From target discovery to clinical drug development with human genetics.

The substantial investments in human genetics and genomics made over the past three decades were anticipated to result in many innovative therapies. Here we investigate the extent to which these expectations have been met, excluding cancer treatments. In our search, we identified 40 germline genetic observations that led directly to new targets and subsequently to novel approved therapies for 36 rare and 4 common conditions. The median time between genetic target discovery and drug approval was 25 years. Most of the genetically driven therapies for rare diseases compensate for disease-causing loss-of-function mutations. The therapies approved for common conditions are all inhibitors designed to pharmacologically mimic the natural, disease-protective effects of rare loss-of-function variants. Large biobank-based genetic studies have the power to identify and validate a large number of new drug targets. Genetics can also assist in the clinical development phase of drugs-for example, by selecting individuals who are most likely to respond to investigational therapies. This approach to drug development requires investments into large, diverse cohorts of deeply phenotyped individuals with appropriate consent for genetically assisted trials. A robust framework that facilitates responsible, sustainable benefit sharing will be required to capture the full potential of human genetics and genomics and bring effective and safe innovative therapies to patients quickly.

Cardiovascular Pharmacogenetics: From Discovery of Genetic Association to Clinical Adoption of Derived Test.

Recent breakthroughs in human genetics and in information technologies have markedly expanded our understanding at the molecular level of the response to drugs, i.e., pharmacogenetics (PGx), across therapy areas. This review is restricted to PGx for cardiovascular (CV) drugs. First, we examined the PGx information in the labels approved by regulatory agencies in Europe, Japan, and North America and related recommendations from expert panels. Out of 221 marketed CV drugs, 36 had PGx information in their labels approved by one or more agencies. The level of annotations and recommendations varied markedly between agencies and expert panels. Clopidogrel is the only CV drug with consistent PGx recommendation (i.e., "actionable"). This situation prompted us to dissect the steps from discovery of a PGx association to clinical translation. We found 101 genome-wide association studies that investigated the response to CV drugs or drug classes. These studies reported significant associations for 48 PGx traits mapping to 306 genes. Six of these 306 genes are mentioned in the corresponding PGx labels or recommendations for CV drugs. Genomic analyses also highlighted the wide between-population differences in risk allele frequencies and the individual load of actionable PGx variants. Given the high attrition rate and the long road to clinical translation, additional work is warranted to identify and validate PGx variants for more CV drugs across diverse populations and to demonstrate the utility of PGx testing. To that end, pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond. SIGNIFICANCE STATEMENT: Despite spectacular breakthroughs in human molecular genetics and information technologies, consistent evidence supporting PGx testing in the cardiovascular area is limited to a few drugs. Additional work is warranted to discover and validate new PGx markers and demonstrate their utility. Pre-emptive PGx combining genomic profiling with electronic medical records opens unprecedented opportunities to improve healthcare, for CV diseases and beyond.

Are some children genetically predisposed to poor sleep? A polygenic risk study in the general population.

BACKGROUND: Twin studies show moderate heritability of sleep traits: 40% for insomnia symptoms and 46% for sleep duration. Genome-wide association studies (GWAS) have identified genetic variants involved in insomnia and sleep duration in adults, but it is unknown whether these variants affect sleep during early development. We assessed whether polygenic risk scores for insomnia (PRS-I) and sleep duration (PRS-SD) affect sleep throughout early childhood to adolescence. METHODS: We included 2,458 children of European ancestry (51% girls). Insomnia-related items of the Child Behavior Checklist were reported by mothers at child's age 1.5, 3, and 6 years. At 10-15 years, the Sleep Disturbance Scale for Children and actigraphy were assessed in a subsample (N = 975). Standardized PRS-I and PRS-SD (higher scores indicate genetic susceptibility for insomnia and longer sleep duration, respectively) were computed at multiple p-value thresholds based on largest GWAS to date. RESULTS: Children with higher PRS-I had more insomnia-related sleep problems between 1.5 and 15 years (BPRS-I < 0.001 = .09, 95% CI: 0.05; 0.14). PRS-SD was not associated with mother-reported sleep problems. A higher PRS-SD was in turn associated with longer actigraphically estimated sleep duration (BPRS-SD < 5e08 = .05, 95% CI: 0.001; 0.09) and more wake after sleep onset (BPRS-SD < 0.005 = .25, 95% CI: 0.04; 0.47) at 10-15 years, but these associations did not survive multiple testing correction. CONCLUSIONS: Children who are genetically predisposed to insomnia have more insomnia-like sleep problems, whereas those who are genetically predisposed to longer sleep have longer sleep duration, but are also more awake during the night in adolescence. This indicates that polygenic risk for sleep traits, based on GWAS in adults, affects sleep already in children.

