Metabolomic pattern associated with physical sequelae in patients presenting with respiratory symptoms validates the aestivation concept in dehydrated patients.

Hypertonic dehydration is associated with muscle wasting and synthesis of organic osmolytes. We recently showed a metabolic shift to amino acid production and urea cycle activation in coronavirus-2019 (COVID-19), consistent with the aestivation response. The aim of the present investigation was to validate the metabolic shift and development of long-term physical outcomes in the non-COVID cohort of the Biobanque Québécoise de la COVID-19 (BQC19). We included 824 patients from BQC19, where 571 patients had data of dehydration in the form of estimated osmolality (eOSM = 2Na + 2K + glucose + urea), and 284 patients had metabolome data and long-term follow-up. We correlated the degree of dehydration to mortality, invasive mechanical ventilation, acute kidney injury, and long-term symptoms. As found in the COVID cohort, higher eOSM correlated with a higher proportion of urea and glucose of total eOSM, and an enrichment of amino acids compared with other metabolites. Sex-stratified analysis indicated that women may show a weaker aestivation response. More severe dehydration was associated with mortality, invasive mechanical ventilation, and acute kidney injury during the acute illness. Importantly, more severe dehydration was associated with physical long-term symptoms but not mental long-term symptoms after adjustment for age, sex, and disease severity. Patients with water deficit in the form of increased eOSM tend to have more severe disease and experience more physical symptoms after an acute episode of care. This is associated with amino acid and urea production, indicating dehydration-induced muscle wasting.NEW & NOTEWORTHY We have previously shown that humans exhibit an aestivation-like response where dehydration leads to a metabolic shift to urea synthesis, which is associated with long-term weakness indicating muscle wasting. In the present study, we validate this response in a new cohort and present a deeper metabolomic analysis and pathway analysis. Finally, we present a sex-stratified analysis suggesting weaker aestivation in women. However, women show less dehydration, so the association warrants further study.

Predicting ExWAS findings from GWAS data: a shorter path to causal genes.

GWAS has identified thousands of loci associated with disease, yet the causal genes within these loci remain largely unknown. Identifying these causal genes would enable deeper understanding of the disease and assist in genetics-based drug development. Exome-wide association studies (ExWAS) are more expensive but can pinpoint causal genes offering high-yield drug targets, yet suffer from a high false-negative rate. Several algorithms have been developed to prioritize genes at GWAS loci, such as the Effector Index (Ei), Locus-2-Gene (L2G), Polygenic Prioritization score (PoPs), and Activity-by-Contact score (ABC) and it is not known if these algorithms can predict ExWAS findings from GWAS data. However, if this were the case, thousands of associated GWAS loci could potentially be resolved to causal genes. Here, we quantified the performance of these algorithms by evaluating their ability to identify ExWAS significant genes for nine traits. We found that Ei, L2G, and PoPs can identify ExWAS significant genes with high areas under the precision recall curve (Ei: 0.52, L2G: 0.37, PoPs: 0.18, ABC: 0.14). Furthermore, we found that for every unit increase in the normalized scores, there was an associated 1.3-4.6-fold increase in the odds of a gene reaching exome-wide significance (Ei: 4.6, L2G: 2.5, PoPs: 2.1, ABC: 1.3). Overall, we found that Ei, L2G, and PoPs can anticipate ExWAS findings from widely available GWAS results. These techniques are therefore promising when well-powered ExWAS data are not readily available and can be used to anticipate ExWAS findings, allowing for prioritization of genes at GWAS loci.

Genome-wide Association Study for Vitamin D Levels Reveals 69 Independent Loci.

