forces in bone. These cells regulate osteoclastic bone resorption and osteoblastic bone formation as well as osteocytic perilacunar remodeling. We hypothesized that MVD changes morphometric osteocyte lacunar parameters in individuals with T2D. We collected iliac crest bone biopsies from 35 individuals (10 female, 25 male) with T2D with MVD (15%) or without MVD (21%) with a median age of 67 years (interquartile range [IQR] 62–72 years). The participants were included based on c‐peptide levels >700 pmol L−1, absence of anti‐GAD65 antibodies, and glycated hemoglobin (HbA1c) levels between 40 and 82 mmol mol−1 or 5.8% and 9.7%, respectively. We assessed osteocyte lacunar morphometric parameters in trabecular and cortical bone regions using micro‐computed tomography (micro‐CT) at a nominal resolution of 1.2 μm voxel size. The cortical osteocyte lacunar volume (Lc.V) was 7.7% larger (p = 0.05) and more spherical (Lc.Sr, p < 0.01) in the T2D + MVD group. Using linear regression, we found that lacunar density (Lc.N/BV) in trabecular but not cortical bone was associated with HbA1c (p < 0.05, R2 = 0.067) independently of MVD. Furthermore, Lc.V was larger and Lc.Sr higher in the center than in the periphery of the trabecular and cortical bone regions (p < 0.05). In conclusion, these data imply that MVD may impair skeletal integrity, possibly contributing to increased skeletal fragility in T2D complicated by MVD. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research

Bone mineral density and the risk of incident dementia: A meta-analysis

BACKGROUND: It is not known whether bone mineral density (BMD) measured at baseline or as the rate of decline prior to baseline (prior bone loss) is a stronger predictor of incident dementia or Alzheimer\u27s disease (AD). METHODS: We performed a meta-analysis of three longitudinal studies, the Framingham Heart Study (FHS), the Rotterdam Study (RS), and the Rush Memory and Aging Project (MAP), modeling the time to diagnosis of dementia as a function of BMD measures accounting for covariates. We included individuals with one or two BMD assessments, aged ≥60 years, and free of dementia at baseline with follow-up available. BMD was measured at the hip femoral neck using dual-energy X-ray absorptiometry (DXA), or at the heel calcaneus using quantitative ultrasound to calculate estimated BMD (eBMD). BMD at study baseline ( baseline BMD ) and annualized percentage change in BMD prior to baseline ( prior bone loss ) were included as continuous measures. The primary outcome was incident dementia diagnosis within 10 years of baseline, and incident AD was a secondary outcome. Baseline covariates included age, sex, body mass index, ApoE4 genotype, and education. RESULTS: The combined sample size across all three studies was 4431 with 606 incident dementia diagnoses, 498 of which were AD. A meta-analysis of baseline BMD across three studies showed higher BMD to have a significant protective association with incident dementia with a hazard ratio of 0.47 (95% CI: 0.23-0.96; p = 0.038) per increase in g/cm , or 0.91 (95% CI: 0.84-0.995) per standard deviation increase. We observed a significant association between prior bone loss and incident dementia with a hazard ratio of 1.30 (95% CI: 1.12-1.51; p \u3c 0.001) per percent increase in prior bone loss only in the FHS cohort. CONCLUSIONS: Baseline BMD but not prior bone loss was associated with incident dementia in a meta-analysis across three studies

Association of Bone Mineral Density and Dementia: The Rotterdam Study

BACKGROUND: & Objective: Low bone mineral density and dementia commonly co-occur in the elderly, with bone loss accelerating in dementia patients due to physical inactivity and poor nutrition. However, uncertainty persists over the extent to which bone loss already exists prior to the onset of dementia. Therefore, we investigated how dementia risk was affected by bone mineral density at various skeletal regions in community-dwelling older adults. METHODS: In a prospective population-based cohort study, bone mineral density at the femoral neck, lumbar spine, and total body and the trabecular bone score were obtained using dual-energy X-ray absorptiometry (DXA) in 3,651 participants free from dementia between 2002-2005. Persons at risk of dementia were followed up until 1 January 2020. For analyses of the association between bone mineral density at baseline and the risk of incident dementia, we used Cox proportional-hazards regression analyses, adjusting for age, sex, educational attainment, physical activity, smoking status, body mass index, systolic blood pressure, diastolic blood pressure, cholesterol level, high-density lipoprotein cholesterol, history of comorbidities (stroke and diabetes mellitus), and APOE genotype. RESULTS: Among the 3,651 participants (median age 72.3±10.0 years, 57.9% women), 688 (18.8%) developed incident dementia during a median of 11.1 years, of whom 528 (76.7%) developed Alzheimer's disease. During the whole follow-up, participants with lower bone mineral density at the femoral neck (per SD decrease) were more likely to develop all-cause dementia (Hazard ratio [HR] total follow-up: 1.12, 95% Confidential interval [CI]: 1.02-1.23) and Alzheimer's disease (HR total follow-up: 1.14, 95% CI: 1.02-1.28). Within the first ten years following baseline, the risk of dementia was greatest for groups with the lowest tertile of bone mineral density (femoral neck bone mineral density, HR0-10years 2.03; 95% CI, 1.39-2.96; total body bone mineral density, HR0-10years 1.42; 95% CI, 1.01-2.02; trabecular bone score, HR0-10years 1.59; 95% CI, 1.11-2.28). CONCLUSIONS: In conclusion, participants with low femoral neck and total body bone mineral density and low trabecular bone score were more likely to develop dementia. Further studies should focus on the predictive ability of bone mineral density for dementia