Deep learning predicted perceived age is a reliable approach for analysis of facial ageing: A proof of principle study.

BACKGROUND: Perceived age (PA) has been associated with mortality, genetic variants linked to ageing and several age-related morbidities. However, estimating PA in large datasets is laborious and costly to generate, limiting its practical applicability. OBJECTIVES: To determine if estimating PA using deep learning-based algorithms results in the same associations with morbidities and genetic variants as human-estimated perceived age. METHODS: Self-supervised learning (SSL) and deep feature transfer (DFT) deep learning (DL) approaches were trained and tested on human-estimated PAs and their corresponding frontal face images of middle-aged to elderly Dutch participants (n = 2679) from a population-based study in the Netherlands. We compared the DL-estimated PAs with morbidities previously associated with human-estimated PA as well as genetic variants in the gene MC1R; we additionally tested the PA associations with MC1R in a new validation cohort (n = 1158). RESULTS: The DL approaches predicted PA in this population with a mean absolute error of 2.84 years (DFT) and 2.39 years (SSL). In the training-test dataset, we found the same significant (p < 0.05) associations for DL PA with osteoporosis, ARHL, cognition, COPD and cataracts and MC1R, as with human PA. We also found a similar but less significant association for SSL and DFT PAs (0.69 and 0.71 years per allele, p = 0.008 and 0.011, respectively) with MC1R variants in the validation dataset as that found with human, SSL and DFT PAs in the training-test dataset (0.79, 0.78 and 0.71 years per allele respectively; all p < 0.0001). CONCLUSIONS: Deep learning methods can automatically estimate PA from facial images with enough accuracy to replicate known links between human-estimated perceived age and several age-related morbidities. Furthermore, DL predicted perceived age associated with MC1R gene variants in a validation cohort. Hence, such DL PA techniques may be used instead of human estimations in perceived age studies thereby reducing time and costs.

Younger facial looks are associate with a lower likelihood of several age-related morbidities in the middle-aged to elderly.

BACKGROUND: Looking older for one's chronological age is associated with a higher mortality rate. Yet it remains unclear how perceived facial age relates to morbidity and the degree to which facial ageing reflects systemic ageing of the human body. OBJECTIVES: To investigate the association between ΔPA and age-related morbidities of different organ systems, where ΔPA represents the difference between perceived age (PA) and chronological age. METHODS: We performed a cross-sectional analysis on data from the Rotterdam Study, a population-based cohort study in the Netherlands. High-resolution facial photographs of 2679 men and women aged 51.5-87.8 years of European descent were used to assess PA. PA was estimated and scored in 5-year categories using these photographs by a panel of men and women who were blinded for chronological age and medical history. A linear mixed model was used to generate the mean PAs. The difference between the mean PA and chronological age was calculated (ΔPA), where a higher (positive) ΔPA means that the person looks younger for their age and a lower (negative) ΔPA that the person looks older. ΔPA was tested as a continuous variable for association with ageing-related morbidities including cardiovascular, pulmonary, ophthalmological, neurocognitive, renal, skeletal and auditory morbidities in separate regression analyses, adjusted for age and sex (model 1) and additionally for body mass index, smoking and sun exposure (model 2). RESULTS: We observed 5-year higher ΔPA (i.e. looking younger by 5 years for one's age) to be associated with less osteoporosis [odds ratio (OR) 0.76, 95% confidence interval (CI) 0.62-0.93], less chronic obstructive pulmonary disease (OR 0.85, 95% CI 0.77-0.95), less age-related hearing loss (model 2; B = -0.76, 95% CI -1.35 to -0.17) and fewer cataracts (OR 0.84, 95% CI 0.73-0.97), but with better global cognitive functioning (g-factor; model 2; B = 0.07, 95% CI 0.04-0.10). CONCLUSIONS: PA is associated with multiple morbidities and better cognitive function, suggesting that systemic ageing and cognitive ageing are, to an extent, externally visible in the human face.

