Samuel Ghatan

Functional interpretation is essential for understanding how genetic variants contribute to complex traits. Here, we identified and characterized regulatory variants in CD4+ T cells collected from 362 donors. We integrated molecular QTL mapping from single-cell RNA-seq profiles and chromatin accessibility with predicted variant effects from a deep learning model trained on chromatin accessibility data. We identified molecular features and transcription factor binding mechanisms underlying variant sharing and mediated effects across the modalities and approaches. While predicted variant effects correlated with molQTLs, only a small fraction of empirically detected molQTLs were discovered by predictive models. MolQTLs, primarily those affecting chromatin, indicated potential molecular drivers for 33% of immune-related GWAS loci, with the deep learning approach providing insights into 4.7% of GWAS loci. These results highlight the value of multi-omic data and systematic integration of empirical and predictive approaches to interpret regulatory effects of genetic variants.

Parental genetic variants can indirectly influence the traits of their child through the environment, a concept termed ‘genetic nurture’, or indirect genetic effects (IGE). This study estimated the direct genetic effects (DGE), via direct allelic transmission, and IGE shaping height, body mass index (BMI), and bone mineral density (BMD) in a multi-ethnic Dutch pediatric cohort, examining children with repeated measurements at ages six, nine, and thirteen. We imputed missing parental alleles from the phased haplotypes of 1 931 478 variants (MAF > 1%), utilizing snipar (single nucleotide imputation of parents). We constructed polygenic risk scores (PRSs) and jointly regressed the proband’s trait on their own PRS, while controlling for the proband’s maternal and paternal PRSs. A total of 4488 probands, with genetic data, underwent at least one of the three specified measurements. We found statistically significant DGE estimates for the three traits across ages six, nine and thirteen. For instance, 71%–77% of the BMI variance explained by the BMI-PRS can be attributed solely to the DGE. IGE estimates reached significance only for BMI measured at ages nine (Beta: 0.05, 95%CI: 0.01–0.09) and thirteen (Beta: 0.05, 95%CI: 0.01–0.09). Maternal and paternal IGE were of a similar magnitude in all our analyses. Our findings indicate that genetic nurture has limited influence on anthropometric traits during formative years. In addition, we do not observe differences between the maternal and paternal indirect contributions to these traits, opposite to the stronger maternal nurturing effect reported for other traits.

Most genetic variants associated with human traits and diseases lie in noncoding regions of the genome ¹ , and a key challenge is determining which genes they affect ^2,3 . A common approach has been to leverage associations between natural genetic variation and gene expression to identify expression quantitative trait loci (eQTLs) in the population ^4,5 . At the same time, a novel approach uses pooled CRISPR interference (CRISPRi) perturbations of noncoding loci with single-cell transcriptome sequencing ^6,7 . Here, we systematically harmonized and compared the results from these approaches across hundreds of genomic regions associated with blood cell traits. We find that while the two approaches sometimes identify the same target genes, there are considerable differences that affect biological inferences made from the data. CRISPRi preferentially maps highly proximal, constraint-enriched genes, whereas eQTLs recover multiple, often distal targets. By benchmarking against 1,075 gold-standard CRE–gene pairs linked to blood traits, we show that the two approaches identify largely distinct targets; when combined, they achieve a balance between accuracy and completeness of gene discovery. Our results offer guidance for improved design of CRISPRi and eQTL studies and highlight their joint potential as a powerful toolkit for interpreting disease-associated loci.

We aimed to: (1) examine the relationship between glycemic control, BMD estimated from heel ultrasound (eBMD) and fracture risk in individuals with type 1 (T1D) and type 2 diabetes (T2D) and (2) perform a one-sample Mendelian randomization (MR) study to explore potential causal associations between glycemic control, eBMD, and fractures. This study comprised 452 131 individuals from the UK Biobank with glycated hemoglobin A1C (HbA_1c) and eBMD levels. At baseline, 4078 participants were diagnosed with T1D and 23 682 with T2D. HbA_1c was used to classify patients into “adequately-” (ACD; n = 17 078; HbA_1c < 7.0%/53 mmol/mol) and “inadequately-” (ICD; n = 10 682; HbA_1c ≥ 7.0%/53 mmol/mol) controlled diabetes. In individuals with T1D, a 1% unit (11 mmol/mol) increase in HbA_1c levels was associated with a 12% increase in fracture risk (HR: 1.12, 95% CI [1.05-1.19]). Fracture risk was highest in individuals with T1D and ICD (HR 2.84, 95%CI [2.53, 3.19]), followed by those with ACD (HR 2.26, 95%CI [1.91, 2.69]), as compared to subjects without diabetes. Evidence for a non-linear association between HbA_1c and fracture risk was observed (F-test ANOVA p-value = 0.002) in individuals with T2D, with risk being increased at both low and high levels of HbA_1c. Fracture risk between the T2D ACD and ICD groups was not significantly different (HR: 0.97, 95%CI [0.91-1.16]), despite increased BMD. In MR analyses genetically predicted higher HbA_1c levels were not significantly associated with fracture risk (causal risk ratio: 1.04, 95%CI [0.95-1.14]). We did observe evidence of a non-linear causal association with eBMD (quadratic test p-value = 0.0002), indicating U-shaped relationship between HbA_1c and eBMD. We obtained evidence that lower HbA_1c levels will reduce fracture risk in patients with T1D. In individuals with T2D, lowering HbA_1c levels can mitigate the risk of fractures up to a threshold, beyond which the risk may begin to rise again.