We aimed to increase our understanding of the genetic determinants of vitamin D levels by undertaking a large-scale genome-wide association study (GWAS) of serum 25 hydroxyvitamin D (25OHD). To do so, we used imputed genotypes from 401,460 white British UK Biobank participants with available 25OHD levels, retaining single-nucleotide polymorphisms (SNPs) with minor allele frequency (MAF) > 0.1% and imputation quality score > 0.3. We performed a linear mixed model GWAS on standardized log-transformed 25OHD, adjusting for age, sex, season of measurement, and vitamin D supplementation. These results were combined with those from a previous GWAS including 42,274 Europeans. In silico functional follow-up of the GWAS results was undertaken to identify enrichment in gene sets, pathways, and expression in tissues, and to investigate the partitioned heritability of 25OHD and its shared heritability with other traits. Using this approach, the SNP heritability of 25OHD was estimated to 16.1%. 138 conditionally independent SNPs were detected (p value < 6.6 × 10-9) among which 53 had MAF < 5%. Single variant association signals mapped to 69 distinct loci, among which 63 were previously unreported. We identified enrichment in hepatic and lipid metabolism gene pathways and enriched expression of the 25OHD genes in liver, skin, and gastrointestinal tissues. We observed partially shared heritability between 25OHD and socio-economic traits, a feature which may be mediated through time spent outdoors. Therefore, through a large 25OHD GWAS, we identified 63 loci that underline the contribution of genes outside the vitamin D canonical metabolic pathway to the genetic architecture of 25OHD.

Block coordinate descent algorithm improves variable selection and estimation in error-in-variables regression.

Medical research increasingly includes high-dimensional regression modeling with a need for error-in-variables methods. The Convex Conditioned Lasso (CoCoLasso) utilizes a reformulated Lasso objective function and an error-corrected cross-validation to enable error-in-variables regression, but requires heavy computations. Here, we develop a Block coordinate Descent Convex Conditioned Lasso (BDCoCoLasso) algorithm for modeling high-dimensional data that are only partially corrupted by measurement error. This algorithm separately optimizes the estimation of the uncorrupted and corrupted features in an iterative manner to reduce computational cost, with a specially calibrated formulation of cross-validation error. Through simulations, we show that the BDCoCoLasso algorithm successfully copes with much larger feature sets than CoCoLasso, and as expected, outperforms the naïve Lasso with enhanced estimation accuracy and consistency, as the intensity and complexity of measurement errors increase. Also, a new smoothly clipped absolute deviation penalization option is added that may be appropriate for some data sets. We apply the BDCoCoLasso algorithm to data selected from the UK Biobank. We develop and showcase the utility of covariate-adjusted genetic risk scores for body mass index, bone mineral density, and lifespan. We demonstrate that by leveraging more information than the naïve Lasso in partially corrupted data, the BDCoCoLasso may achieve higher prediction accuracy. These innovations, together with an R package, BDCoCoLasso, make error-in-variables adjustments more accessible for high-dimensional data sets. We posit the BDCoCoLasso algorithm has the potential to be widely applied in various fields, including genomics-facilitated personalized medicine research.

An effector index to predict target genes at GWAS loci.

Drug development and biological discovery require effective strategies to map existing genetic associations to causal genes. To approach this problem, we selected 12 common diseases and quantitative traits for which highly powered genome-wide association studies (GWAS) were available. For each disease or trait, we systematically curated positive control gene sets from Mendelian forms of the disease and from targets of medicines used for disease treatment. We found that these positive control genes were highly enriched in proximity of GWAS-associated single-nucleotide variants (SNVs). We then performed quantitative assessment of the contribution of commonly used genomic features, including open chromatin maps, expression quantitative trait loci (eQTL), and chromatin conformation data. Using these features, we trained and validated an Effector Index (Ei), to map target genes for these 12 common diseases and traits. Ei demonstrated high predictive performance, both with cross-validation on the training set, and an independently derived set for type 2 diabetes. Key predictive features included coding or transcript-altering SNVs, distance to gene, and open chromatin-based metrics. This work outlines a simple, understandable approach to prioritize genes at GWAS loci for functional follow-up and drug development, and provides a systematic strategy for prioritization of GWAS target genes.