Life-Course Genome-wide Association Study Meta-analysis of Total Body BMD and Assessment of Age-Specific Effects.

Bone mineral density (BMD) assessed by DXA is used to evaluate bone health. In children, total body (TB) measurements are commonly used; in older individuals, BMD at the lumbar spine (LS) and femoral neck (FN) is used to diagnose osteoporosis. To date, genetic variants in more than 60 loci have been identified as associated with BMD. To investigate the genetic determinants of TB-BMD variation along the life course and test for age-specific effects, we performed a meta-analysis of 30 genome-wide association studies (GWASs) of TB-BMD including 66,628 individuals overall and divided across five age strata, each spanning 15 years. We identified variants associated with TB-BMD at 80 loci, of which 36 have not been previously identified; overall, they explain approximately 10% of the TB-BMD variance when combining all age groups and influence the risk of fracture. Pathway and enrichment analysis of the association signals showed clustering within gene sets implicated in the regulation of cell growth and SMAD proteins, overexpressed in the musculoskeletal system, and enriched in enhancer and promoter regions. These findings reveal TB-BMD as a relevant trait for genetic studies of osteoporosis, enabling the identification of variants and pathways influencing different bone compartments. Only variants in ESR1 and close proximity to RANKL showed a clear effect dependency on age. This most likely indicates that the majority of genetic variants identified influence BMD early in life and that their effect can be captured throughout the life course.

Mendelian randomization study on vitamin D levels and osteoarthritis risk: a concise report.

OBJECTIVE: The role of vitamin D in OA is unclear and previous epidemiological studies have provided inconsistent results. We conducted a two-sample Mendelian randomization (MR) study to investigate the causal relationship between genetically determined serum vitamin D levels and hip/knee OA. METHODS: Six single-nucleotide polymorphisms (SNPs) associated with vitamin D levels in the Study of Underlying Genetic Determinants of Vitamin D and Highly Related Traits Consortium were selected as instrumental variables. Summary statistics of the SNPs effects on OA were derived from the Iceland and UK Biobank, comprising 23 877 knee OA cases, 17 151 hip OA cases and >562 000 controls. The control samples match the OA cases in age, sex and county of origin. RESULTS: The MR analyses showed no causal association between genetically determined vitamin D levels and knee OA [odds ratio (OR) 1.03 (95% CI 0.84, 1.26)] or hip OA [OR 1.06 (95% CI 0.83, 1.35)]. CONCLUSION: Genetic variations associated with low vitamin D serum levels are not associated with increased risk of hip or knee OA in community-dwelling older adults, suggesting that vitamin D levels are not causally linked to OA. It is therefore unlikely that vitamin D supplementation protects against hip or knee OA.

Associations Between Prenatal, Perinatal, and Early Childhood Vitamin D Status and Risk of Dental Caries at 6 Years.

BACKGROUND: Previous studies have suggested that insufficient concentrations of vitamin D are associated with dental caries in primary teeth, but evidence remains inconclusive. OBJECTIVES: We assessed the longitudinal associations between prenatal, perinatal, and early childhood serum 25-hydroxyvitamin D concentrations [25(OH)D] and the risk of dental caries in 6-year-old children. METHODS: This research was conducted within the Generation R Study, a large, multi-ethnic, prospective cohort study located in Rotterdam, the Netherlands. Dental caries were assessed in children using the decayed-missing-filled-primary teeth index at a mean age of 6.1 years (90% range, 4.8-9.1). We measured serum total 25(OH)D concentrations at 3 time points: prenatally (at 18-24 weeks of gestation), perinatally (at birth), and during early childhood (at age 6 years). We performed logistic regression analyses to determine the longitudinal association of serum 25(OH)D concentrations with caries risks in 5257 children. Additionally, we constructed a Genetic Risk Score (GRS) for the genetic predispositions to serum total 25(OH)D concentrations based on 6 vitamin D-related single nucleotide polymorphisms in a subsample of 3385 children. RESULTS: Children with severe prenatal and early childhood serum 25(OH)D deficiencies (<25 nmol/L) were more likely to be diagnosed with caries [OR, 1.56 (95% CI, 1.18-2.06) and 1.58 (95% CI, 1.10-2.25), respectively] than children with optimal concentrations (≥75 nmol/L). After adjustment for residuals of serum 25(OH)D concentrations at other time points, only the early childhood serum 25(OH)D concentration was inversely associated with the caries risk at 6 years (OR, 0.97; 95% CI, 0.95-0.98). However, our GRS analysis showed that children who are genetically predisposed to have lower serum 25(OH)D concentrations do not have a higher risk of developing caries in primary teeth. CONCLUSIONS: Our study suggests a weak association between serum 25(OH)D concentrations and risks of caries in primary teeth. Based on our results, we do not recommend vitamin D supplementation for the prevention of dental caries in children.

