Polygenic and transcriptional risk scores identify chronic obstructive pulmonary disease subtypes.

Rationale: Genetic variants and gene expression predict risk of chronic obstructive pulmonary disease (COPD), but their effect on COPD heterogeneity is unclear. Objectives: Define high-risk COPD subtypes using both genetics (polygenic risk score, PRS) and blood gene expression (transcriptional risk score, TRS) and assess differences in clinical and molecular characteristics. Methods: We defined high-risk groups based on PRS and TRS quantiles by maximizing differences in protein biomarkers in a COPDGene training set and identified these groups in COPDGene and ECLIPSE test sets. We tested multivariable associations of subgroups with clinical outcomes and compared protein-protein interaction networks and drug repurposing analyses between high-risk groups. Measurements and Main Results: We examined two high-risk omics-defined groups in non-overlapping test sets (n=1,133 NHW COPDGene, n=299 African American (AA) COPDGene, n=468 ECLIPSE). We defined "High activity" (low PRS/high TRS) and "severe risk" (high PRS/high TRS) subgroups. Participants in both subgroups had lower body-mass index (BMI), lower lung function, and alterations in metabolic, growth, and immune signaling processes compared to a low-risk (low PRS, low TRS) reference subgroup. "High activity" but not "severe risk" participants had greater prospective FEV 1 decline (COPDGene: -51 mL/year; ECLIPSE: - 40 mL/year) and their proteomic profiles were enriched in gene sets perturbed by treatment with 5-lipoxygenase inhibitors and angiotensin-converting enzyme (ACE) inhibitors. Conclusions: Concomitant use of polygenic and transcriptional risk scores identified clinical and molecular heterogeneity amongst high-risk individuals. Proteomic and drug repurposing analysis identified subtype-specific enrichment for therapies and suggest prior drug repurposing failures may be explained by patient selection.

Examining the Effect of Genes on Depression as Mediated by Smoking and Modified by Sex.

Depression is heritable, differs by sex, and has environmental risk factors such as cigarette smoking. However, the effect of single nucleotide polymorphisms (SNPs) on depression through cigarette smoking and the role of sex is unclear. In order to examine the association of SNPs with depression and smoking in the UK Biobank with replication in the COPDGene study, we used counterfactual-based mediation analysis to test the indirect or mediated effect of SNPs on broad depression through the log of pack-years of cigarette smoking, adjusting for age, sex, current smoking status, and genetic ancestry (via principal components). In secondary analyses, we adjusted for age, sex, current smoking status, genetic ancestry (via principal components), income, education, and living status (urban vs. rural). In addition, we examined sex-stratified mediation models and sex-moderated mediation models. For both analyses, we adjusted for age, current smoking status, and genetic ancestry (via principal components). In the UK Biobank, rs6424532 [LOC105378800] had a statistically significant indirect effect on broad depression through the log of pack-years of cigarette smoking (p = 4.0 × 10-4) among all participants and a marginally significant indirect effect among females (p = 0.02) and males (p = 4.0 × 10-3). Moreover, rs10501696 [GRM5] had a marginally significant indirect effect on broad depression through the log of pack-years of cigarette smoking (p = 0.01) among all participants and a significant indirect effect among females (p = 2.2 × 10-3). In the secondary analyses, the sex-moderated indirect effect was marginally significant for rs10501696 [GRM5] on broad depression through the log of pack-years of cigarette smoking (p = 0.01). In the COPDGene study, the effect of an SNP (rs10501696) in GRM5 on depressive symptoms and medication was mediated by log of pack-years (p = 0.02); however, no SNPs had a sex-moderated mediated effect on depressive symptoms. In the UK Biobank, we found SNPs in two genes [LOC105378800, GRM5] with an indirect effect on broad depression through the log of pack-years of cigarette smoking. In addition, the indirect effect for GRM5 on broad depression through smoking may be moderated by sex. These results suggest that genetic regions associated with broad depression may be mediated by cigarette smoking and this relationship may be moderated by sex.

Late-Stage Skeletal Muscle Transcriptome in Duchenne muscular dystrophy shows a BMP4-Induced Molecular Signature.