Genetically increased circulating FUT3 level leads to reduced risk of idiopathic pulmonary fibrosis: a Mendelian randomisation study.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive, fatal fibrotic interstitial lung disease. Few circulating biomarkers have been identified to have causal effects on IPF. METHODS: To identify candidate IPF-influencing circulating proteins, we undertook an efficient screen of circulating proteins by applying a two-sample Mendelian randomisation (MR) approach with existing publicly available data. For instruments, we used genetic determinants of circulating proteins which reside cis to the encoded gene (cis-single nucleotide polymorphisms (SNPs)), identified by two genome-wide association studies (GWASs) in European individuals (3301 and 3200 subjects). We then applied MR methods to test if the levels of these circulating proteins influenced IPF susceptibility in the largest IPF GWAS (2668 cases and 8591 controls). We validated the MR results using colocalisation analyses to ensure that both the circulating proteins and IPF shared a common genetic signal. RESULTS: MR analyses of 834 proteins found that a 1 sd increase in circulating galactoside 3(4)-l-fucosyltransferase (FUT3) and α-(1,3)-fucosyltransferase 5 (FUT5) was associated with a reduced risk of IPF (OR 0.81, 95% CI 0.74-0.88; p=6.3×10-7 and OR 0.76, 95% CI 0.68-0.86; p=1.1×10-5, respectively). Sensitivity analyses including multiple cis-SNPs provided similar estimates both for FUT3 (inverse variance weighted (IVW) OR 0.84, 95% CI 0.78-0.91; p=9.8×10-6 and MR-Egger OR 0.69, 95% CI 0.50-0.97; p=0.03) and FUT5 (IVW OR 0.84, 95% CI 0.77-0.92; p=1.4×10-4 and MR-Egger OR 0.59, 95% CI 0.38-0.90; p=0.01). FUT3 and FUT5 signals colocalised with IPF signals, with posterior probabilities of a shared genetic signal of 99.9% and 97.7%, respectively. Further transcriptomic investigations supported the protective effects of FUT3 for IPF. CONCLUSIONS: An efficient MR scan of 834 circulating proteins provided evidence that genetically increased circulating FUT3 level is associated with reduced risk of IPF.

Polygenic risk score as a possible tool for identifying familial monogenic causes of complex diseases.

PURPOSE: The study aimed to evaluate whether polygenic risk scores could be helpful in addition to family history for triaging individuals to undergo deep-depth diagnostic sequencing for identifying monogenic causes of complex diseases. METHODS: Among 44,550 exome-sequenced European ancestry UK Biobank participants, we identified individuals with a clinically reported or computationally predicted monogenic pathogenic variant for breast cancer, bowel cancer, heart disease, diabetes, or Alzheimer disease. We derived polygenic risk scores for these diseases. We tested whether a polygenic risk score could identify rare pathogenic variant heterozygotes among individuals with a parental disease history. RESULTS: Monogenic causes of complex diseases were more prevalent among individuals with a parental disease history than in the rest of the population. Polygenic risk scores showed moderate discriminative power to identify familial monogenic causes. For instance, we showed that prescreening the patients with a polygenic risk score for type 2 diabetes can prioritize individuals to undergo diagnostic sequencing for monogenic diabetes variants and reduce needs for such sequencing by up to 37%. CONCLUSION: Among individuals with a family history of complex diseases, those with a low polygenic risk score are more likely to have monogenic causes of the disease and could be prioritized to undergo genetic testing.

Dehydration is associated with production of organic osmolytes and predicts physical long-term symptoms after COVID-19: a multicenter cohort study.

BACKGROUND: We have previously shown that iatrogenic dehydration is associated with a shift to organic osmolyte production in the general ICU population. The aim of the present investigation was to determine the validity of the physiological response to dehydration known as aestivation and its relevance for long-term disease outcome in COVID-19. METHODS: The study includes 374 COVID-19 patients from the Pronmed cohort admitted to the ICU at Uppsala University Hospital. Dehydration data was available for 165 of these patients and used for the primary analysis. Validation was performed in Biobanque Québécoise de la COVID-19 (BQC19) using 1052 patients with dehydration data. Dehydration was assessed through estimated osmolality (eOSM = 2Na + 2 K + glucose + urea), and correlated to important endpoints including death, invasive mechanical ventilation, acute kidney injury, and long COVID-19 symptom score grouped by physical or mental. RESULTS: Increasing eOSM was correlated with increasing role of organic osmolytes for eOSM, while the proportion of sodium and potassium of eOSM were inversely correlated to eOSM. Acute outcomes were associated with pronounced dehydration, and physical long-COVID was more strongly associated with dehydration than mental long-COVID after adjustment for age, sex, and disease severity. Metabolomic analysis showed enrichment of amino acids among metabolites that showed an aestivating pattern. CONCLUSIONS: Dehydration during acute COVID-19 infection causes an aestivation response that is associated with protein degradation and physical long-COVID. TRIAL REGISTRATION: The study was registered à priori (clinicaltrials.gov: NCT04316884 registered on 2020-03-13 and NCT04474249 registered on 2020-06-29).