Whole-genome sequencing identifies EN1 as a determinant of bone density and fracture.

The extent to which low-frequency (minor allele frequency (MAF) between 1-5%) and rare (MAF ≤ 1%) variants contribute to complex traits and disease in the general population is mainly unknown. Bone mineral density (BMD) is highly heritable, a major predictor of osteoporotic fractures, and has been previously associated with common genetic variants, as well as rare, population-specific, coding variants. Here we identify novel non-coding genetic variants with large effects on BMD (ntotal = 53,236) and fracture (ntotal = 508,253) in individuals of European ancestry from the general population. Associations for BMD were derived from whole-genome sequencing (n = 2,882 from UK10K (ref. 10); a population-based genome sequencing consortium), whole-exome sequencing (n = 3,549), deep imputation of genotyped samples using a combined UK10K/1000 Genomes reference panel (n = 26,534), and de novo replication genotyping (n = 20,271). We identified a low-frequency non-coding variant near a novel locus, EN1, with an effect size fourfold larger than the mean of previously reported common variants for lumbar spine BMD (rs11692564(T), MAF = 1.6%, replication effect size = +0.20 s.d., Pmeta = 2 × 10(-14)), which was also associated with a decreased risk of fracture (odds ratio = 0.85; P = 2 × 10(-11); ncases = 98,742 and ncontrols = 409,511). Using an En1(cre/flox) mouse model, we observed that conditional loss of En1 results in low bone mass, probably as a consequence of high bone turnover. We also identified a novel low-frequency non-coding variant with large effects on BMD near WNT16 (rs148771817(T), MAF = 1.2%, replication effect size = +0.41 s.d., Pmeta = 1 × 10(-11)). In general, there was an excess of association signals arising from deleterious coding and conserved non-coding variants. These findings provide evidence that low-frequency non-coding variants have large effects on BMD and fracture, thereby providing rationale for whole-genome sequencing and improved imputation reference panels to study the genetic architecture of complex traits and disease in the general population.

Genome-wide association study identifies nine novel loci for 2D:4D finger ratio, a putative retrospective biomarker of testosterone exposure in utero.

The ratio of the length of the index finger to that of the ring finger (2D:4D) is sexually dimorphic and is commonly used as a non-invasive biomarker of prenatal androgen exposure. Most association studies of 2D:4D ratio with a diverse range of sex-specific traits have typically involved small sample sizes and have been difficult to replicate, raising questions around the utility and precise meaning of the measure. In the largest genome-wide association meta-analysis of 2D:4D ratio to date (N = 15 661, with replication N = 75 821), we identified 11 loci (9 novel) explaining 3.8% of the variance in mean 2D:4D ratio. We also found weak evidence for association (ß = 0.06; P = 0.02) between 2D:4D ratio and sensitivity to testosterone [length of the CAG microsatellite repeat in the androgen receptor (AR) gene] in females only. Furthermore, genetic variants associated with (adult) testosterone levels and/or sex hormone-binding globulin were not associated with 2D:4D ratio in our sample. Although we were unable to find strong evidence from our genetic study to support the hypothesis that 2D:4D ratio is a direct biomarker of prenatal exposure to androgens in healthy individuals, our findings do not explicitly exclude this possibility, and pathways involving testosterone may become apparent as the size of the discovery sample increases further. Our findings provide new insight into the underlying biology shaping 2D:4D variation in the general population.

Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits.

Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader allelic architecture of 12 anthropometric traits associated with height, body mass, and fat distribution in up to 267,616 individuals. We report 106 genome-wide significant signals that have not been previously identified, including 9 low-frequency variants pointing to functional candidates. Of the 106 signals, 6 are in genomic regions that have not been implicated with related traits before, 28 are independent signals at previously reported regions, and 72 represent previously reported signals for a different anthropometric trait. 71% of signals reside within genes and fine mapping resolves 23 signals to one or two likely causal variants. We confirm genetic overlap between human monogenic and polygenic anthropometric traits and find signal enrichment in cis expression QTLs in relevant tissues. Our results highlight the potential of WGS strategies to enhance biologically relevant discoveries across the frequency spectrum.

Identifying potential causal effects of age at menarche: a Mendelian randomization phenome-wide association study.

BACKGROUND: Age at menarche has been associated with various health outcomes. We aimed to identify potential causal effects of age at menarche on health-related traits in a hypothesis-free manner. METHODS: We conducted a Mendelian randomization phenome-wide association study (MR-pheWAS) of age at menarche with 17,893 health-related traits in UK Biobank (n = 181,318) using PHESANT. The exposure of interest was the genetic risk score for age at menarche. We conducted a second MR-pheWAS after excluding SNPs associated with BMI from the genetic risk score, to examine whether results might be due to the genetic overlap between age at menarche and BMI. We followed up a subset of health-related traits to investigate MR assumptions and seek replication in independent study populations. RESULTS: Of the 17,893 tests performed in our MR-pheWAS, we identified 619 associations with the genetic risk score for age at menarche at a 5% false discovery rate threshold, of which 295 were below a Bonferroni-corrected P value threshold. These included potential effects of younger age at menarche on lower lung function, higher heel bone-mineral density, greater burden of psychosocial/mental health problems, younger age at first birth, higher risk of childhood sexual abuse, poorer cardiometabolic health, and lower physical activity. After exclusion of variants associated with BMI, the genetic risk score for age at menarche was related to 37 traits at a 5% false discovery rate, of which 29 were below a Bonferroni-corrected P value threshold. We attempted to replicate findings for bone-mineral density, lung function, neuroticism, and childhood sexual abuse using 5 independent cohorts/consortia. While estimates for lung function, higher bone-mineral density, neuroticism, and childhood sexual abuse in replication cohorts were consistent with UK Biobank estimates, confidence intervals were wide and often included the null. CONCLUSIONS: The genetic risk score for age at menarche was related to a broad range of health-related traits. Follow-up analyses indicated imprecise evidence of an effect of younger age at menarche on greater bone-mineral density, lower lung function, higher neuroticism score, and greater risk of childhood sexual abuse in the smaller replication samples available; hence, these findings need further exploration when larger independent samples become available.

Do Vitamin D Level and Dietary Calcium Intake Modify the Association Between Loop Diuretics and Bone Health?

Loop diuretics (LD) may affect bone health by inhibiting renal calcium reuptake. However, whether vitamin D status and dietary calcium intake modify the association between LD and bone outcome is unclear. Therefore, this study aimed to evaluate whether vitamin D level or calcium intake modify the association between LD and various indices of bone health including bone mineral density (BMD) and Trabecular Bone Score (TBS). From The Rotterdam Study, a prospective population-based cohort study, we used data from 6990 participants aged > 45 year with a DXA scan (2002-2008), 6908 participants with femoral neck (FN)-BMD, 6677 participants with lumbar spine (LS)-BMD and 6476 participants with LS-TBS measurements. Use of LD was available from pharmacy dispensing records. Vitamin D (25(OH)D) level was measured in serum, and dietary calcium intake was measured with a validated food frequency questionnaire. Almost eight percent of the participants used LD. The association between LD (past-users compared to never-users) and LS-TBS was significantly different by 25(OH)D concentrations (P for interaction = 0.04). A significantly lower LS-TBS among LD past-users was observed for 25(OH)D ≥ 50 nmol/l compared to ≤ 20 and 20-50 nmol/l (ß = - 0.036, 95% CI - 0.060; - 0.013 vs. ß = - 0.012, 95% CI - 0.036; 0.013 and ß = - 0.031, 95% CI - 0.096; 0.034, respectively). However, no other significant effect modification by 25(OH)D and dietary calcium intake was found in the associations between LD use and bone health outcomes (P-interaction > 0.13). This study suggests that the association between LD use and indices of bone health is not consistently modified by vitamin D or dietary calcium intake.

Evaluation of shared genetic aetiology between osteoarthritis and bone mineral density identifies SMAD3 as a novel osteoarthritis risk locus.