Duchenne muscular dystrophy (DMD) is a fatal X-linked recessive disease due to loss-of-function mutations in the DYSTROPHIN gene. DMD-related skeletal muscle wasting is typified by an aberrant immune response involving upregulation of TGFß family of cytokines. We previously demonstrated that bone morphogenetic protein 4 (BMP4) is increased in DMD and BMP4 stimulation induces a 20-fold upregulation of Smad8 transcription. However, the role of BMP4 in severely affected DMD skeletal muscle is unknown. We hypothesized that transcriptomic signatures in severely affected human DMD skeletal muscle are driven by BMP4 signaling. Transcriptomes from skeletal muscle biopsies of late-stage DMD vs. non-DMD controls and C2C12 muscle cells with or without BMP4 stimulation were generated by RNA-Seq and analyzed for single transcript differential expression as well as by Ingenuity Pathway Analysis and weighted gene co-expression network analyses. A total of 2,328 and 5,291 transcripts in the human muscle and C2C12 muscle cells, respectively, were differentially expressed. We identified an overlapping molecular signature of 1,027 genes dysregulated in DMD muscle that were induced in BMP4-stimulated C2C12 muscle cells. Highly upregulated DMD transcripts that overlapped with BMP4-stimulated C2C12 muscle cells included ADAMTS3, HCAR2, SERPING1, SMAD8 , and UNC13C. The DMD transcriptome was characterized by dysregulation of pathways involving immune function, extracellular matrix remodeling, and metabolic/mitochondrial function. In summary, we define a late-stage DMD skeletal muscle transcriptome that substantially overlaps with the BMP4-induced molecular signature in C2C12 muscle cells. This supports BMP4 as a disease-driving regulator of transcriptomic changes in late-stage DMD skeletal muscle and expands our understanding of the evolution of dystrophic signaling pathways and their associated gene networks that could be explored for therapeutic development.

Differentially co-expressed myofibre transcripts associated with abnormal myofibre proportion in chronic obstructive pulmonary disease.

BACKGROUND: Skeletal muscle dysfunction is a common extrapulmonary manifestation of chronic obstructive pulmonary disease (COPD). Alterations in skeletal muscle myosin heavy chain expression, with reduced type I and increased type II myosin heavy chain expression, are associated with COPD severity when studied in largely male cohorts. The objectives of this study were (1) to define an abnormal myofibre proportion phenotype in both males and females with COPD and (2) to identify transcripts and transcriptional networks associated with abnormal myofibre proportion in COPD. METHODS: Forty-six participants with COPD were assessed for body composition, strength, endurance and pulmonary function. Skeletal muscle biopsies from the vastus lateralis were assayed for fibre-type distribution and cross-sectional area via immunofluorescence microscopy and RNA-sequenced to generate transcriptome-wide gene expression data. Sex-stratified k-means clustering of type I and IIx/IIax fibre proportions was used to define abnormal myofibre proportion in participants with COPD and contrasted with previously defined criteria. Single transcripts and weighted co-expression network analysis modules were tested for correlation with the abnormal myofibre proportion phenotype. RESULTS: Abnormal myofibre proportion was defined in males with COPD (n = 29) as <18% type I and/or >22% type IIx/IIax fibres and in females with COPD (n = 17) as <36% type I and/or >12% type IIx/IIax fibres. Half of the participants with COPD were classified as having an abnormal myofibre proportion. Participants with COPD and an abnormal myofibre proportion had lower median handgrip strength (26.1 vs. 34.0 kg, P = 0.022), 6-min walk distance (300 vs. 353 m, P = 0.039) and forced expiratory volume in 1 s-to-forced vital capacity ratio (0.42 vs. 0.48, P = 0.041) compared with participants with COPD and normal myofibre proportions. Twenty-nine transcripts were associated with abnormal myofibre proportions in participants with COPD, with the upregulated NEB, TPM1 and TPM2 genes having the largest fold differences. Co-expression network analysis revealed that two transcript modules were significantly positively associated with the presence of abnormal myofibre proportions. One of these co-expression modules contained genes classically associated with muscle atrophy, as well as transcripts associated with both type I and type II myofibres, and was enriched for genetic loci associated with bone mineral density. CONCLUSIONS: Our findings indicate that there are significant transcriptional alterations associated with abnormal myofibre proportions in participants with COPD. Transcripts canonically associated with both type I and type IIa fibres were enriched in a co-expression network associated with abnormal myofibre proportion, suggesting altered transcriptional regulation across multiple fibre types.