Vitamin D and COVID-19 susceptibility and severity in the COVID-19 Host Genetics Initiative: A Mendelian randomization study.

BACKGROUND: Increased vitamin D levels, as reflected by 25-hydroxy vitamin D (25OHD) measurements, have been proposed to protect against COVID-19 based on in vitro, observational, and ecological studies. However, vitamin D levels are associated with many confounding variables, and thus associations described to date may not be causal. Vitamin D Mendelian randomization (MR) studies have provided results that are concordant with large-scale vitamin D randomized trials. Here, we used 2-sample MR to assess evidence supporting a causal effect of circulating 25OHD levels on COVID-19 susceptibility and severity. METHODS AND FINDINGS: Genetic variants strongly associated with 25OHD levels in a genome-wide association study (GWAS) of 443,734 participants of European ancestry (including 401,460 from the UK Biobank) were used as instrumental variables. GWASs of COVID-19 susceptibility, hospitalization, and severe disease from the COVID-19 Host Genetics Initiative were used as outcome GWASs. These included up to 14,134 individuals with COVID-19, and up to 1,284,876 without COVID-19, from up to 11 countries. SARS-CoV-2 positivity was determined by laboratory testing or medical chart review. Population controls without COVID-19 were also included in the control groups for all outcomes, including hospitalization and severe disease. Analyses were restricted to individuals of European descent when possible. Using inverse-weighted MR, genetically increased 25OHD levels by 1 standard deviation on the logarithmic scale had no significant association with COVID-19 susceptibility (odds ratio [OR] = 0.95; 95% CI 0.84, 1.08; p = 0.44), hospitalization (OR = 1.09; 95% CI: 0.89, 1.33; p = 0.41), and severe disease (OR = 0.97; 95% CI: 0.77, 1.22; p = 0.77). We used an additional 6 meta-analytic methods, as well as conducting sensitivity analyses after removal of variants at risk of horizontal pleiotropy, and obtained similar results. These results may be limited by weak instrument bias in some analyses. Further, our results do not apply to individuals with vitamin D deficiency. CONCLUSIONS: In this 2-sample MR study, we did not observe evidence to support an association between 25OHD levels and COVID-19 susceptibility, severity, or hospitalization. Hence, vitamin D supplementation as a means of protecting against worsened COVID-19 outcomes is not supported by genetic evidence. Other therapeutic or preventative avenues should be given higher priority for COVID-19 randomized controlled trials.

Individuals with common diseases but with a low polygenic risk score could be prioritized for rare variant screening.

PURPOSE: Identifying rare genetic causes of common diseases can improve diagnostic and treatment strategies, but incurs high costs. We tested whether individuals with common disease and low polygenic risk score (PRS) for that disease generated from less expensive genome-wide genotyping data are more likely to carry rare pathogenic variants. METHODS: We identified patients with one of five common complex diseases among 44,550 individuals who underwent exome sequencing in the UK Biobank. We derived PRS for these five diseases, and identified pathogenic rare variant heterozygotes. We tested whether individuals with disease and low PRS were more likely to carry rare pathogenic variants. RESULTS: While rare pathogenic variants conferred, at most, 5.18-fold (95% confidence interval [CI]: 2.32-10.13) increased odds of disease, a standard deviation increase in PRS, at most, increased the odds of disease by 5.25-fold (95% CI: 5.06-5.45). Among diseased patients, a standard deviation decrease in the PRS was associated with, at most, 2.82-fold (95% CI: 1.14-7.46) increased odds of identifying rare variant heterozygotes. CONCLUSION: Rare pathogenic variants were more prevalent among affected patients with a low PRS. Therefore, prioritizing individuals for sequencing who have disease but low PRS may increase the yield of sequencing studies to identify rare variant heterozygotes.

Childhood obesity and multiple sclerosis: A Mendelian randomization study.