Osteoarthritis (OA) is a common complex disease with high public health burden and no curative therapy. High bone mineral density (BMD) is associated with an increased risk of developing OA, suggesting a shared underlying biology. Here, we performed the first systematic overlap analysis of OA and BMD on a genome wide scale. We used summary statistics from the GEFOS consortium for lumbar spine (n = 31,800) and femoral neck (n = 32,961) BMD, and from the arcOGEN consortium for three OA phenotypes (hip, ncases=3,498; knee, ncases=3,266; hip and/or knee, ncases=7,410; ncontrols=11,009). Performing LD score regression we found a significant genetic correlation between the combined OA phenotype (hip and/or knee) and lumbar spine BMD (rg=0.18, P = 2.23 × 10-2), which may be driven by the presence of spinal osteophytes. We identified 143 variants with evidence for cross-phenotype association which we took forward for replication in independent large-scale OA datasets, and subsequent meta-analysis with arcOGEN for a total sample size of up to 23,425 cases and 236,814 controls. We found robustly replicating evidence for association with OA at rs12901071 (OR 1.08 95% CI 1.05-1.11, Pmeta=3.12 × 10-10), an intronic variant in the SMAD3 gene, which is known to play a role in bone remodeling and cartilage maintenance. We were able to confirm expression of SMAD3 in intact and degraded cartilage of the knee and hip. Our findings provide the first systematic evaluation of pleiotropy between OA and BMD, highlight genes with biological relevance to both traits, and establish a robust new OA genetic risk locus at SMAD3.

The association between dietary protein intake, energy intake and physical frailty: results from the Rotterdam Study.

Sufficient protein intake has been suggested to be important for preventing physical frailty, but studies show conflicting results which may be explained because not all studies address protein source and intake of other macronutrients and total energy. Therefore, we studied 2504 subjects with data on diet and physical frailty, participating in a large population-based prospective cohort among subjects aged 45+ years (the Rotterdam Study). Dietary intake was assessed with a FFQ. Frailty was defined according to the frailty phenotype as the presence of at least three out of the following five symptoms: weight loss, low physical activity, weakness, slowness and fatigue. We used multinomial logistic regression models to evaluate the independent association between protein intake and frailty using two methods: nutrient residual models and energy decomposition models. With every increase in 10 g total, plant or animal protein per d, the odds to be frail were 1·06 (95 % CI 0·98, 1·15), 0·87 (95 % CI 0·71, 1·07) and 1·07 (95 % CI 0·99, 1·15), respectively, using the nutrient residual method. Using the energy partition model, we observed that the odds to be frail were lower with higher vegetable protein intake (OR per 418·4 kJ (100 kcal): 0·61, 95 % CI 0·39, 0·97), however, results disappeared when adjusting for physical activity. For energy intake from any source we observed that with every 418·4 kJ (100 kcal) increase, the odds to be frail were 5 % lower (OR: 0·95, 95 % CI 0·93, 0·97). Our results suggest that energy intake, but not protein specifically, is associated with less frailty. Considering other macronutrients, physical activity and diet quality seems to be essential for future studies on protein and frailty.

Genetics of Bone and Muscle Interactions in Humans.

PURPOSE OF REVIEW: To summarize the evidence from recent studies on the shared genetics between bone and muscle in humans. RECENT FINDINGS: Genome-wide association studies (GWAS) have successfully identified a multitude of loci influencing the variability of different bone or muscle parameters, with multiple loci overlapping between the traits. In addition, joint analyses of multiple correlated musculoskeletal traits (i.e., multivariate GWAS) have underscored several genes with possible pleiotropic effects on both bone and muscle including MEF2C and SREBF1. Notably, several of the proposed pleiotropic genes have been validated using human cells or animal models. It is clear that the study of pleiotropy may provide novel insights into disease pathophysiology potentially leading to the identification of new treatment strategies that simultaneously prevent or treat both osteoporosis and sarcopenia. However, the role of muscle factors (myokines) that stimulate bone metabolism, as well as osteokines that affect muscles, is in its earliest stage of understanding.

Using Mendelian Randomization to Decipher Mechanisms of Bone Disease.