Proteomics and Machine Learning in the Prediction and Explanation of Low Pectoralis Muscle Area.

Low muscle mass is associated with numerous adverse outcomes independent of other associated comorbid diseases. We aimed to predict and understand an individual's risk for developing low muscle mass using proteomics and machine learning. We identified 8 biomarkers associated with low pectoralis muscle area (PMA). We built 3 random forest classification models that used either clinical measures, feature selected biomarkers, or both to predict development of low PMA. The area under the receiver operating characteristic curve for each model was: clinical-only = 0.646, biomarker-only = 0.740, and combined = 0.744. We displayed the heterogenetic nature of an individual's risk for developing low PMA and identified 2 distinct subtypes of participants who developed low PMA. While additional validation is required, our methods for identifying and understanding individual and group risk for low muscle mass could be used to enable developments in the personalized prevention of low muscle mass.

Genetically Predicted Body Mass Index and Mortality in COPD.

RATIONALE: BMI is associated with COPD mortality, but the underlying mechanisms are unclear. The effect of genetic variants aggregated into a polygenic score may elucidate causal mechanisms and predict risk. OBJECTIVES: To examine the associations of genetically predicted BMI with all-cause and cause-specific mortality in COPD. METHODS: We developed a polygenic score for BMI (PGSBMI) and tested for associations of the PGSBMI with all-cause, respiratory, and cardiovascular mortality in participants with COPD from the COPDGene, ECLIPSE, and Framingham Heart studies. We calculated the difference between measured BMI and PGS-predicted BMI (BMIdiff) and categorized participants into groups of discordantly low (BMIdiff < 20th percentile), concordant (BMIdiff between 20th - 80th percentile), and discordantly high (BMIdiff > 80th percentile) BMI. We applied Cox models, examined potential non-linear associations of the PGSBMI and BMIdiff with mortality, and summarized results with meta-analysis. MEASUREMENTS AND MAIN RESULTS: We observed significant non-linear associations of measured BMI and BMIdiff, but not PGSBMI, with all-cause mortality. In meta-analyses, a one standard deviation increase in the PGSBMI was associated with an increased hazard for cardiovascular mortality (HR=1.29, 95% CI=1.12-1.49), but not with respiratory or all-cause mortality. Compared to participants with concordant measured and genetically predicted BMI, those with discordantly low BMI had higher mortality risk for all-cause (HR=1.57, CI=1.41-1.74) and respiratory death (HR=2.01, CI=1.61-2.51). CONCLUSIONS: In people with COPD, higher genetically predicted BMI is associated with higher cardiovascular mortality but not respiratory mortality. Individuals with discordantly low BMI have higher all-cause and respiratory mortality compared to those with concordant BMI.

Gene polymorphisms associated with heterogeneity and senescence characteristics of sarcopenia in chronic obstructive pulmonary disease.