BACKGROUND: Higher childhood body mass index (BMI) has been associated with an increased risk of multiple sclerosis (MS). OBJECTIVE: To evaluate whether childhood BMI has a causal influence on MS, and whether this putative effect is independent from early adult obesity and pubertal timing. METHODS: We performed Mendelian randomization (MR) using summary genetic data on 14,802 MS cases and 26,703 controls. Large-scale genome-wide association studies provided estimates for BMI in childhood (n = 47,541) and adulthood (n = 322,154). In multivariable MR, we examined the direct effects of each timepoint and further adjusted for age at puberty. Findings were replicated using the UK Biobank (n = 453,169). RESULTS: Higher genetically predicted childhood BMI was associated with increased odds of MS (odds ratio (OR) = 1.26/SD BMI increase, 95% confidence interval (CI): 1.07-1.50). However, there was little evidence of a direct effect after adjusting for adult BMI (OR = 1.03, 95% CI: 0.70-1.53). Conversely, the effect of adult BMI persisted independent of childhood BMI (OR = 1.43; 95% CI: 1.01-2.03). The addition of age at puberty did not alter the findings. UK Biobank analyses showed consistent results. Sensitivity analyses provided no evidence of pleiotropy. CONCLUSION: Genetic evidence supports an association between childhood obesity and MS susceptibility, mediated by persistence of obesity into early adulthood but independent of pubertal timing.

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.

Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study.

BACKGROUND: Since screening programs identify only a small proportion of the population as eligible for an intervention, genomic prediction of heritable risk factors could decrease the number needing to be screened by removing individuals at low genetic risk. We therefore tested whether a polygenic risk score for heel quantitative ultrasound speed of sound (SOS)-a heritable risk factor for osteoporotic fracture-can identify low-risk individuals who can safely be excluded from a fracture risk screening program. METHODS AND FINDINGS: A polygenic risk score for SOS was trained and selected in 2 separate subsets of UK Biobank (comprising 341,449 and 5,335 individuals). The top-performing prediction model was termed "gSOS", and its utility in fracture risk screening was tested in 5 validation cohorts using the National Osteoporosis Guideline Group clinical guidelines (N = 10,522 eligible participants). All individuals were genome-wide genotyped and had measured fracture risk factors. Across the 5 cohorts, the average age ranged from 57 to 75 years, and 54% of studied individuals were women. The main outcomes were the sensitivity and specificity to correctly identify individuals requiring treatment with and without genetic prescreening. The reference standard was a bone mineral density (BMD)-based Fracture Risk Assessment Tool (FRAX) score. The secondary outcomes were the proportions of the screened population requiring clinical-risk-factor-based FRAX (CRF-FRAX) screening and BMD-based FRAX (BMD-FRAX) screening. gSOS was strongly correlated with measured SOS (r2 = 23.2%, 95% CI 22.7% to 23.7%). Without genetic prescreening, guideline recommendations achieved a sensitivity and specificity for correct treatment assignment of 99.6% and 97.1%, respectively, in the validation cohorts. However, 81% of the population required CRF-FRAX tests, and 37% required BMD-FRAX tests to achieve this accuracy. Using gSOS in prescreening and limiting further assessment to those with a low gSOS resulted in small changes to the sensitivity and specificity (93.4% and 98.5%, respectively), but the proportions of individuals requiring CRF-FRAX tests and BMD-FRAX tests were reduced by 37% and 41%, respectively. Study limitations include a reliance on cohorts of predominantly European ethnicity and use of a proxy of fracture risk. CONCLUSIONS: Our results suggest that the use of a polygenic risk score in fracture risk screening could decrease the number of individuals requiring screening tests, including BMD measurement, while maintaining a high sensitivity and specificity to identify individuals who should be recommended an intervention.

Low-Frequency Synonymous Coding Variation in CYP2R1 Has Large Effects on Vitamin D Levels and Risk of Multiple Sclerosis.