PURPOSE OF REVIEW: This review summarizes the basic principles of Mendelian randomization (MR) and provides evidence for the causal effect of multiple modifiable factors on bone outcomes. RECENT FINDINGS: Several studies using MR approach have provided support for the causal effect of obesity on bone mineral density (BMD). Strikingly, studies have failed to prove a causal association between elevated 25(OH) D concentrations and higher BMD in community-dwelling individuals. The MR approach has been successfully used to evaluate multiple factors related to bone mineral density variation and/or fracture risk. The MR approach avoids some of the classical observational study limitations and provides more robust causal evidence, ensuring bigger success of the clinical trials. The selection of interventions based on genetic evidence could have a substantial impact on clinical practice.

Evaluating the relationship between glycemic control and bone fragility within the UK Biobank: observational and one-sample Mendelian randomization analyses.

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 (HbA1c) and eBMD levels. At baseline, 4078 participants were diagnosed with T1D and 23 682 with T2D. HbA1c was used to classify patients into "adequately-" (ACD; n = 17 078; HbA1c < 7.0%/53 mmol/mol) and "inadequately-" (ICD; n = 10 682; HbA1c ≥ 7.0%/53 mmol/mol) controlled diabetes. In individuals with T1D, a 1% unit (11 mmol/mol) increase in HbA1c 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 HbA1c 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 HbA1c. 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 HbA1c 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 HbA1c and eBMD. We obtained evidence that lower HbA1c levels will reduce fracture risk in patients with T1D. In individuals with T2D, lowering HbA1c levels can mitigate the risk of fractures up to a threshold, beyond which the risk may begin to rise again.

A cost-effective sequencing method for genetic studies combining high-depth whole exome and low-depth whole genome.

Whole genome sequencing (WGS) at high-depth (30X) allows the accurate discovery of variants in the coding and non-coding DNA regions and helps elucidate the genetic underpinnings of human health and diseases. Yet, due to the prohibitive cost of high-depth WGS, most large-scale genetic association studies use genotyping arrays or high-depth whole exome sequencing (WES). Here we propose a cost-effective method which we call "Whole Exome Genome Sequencing" (WEGS), that combines low-depth WGS and high-depth WES with up to 8 samples pooled and sequenced simultaneously (multiplexed). We experimentally assess the performance of WEGS with four different depth of coverage and sample multiplexing configurations. We show that the optimal WEGS configurations are 1.7-2.0 times cheaper than standard WES (no-plexing), 1.8-2.1 times cheaper than high-depth WGS, reach similar recall and precision rates in detecting coding variants as WES, and capture more population-specific variants in the rest of the genome that are difficult to recover when using genotype imputation methods. We apply WEGS to 862 patients with peripheral artery disease and show that it directly assesses more known disease-associated variants than a typical genotyping array and thousands of non-imputable variants per disease-associated locus.

Association of Bone Mineral Density and Dementia: The Rotterdam Study.

BACKGROUND AND OBJECTIVES: Low bone mineral density (BMD) and dementia commonly co-occur in older individuals, with bone loss accelerating in patients with dementia due to physical inactivity and poor nutrition. However, uncertainty persists over the extent to which bone loss already exists before onset of dementia. Therefore, we investigated how dementia risk was affected by BMD at various skeletal regions in community-dwelling older adults. METHODS: In a prospective population-based cohort study, BMD at the femoral neck, lumbar spine, and total body and the trabecular bone score (TBS) were obtained using dual-energy X-ray absorptiometry in 3,651 participants free from dementia between 2002 and 2005. Persons at risk of dementia were followed up until January 1, 2020. For analyses of the association between BMD 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 and 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 disease (AD). During the whole follow-up period, participants with lower BMD at the femoral neck (per SD decrease) were more likely to develop all-cause dementia (hazard ratio [HR] total follow-up 1.12, 95% CI 1.02-1.23) and AD (HRtotal follow-up 1.14, 95% CI 1.02-1.28). Within the first 10 years after baseline, the risk of dementia was greatest for groups with the lowest tertile of BMD (femoral neck BMD, HR0-10 years 2.03; 95% CI 1.39-2.96; total body BMD, HR0-10 years 1.42; 95% CI 1.01-2.02; and TBS, HR0-10 years 1.59; 95% CI 1.11-2.28). DISCUSSION: In conclusion, participants with low femoral neck and total body BMD and low TBS were more likely to develop dementia. Further studies should focus on the predictive ability of BMD for dementia.