BACKGROUND: Sarcopenia, or loss of skeletal muscle mass and decreased contractile strength, contributes to morbidity and mortality in patients with chronic obstructive pulmonary disease (COPD). The severity of sarcopenia in COPD is variable, and there are limited data to explain phenotype heterogeneity. Others have shown that COPD patients with sarcopenia have several hallmarks of cellular senescence, a potential mechanism of primary (age-related) sarcopenia. We tested if genetic contributors explain the variability in sarcopenic phenotype and accelerated senescence in COPD. METHODS: To identify gene variants [single nucleotide polymorphisms (SNPs)] associated with sarcopenia in COPD, we performed a genome-wide association study (GWAS) of fat free mass index (FFMI) in 32 426 non-Hispanic White (NHW) UK Biobank participants with COPD. Several SNPs within the fat mass and obesity-associated (FTO) gene were associated with sarcopenia that were validated in an independent COPDGene cohort (n = 3656). Leucocyte telomere length quantified in the UK Biobank cohort was used as a marker of senescence. Experimental validation was done by genetic depletion of FTO in murine skeletal myotubes exposed to prolonged intermittent hypoxia or chronic hypoxia because hypoxia contributes to sarcopenia in COPD. Molecular biomarkers for senescence were also quantified with FTO depletion in murine myotubes. RESULTS: Multiple SNPs located in the FTO gene were associated with sarcopenia in addition to novel SNPs both within and in proximity to the gene AC090771.2, which transcribes long non-coding RNA (lncRNA). To replicate our findings, we performed a GWAS of FFMI in NHW subjects from COPDGene. The SNP most significantly associated with FFMI was on chromosome (chr) 16, rs1558902A > T in the FTO gene (ß = 0.151, SE = 0.021, P = 1.40 × 10-12 for UK Biobank |ß= 0.220, SE = 0.041, P = 9.99 × 10-8 for COPDGene) and chr 18 SNP rs11664369C > T nearest to the AC090771.2 gene (ß = 0.129, SE = 0.024, P = 4.64 × 10-8 for UK Biobank |ß = 0.203, SE = 0.045, P = 6.38 × 10-6 for COPDGene). Lower handgrip strength, a measure of muscle strength, but not FFMI was associated with reduced telomere length in the UK Biobank. Experimentally, in vitro knockdown of FTO lowered myotube diameter and induced a senescence-associated molecular phenotype, which was worsened by prolonged intermittent hypoxia and chronic hypoxia. CONCLUSIONS: Genetic polymorphisms of FTO and AC090771.2 were associated with sarcopenia in COPD in independent cohorts. Knockdown of FTO in murine myotubes caused a molecular phenotype consistent with senescence that was exacerbated by hypoxia, a common condition in COPD. Genetic variation may interact with hypoxia and contribute to variable severity of sarcopenia and skeletal muscle molecular senescence phenotype in COPD.

Associations Between Muscle Weakness and Clinical Outcomes in Current and Former Smokers.

Introduction: Smokers with chronic obstructive pulmonary disease (COPD) are at increased risk of muscle weakness. There are limited data describing weakness in smokers with normal spirometry and preserved ratio-impaired spirometry (PRISm), 2 subgroups at risk of respiratory symptom burden and activity limitations. In this study, we evaluated the associations of 2 weakness measures, sit-to-stand (STS) and handgrip strength (HGS), with clinical outcomes in smokers with COPD, normal spirometry, and PRISm. Methods: We evaluated 1972 current and former smokers from the COPD Genetic Epidemiology (COPDGene®) cohort with STS and HGS measurements at their 10-year study visit. Multivariable regression modeling was used to assess associations between weakness measures and the 6-minute walk distance (6MWD) test, the St George's Respiratory Questionnaire (SGRQ), the Short-Form-36 (SF-36), severe exacerbations, and prospective mortality, reported as standardized coefficients (ß), odds ratios (ORs), or hazard ratios (HRs). Results: Compared with HGS, STS was more strongly associated with the 6MWD (ß=0.45, p<0.001 versus. ß=0.25, p<0.001), SGRQ (ß=-0.24, p<0.001 versus ß=-0.18, p<0.001), SF-36 Physical Functioning (ß=0.36, p<0.001 versus ß=0.25, p<0.001), severe exacerbations (OR 0.95, p=0.04 versus OR 0.97, p=0.01), and prospective mortality (HR 0.83, p=0.001 versus HR 0.94, p=0.03). Correlations remained after stratification by spirometric subgroups. Compared with males, females had larger magnitude effect sizes between STS and clinical outcomes. Conclusions: STS and HGS are easy to perform weakness measures that provide important information about functional performance, health-related quality of life, severe exacerbations, and survival in smokers, regardless of spirometric subgroup. This iterates the importance of screening current and former smokers for weakness in the outpatient setting.

Whole-exome sequence analysis of anthropometric traits illustrates challenges in identifying effects of rare genetic variants.