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.

Aims/hypothesis: This study aimed to: (1) examine the relationship between glycemic control, bone mineral density estimated from heel ultrasound (eBMD) and fracture risk in individuals with type 1 and type 2 diabetes and (2) perform a one-sample Mendelian randomization study to explore potential linear and non-linear associations between glycemic control, eBMD, and fractures. Methods: This study comprised 452,131 individuals from the UK Biobank with glycated hemoglobin A1C (HbA1c) and eBMD levels. At baseline, 4,078 participants were diagnosed with type 1 diabetes and 23,682 with type 2 diabetes. HbA1c was used to classify patients into “adequately-” (ACD; n=17,078; HbA1c < 7.0%/53mmol/mol) and “inadequately-” (ICD; n=10,682; HbA1c ≥ 7.0%/53mmol/mol) controlled diabetes. The association between glycemic control (continuous and categorical) and eBMD was tested using linear regression, while fracture risk was estimated in Cox regression models, both controlling for covariates. Mendelian randomization (MR) was used to evaluate linear and non-linear causal relationships between HbA1c levels, fracture risk, and eBMD. Results: In individuals with type 1 diabetes, a 1% unit (11mmol/mol) increase in HbA1c levels was associated with a 12% increase in fracture risk (HR: 1.12, 95% CI [1.05-1.19]). Individuals with type 1 diabetes had lower eBMD in both the ICD (beta = −0.08, 95% CI [−0.11, −0.04]) and ACD (beta = −0.05, 95% CI [-0.11,0.01]) groups, as compared to subjects without diabetes. Fracture risk was highest in individuals with type 1 diabetes and ICD (HR 2.84, 95%CI [2.53, 3.19]), followed by those with ACD (HR 2.26, 95%CI [1.91, 2.69]). Individuals with type 2 diabetes had higher eBMD in both ICD (beta=0.12SD, 95%CI [0.10, 0.14]) and ACD (beta=0.07SD, 95%CI [0.05, 0.08]) groups. Significant evidence for a non-linear association between HbA1c and fracture risk was observed (F-test ANOVA p-value = 0.002) in individuals with type 2 diabetes, with risk being increased at both low and high levels of HbA1c. Fracture risk between the type 2 diabetes ACD and ICD groups was not significantly different (HR: 0.97, 95%CI [0.91-1.16]), despite increased BMD. In MR analyses genetically predicted higher HbA1c levels were not significantly associated with fracture risk (Causal Risk Ratio: 1.04, 95%CI [0.95-1.14]). However, disease stratified analyses were underpowered. We did observe evidence of a non-linear causal association with eBMD (quadratic test P-value = 0.0002), indicating U-shaped relationship between HbA1c and eBMD. Conclusion/interpretation: We obtained evidence that lower HbA1c levels will reduce fracture risk in patients with type 1 diabetes. In individuals with type 2 diabetes, lowering HbA1c levels can mitigate the risk of fractures up to a threshold, beyond which the risk may begin to rise once more. MR analyses demonstrated a causal relationship between genetically predicted HbA1c levels and eBMD, but not fracture risk.

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.

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 methods and the diverse treatment options for osteoporosis. Despite these advances and a growing incidence of osteoporosis, there is a large group being left undertreated or even untreated. This group of the under/untreated has been called the treatment gap. Concerns regarding rare side effects of the medications, such as osteonecrosis of the jaw, have been reported to be one of the many causes for the treatment gap. Also, this group seems not to be sufficiently informed of the major benefits of the treatment and the diversity in treatment options. Knowledge of these could be very helpful in improving compliance and hopefully reducing the gap. In this paper, we summarize recent evidence regarding the efficacy of the various treatment options, potential side effects, and the overall benefit of treatment.

Purpose of Review: Fractures are frequently encountered in paediatric practice. Although recurrent fractures in children usually unveil a monogenic syndrome, paediatric fracture risk could be shaped by the individual genetic background influencing the acquisition of bone mineral density, and therefore, the skeletal fragility as shown in adults. Here, we examine paediatric fractures from the perspective of monogenic and complex trait genetics. Recent Findings: Large-scale genome-wide studies in children have identified ~44 genetic loci associated with fracture or bone traits whereas ~35 monogenic diseases characterized by paediatric fractures have been described. Summary: Genetic variation can predispose to paediatric fractures through monogenic risk variants with a large effect and polygenic risk involving many variants of small effects. Studying genetic factors influencing peak bone attainment might help in identifying individuals at higher risk of developing early-onset osteoporosis and discovering drug targets to be used as bone restorative pharmacotherapies to prevent, or even reverse, bone loss later in life.

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.