Anthropometric traits, measuring body size and shape, are highly heritable and significant clinical risk factors for cardiometabolic disorders. These traits have been extensively studied in genome-wide association studies (GWASs), with hundreds of genome-wide significant loci identified. We performed a whole-exome sequence analysis of the genetics of height, body mass index (BMI) and waist/hip ratio (WHR). We meta-analyzed single-variant and gene-based associations of whole-exome sequence variation with height, BMI, and WHR in up to 22,004 individuals, and we assessed replication of our findings in up to 16,418 individuals from 10 independent cohorts from Trans-Omics for Precision Medicine (TOPMed). We identified four trait associations with single-nucleotide variants (SNVs; two for height and two for BMI) and replicated the LECT2 gene association with height. Our expression quantitative trait locus (eQTL) analysis within previously reported GWAS loci implicated CEP63 and RFT1 as potential functional genes for known height loci. We further assessed enrichment of SNVs, which were monogenic or syndromic variants within loci associated with our three traits. This led to the significant enrichment results for height, whereas we observed no Bonferroni-corrected significance for all SNVs. With a sample size of ∼20,000 whole-exome sequences in our discovery dataset, our findings demonstrate the importance of genomic sequencing in genetic association studies, yet they also illustrate the challenges in identifying effects of rare genetic variants.

Novel genetic loci associated with osteoarthritis in multi-ancestry analyses in the Million Veteran Program and UK Biobank.

Osteoarthritis is a common progressive joint disease. As no effective medical interventions are available, osteoarthritis often progresses to the end stage, in which only surgical options such as total joint replacement are available. A more thorough understanding of genetic influences of osteoarthritis is essential to develop targeted personalized approaches to treatment, ideally long before the end stage is reached. To date, there have been no large multiancestry genetic studies of osteoarthritis. Here, we leveraged the unique resources of 484,374 participants in the Million Veteran Program and UK Biobank to address this gap. Analyses included participants of European, African, Asian and Hispanic descent. We discovered osteoarthritis-associated genetic variation at 10 loci and replicated findings from previous osteoarthritis studies. We also present evidence that some osteoarthritis-associated regions are robust to population ancestry. Drug repurposing analyses revealed enrichment of targets of several medication classes and provide potential insight into the etiology of beneficial effects of antiepileptics on osteoarthritis pain.

Increased chest CT derived bone and muscle measures capture markers of improved morbidity and mortality in COPD.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a disease of accelerated aging and is associated with comorbid conditions including osteoporosis and sarcopenia. These extrapulmonary conditions are highly prevalent yet frequently underdiagnosed and overlooked by pulmonologists in COPD treatment and management. There is evidence supporting a role for bone-muscle crosstalk which may compound osteoporosis and sarcopenia risk in COPD. Chest CT is commonly utilized in COPD management, and we evaluated its utility to identify low bone mineral density (BMD) and reduced pectoralis muscle area (PMA) as surrogates for osteoporosis and sarcopenia. We then tested whether BMD and PMA were associated with morbidity and mortality in COPD. METHODS: BMD and PMA were analyzed from chest CT scans of 8468 COPDGene participants with COPD and controls (smoking and non-smoking). Multivariable regression models tested the relationship of BMD and PMA with measures of function (6-min walk distance (6MWD), handgrip strength) and disease severity (percent emphysema and lung function). Multivariable Cox proportional hazards models were used to evaluate the relationship between sex-specific quartiles of BMD and/or PMA derived from non-smoking controls with all-cause mortality. RESULTS: COPD subjects had significantly lower BMD and PMA compared with controls. Higher BMD and PMA were associated with increased physical function and less disease severity. Participants with the highest BMD and PMA quartiles had a significantly reduced mortality risk (36% and 46%) compared to the lowest quartiles. CONCLUSIONS: These findings highlight the potential for CT-derived BMD and PMA to characterize osteoporosis and sarcopenia using equipment available in the pulmonary setting.

Update on the Etiology, Assessment, and Management of COPD Cachexia: Considerations for the Clinician.

Cachexia is a commonly observed but frequently neglected extra-pulmonary manifestation in patients with chronic obstructive pulmonary disease (COPD). Cachexia is a multifactorial syndrome characterized by severe loss of body weight, muscle, and fat, as well as increased protein catabolism. COPD cachexia places a high burden on patients (eg, increased mortality risk and disease burden, reduced exercise capacity and quality of life) and the healthcare system (eg, increased number, length, and cost of hospitalizations). The etiology of COPD cachexia involves a complex interplay of non-modifiable and modifiable factors (eg, smoking, hypoxemia, hypercapnia, physical inactivity, energy imbalance, and exacerbations). Addressing these modifiable factors is needed to prevent and treat COPD cachexia. Oral nutritional supplementation combined with exercise training should be the primary multimodal treatment approach. Adding a pharmacological agent might be considered in some, but not all, patients with COPD cachexia. Clinicians and researchers should use longitudinal measures (eg, weight loss, muscle mass loss) instead of cross-sectional measures (eg, low body mass index or fat-free mass index) where possible to evaluate patients with COPD cachexia. Lastly, in future research, more detailed phenotyping of cachectic patients to enable a better comparison of included patients between studies, prospective longitudinal studies, and more focus on the impact of exacerbations and the role of biomarkers in COPD cachexia, are highly recommended.

Comparative transcriptomics in human COPD reveals dysregulated genes uniquely expressed in ferrets.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a progressive lung disease with poor treatment options. However, most mouse models of COPD produce a primarily emphysematous disease not recapitulating clinically meaningful COPD features like chronic bronchitis. METHODS: Wild-type ferrets (Mustela putorius furo) were divided randomly into two groups: whole body cigarette smoke exposure and air controls. Ferrets were exposed to smoke from 1R6F research cigarettes, twice daily for six months. RNA-sequencing was performed on RNA isolated from lung tissue. Comparative transcriptomics analyses of COPD in ferrets, mice, and humans were done to find the uniquely expressed genes. Further, Real-time PCR was performed to confirmed RNA-Seq data on multiple selected genes. RESULTS: RNA-sequence analysis identified 420 differentially expressed genes (DEGs) that were associated with the development of COPD in ferrets. By comparative analysis, we identified 25 DEGs that are uniquely expressed in ferrets and humans, but not mice. Among DEGs, a number were related to mucociliary clearance (NEK-6, HAS1, and KL), while others have been correlated with abnormal lung function (IL-18), inflammation (TREM1, CTSB), or oxidative stress (SRX1, AHRR). Multiple cellular pathways were aberrantly altered in the COPD ferret model, including pathways associated with COPD pathogenesis in humans. Validation of these selected unique DEGs using real-time PCR demonstrated > absolute 2-fold changes in mRNA versus air controls, consistent with RNA-seq analysis. CONCLUSION: Cigarette smoke-induced COPD in ferrets modulates gene expression consistent with human COPD and suggests that the ferret model may be uniquely well suited for the study of aspects of the disease.

Recommendations on the use and reporting of race, ethnicity, and ancestry in genetic research: Experiences from the NHLBI TOPMed program.

How race, ethnicity, and ancestry are used in genomic research has wide-ranging implications for how research is translated into clinical care and incorporated into public understanding. Correlation between race and genetic ancestry contributes to unresolved complexity for the scientific community, as illustrated by heterogeneous definitions and applications of these variables. Here, we offer commentary and recommendations on the use of race, ethnicity, and ancestry across the arc of genetic research, including data harmonization, analysis, and reporting. While informed by our experiences as researchers affiliated with the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, these recommendations are applicable to basic and translational genomic research in diverse populations with genome-wide data. Moving forward, considerable collaborative effort will be required to ensure that race, ethnicity, and ancestry are described and used appropriately to generate scientific knowledge that yields broad and equitable benefit.

The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations.

Polygenic risk scores (PRSs) aggregate the effects of genetic variants across the genome and are used to predict risk of complex diseases, such as obesity. Current PRSs only include common variants (minor allele frequency (MAF) ≥1%), whereas the contribution of rare variants in PRSs to predict disease remains unknown. Here, we examine whether augmenting the standard common variant PRS (PRScommon) with a rare variant PRS (PRSrare) improves prediction of obesity. We used genome-wide genotyped and imputed data on 451,145 European-ancestry participants of the UK Biobank, as well as whole exome sequencing (WES) data on 184,385 participants. We performed single variant analyses (for both common and rare variants) and gene-based analyses (for rare variants) for association with BMI (kg/m2), obesity (BMI ≥ 30 kg/m2), and extreme obesity (BMI ≥ 40 kg/m2). We built PRSscommon and PRSsrare using a range of methods (Clumping+Thresholding [C+T], PRS-CS, lassosum, gene-burden test). We selected the best-performing PRSs and assessed their performance in 36,757 European-ancestry unrelated participants with whole genome sequencing (WGS) data from the Trans-Omics for Precision Medicine (TOPMed) program. The best-performing PRScommon explained 10.1% of variation in BMI, and 18.3% and 22.5% of the susceptibility to obesity and extreme obesity, respectively, whereas the best-performing PRSrare explained 1.49%, and 2.97% and 3.68%, respectively. The PRSrare was associated with an increased risk of obesity and extreme obesity (ORobesity = 1.37 per SDPRS, Pobesity = 1.7x10-85; ORextremeobesity = 1.55 per SDPRS, Pextremeobesity = 3.8x10-40), which was attenuated, after adjusting for PRScommon (ORobesity = 1.08 per SDPRS, Pobesity = 9.8x10-6; ORextremeobesity= 1.09 per SDPRS, Pextremeobesity = 0.02). When PRSrare and PRScommon are combined, the increase in explained variance attributed to PRSrare was small (incremental Nagelkerke R2 = 0.24% for obesity and 0.51% for extreme obesity). Consistently, combining PRSrare to PRScommon provided little improvement to the prediction of obesity (PRSrare AUC = 0.591; PRScommon AUC = 0.708; PRScombined AUC = 0.710). In summary, while rare variants show convincing association with BMI, obesity and extreme obesity, the PRSrare provides limited improvement over PRScommon in the prediction of obesity risk, based on these large populations.

Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data.

Analyses of data from genome-wide association studies on unrelated individuals have shown that, for human traits and diseases, approximately one-third to two-thirds of heritability is captured by common SNPs. However, it is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular whether the causal variants are rare, or whether it is overestimated due to bias in inference from pedigree data. Here we estimated heritability for height and body mass index (BMI) from whole-genome sequence data on 25,465 unrelated individuals of European ancestry. The estimated heritability was 0.68 (standard error 0.10) for height and 0.30 (standard error 0.10) for body mass index. Low minor allele frequency variants in low linkage disequilibrium (LD) with neighboring variants were enriched for heritability, to a greater extent for protein-altering variants, consistent with negative selection. Our results imply that rare variants, in particular those in regions of low linkage disequilibrium, are a major source of the still missing heritability of complex traits and disease.

Integrated bioinformatics analysis identifies established and novel TGFß1-regulated genes modulated by anti-fibrotic drugs.

Fibrosis is a leading cause of morbidity and mortality worldwide. Although fibrosis may involve different organ systems, transforming growth factor-ß (TGFß) has been established as a master regulator of fibrosis across organs. Pirfenidone and Nintedanib are the only currently-approved drugs to treat fibrosis, specifically idiopathic pulmonary fibrosis, but their mechanisms of action remain poorly understood. To identify novel drug targets and uncover potential mechanisms by which these drugs attenuate fibrosis, we performed an integrative 'omics analysis of transcriptomic and proteomic responses to TGFß1-stimulated lung fibroblasts. Significant findings were annotated as associated with pirfenidone and nintedanib treatment in silico via Coremine. Integrative 'omics identified a co-expressed transcriptomic and proteomic module significantly correlated with TGFß1 treatment that was enriched (FDR-p = 0.04) with genes associated with pirfenidone and nintedanib treatment. While a subset of genes in this module have been implicated in fibrogenesis, several novel TGFß1 signaling targets were identified. Specifically, four genes (BASP1, HSD17B6, CDH11, and TNS1) have been associated with pirfenidone, while five genes (CLINT1, CADM1, MTDH, SYDE1, and MCTS1) have been associated with nintedanib, and MYDGF has been implicated with treatment using both drugs. Using the Clue Drug Repurposing Hub, succinic acid was highlighted as a metabolite regulated by the protein encoded by HSD17B6. This study provides new insights into the anti-fibrotic actions of pirfenidone and nintedanib and identifies novel targets for future mechanistic studies.

Genetic European Ancestry and Incident Diabetes in Black Individuals: Insights From the SPRINT Trial.

BACKGROUND: Black individuals have high incident diabetes risk, despite having paradoxically lower triglyceride and higher HDL (high-density lipoprotein) cholesterol levels. The basis of this is poorly understood. We evaluated the participants of SPRINT (Systolic Blood Pressure Intervention Trial) to assess the association of estimated European genetic ancestry with the risk of incident diabetes in self-identified Black individuals. METHODS: Self-identified non-Hispanic Black SPRINT participants free of diabetes at baseline were included. Black participants were stratified into tertiles (T1-T3) of European ancestry proportions estimated using 106 biallelic ancestry informative genetic markers. The multivariable-adjusted association of European ancestry proportion with indices of baseline metabolic syndrome (ie, fasting plasma glucose, triglycerides, HDL cholesterol, body mass index, and blood pressure) was assessed. Multivariable-adjusted Cox regression determined the risk of incident diabetes (fasting plasma glucose ≥126 mg/dL or self-reported diabetes treatment) across tertiles of European ancestry proportion. RESULTS: Among 2466 Black SPRINT participants, a higher European ancestry proportion was independently associated with higher baseline triglyceride and lower HDL cholesterol levels (P<0.001 for both). European ancestry proportion was not associated with baseline fasting plasma glucose, body mass index, and blood pressure (P>0.05). Compared with the first tertile, those in the second (hazard ratio, 0.64 [95% CI, 0.45-0.90]) and third tertiles (hazard ratio, 0.61 [95% CI, 0.44-0.89]) of the European ancestry proportion had a lower risk of incident diabetes. A 5% point higher European ancestry was associated with a 29% lower risk of incident diabetes (hazard ratio, 0.71 [95% CI, 0.55-0.93]). There was no evidence of a differential association between the European ancestry proportion tertiles and incident diabetes between those randomized to intensive versus standard blood pressure treatment. CONCLUSIONS: The higher risk of incident diabetes in Black individuals may have genetic determinants in addition to adverse social factors. Further research may help understand the interplay between biological and social determinants of cardiometabolic health in Black individuals. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01206062.

Longitudinal Association Between Muscle Loss and Mortality in Ever Smokers.

BACKGROUND: Body composition measures, specifically low weight or reduced muscle mass, are associated with mortality in COPD, but the effect of longitudinal body composition changes is undefined. RESEARCH QUESTION: Is the longitudinal loss of fat-free mass (FFM) associated with increased mortality, including in those with initially normal or elevated body composition metrics? STUDY DESIGN AND METHODS: Participants with complete data for at least one visit in the COPDGene study (n = 9,268) and the ECLIPSE study (n = 1,760) were included and monitored for 12 and 8 years, respectively. Pectoralis muscle area (PMA) was derived from thoracic CT scans and used as a proxy for FFM. A longitudinal mixed submodel for PMA and a Cox proportional hazards submodel for survival were fitted on a joint distribution, using a shared random intercept parameter and Markov chain Monte Carlo parameter estimation. RESULTS: Both cohorts demonstrated a left-shifted distribution of baseline FFM, not reflected in BMI, and an increase in all-cause mortality risk associated with longitudinal loss of PMA. For each 1-cm2 PMA loss, mortality increased 3.1% (95% CI, 2.4%-3.7%; P < .001) in COPDGene, and 2.4% (95% CI, 0.9%-4.0%; P < .001) in ECLIPSE. Increased mortality risk was independent of enrollment values for BMI and disease severity [BODE (body mass, airflow obstruction, dyspnea, and exercise capacity) index quartiles] and was significant even in participants with initially greater than average PMA. INTERPRETATION: Longitudinal loss of PMA is associated with increased all-cause mortality, regardless of BMI or initial muscle mass. Consideration of novel screening tests and further research into mechanisms contributing to muscle decline may improve risk stratification and identify novel therapeutic targets in ever smokers.