Vitamin D insufficiency is common, correctable, and influenced by genetic factors, and it has been associated with risk of several diseases. We sought to identify low-frequency genetic variants that strongly increase the risk of vitamin D insufficiency and tested their effect on risk of multiple sclerosis, a disease influenced by low vitamin D concentrations. We used whole-genome sequencing data from 2,619 individuals through the UK10K program and deep-imputation data from 39,655 individuals genotyped genome-wide. Meta-analysis of the summary statistics from 19 cohorts identified in CYP2R1 the low-frequency (minor allele frequency = 2.5%) synonymous coding variant g.14900931G>A (p.Asp120Asp) (rs117913124[A]), which conferred a large effect on 25-hydroxyvitamin D (25OHD) levels (-0.43 SD of standardized natural log-transformed 25OHD per A allele; p value = 1.5 × 10-88). The effect on 25OHD was four times larger and independent of the effect of a previously described common variant near CYP2R1. By analyzing 8,711 individuals, we showed that heterozygote carriers of this low-frequency variant have an increased risk of vitamin D insufficiency (odds ratio [OR] = 2.2, 95% confidence interval [CI] = 1.78-2.78, p = 1.26 × 10-12). Individuals carrying one copy of this variant also had increased odds of multiple sclerosis (OR = 1.4, 95% CI = 1.19-1.64, p = 2.63 × 10-5) in a sample of 5,927 case and 5,599 control subjects. In conclusion, we describe a low-frequency CYP2R1 coding variant that exerts the largest effect upon 25OHD levels identified to date in the general European population and implicates vitamin D in the etiology of multiple sclerosis.

The undiagnosed disease burden associated with alpha-1 antitrypsin deficiency genotypes.

Alpha-1 antitrypsin deficiency (AATD), mainly due to the PI*ZZ genotype in SERPINA1, is one of the most common inherited diseases. Since it is associated with a high disease burden and partially prevented by smoking cessation, identification of PI*ZZ individuals through genotyping could improve health outcomes.We examined the frequency of the PI*ZZ genotype in individuals with and without diagnosed AATD from UK Biobank, and assessed the associations of the genotypes with clinical outcomes and mortality. A phenome-wide association study (PheWAS) was conducted to reveal disease associations with genotypes. A polygenic risk score (PRS) for forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) ratio was used to evaluate variable penetrance of PI*ZZ.Among 458 164 European-ancestry participants in UK Biobank, 140 had the PI*ZZ genotype and only nine (6.4%, 95% CI 3.4-11.7%) of them were diagnosed with AATD. Those with PI*ZZ had a substantially higher odds of COPD (OR 8.8, 95% CI 5.8-13.3), asthma (OR 2.0, 95% CI 1.4-3.0), bronchiectasis (OR 7.3, 95%CI 3.2-16.8), pneumonia (OR 2.7, 95% CI 1.5-4.9) and cirrhosis (OR 7.8, 95% CI 2.5-24.6) diagnoses and a higher hazard of mortality (2.4, 95% CI 1.2-4.6), compared to PI*MM (wildtype) (n=398 424). These associations were stronger among smokers. PheWAS demonstrated associations with increased odds of empyema, pneumothorax, cachexia, polycythaemia, aneurysm and pancreatitis. Polygenic risk score and PI*ZZ were independently associated with FEV1/FVC <0.7 (OR 1.4 per 1-sd change, 95% CI 1.4-1.5 and OR 4.5, 95% CI 3.0-6.9, respectively).The important underdiagnosis of AATD, whose outcomes are partially preventable through smoking cession, could be improved through genotype-guided diagnosis.

Polygenic risk for coronary heart disease acts through atherosclerosis in type 2 diabetes.

BACKGROUND: Type 2 diabetes increases the risk of coronary heart disease (CHD), yet the mechanisms involved remain poorly described. Polygenic risk scores (PRS) provide an opportunity to understand risk factors since they reflect etiologic pathways from the entire genome. We therefore tested whether a PRS for CHD influenced risk of CHD in individuals with type 2 diabetes and which risk factors were associated with this PRS. METHODS: We tested the association of a CHD PRS with CHD and its traditional clinical risk factors amongst individuals with type 2 diabetes in UK Biobank (N = 21,102). We next tested the association of the CHD PRS with atherosclerotic burden in a cohort of 352 genome-wide genotyped participants with type 2 diabetes who had undergone coronary angiograms. RESULTS: In the UK Biobank we found that the CHD PRS was strongly associated with CHD amongst individuals with type 2 diabetes (OR per standard deviation increase = 1.50; p = 1.5 × 10- 59). But this CHD PRS was, at best, only weakly associated with traditional clinical risk factors, such as hypertension, hyperlipidemia, glycemic control, obesity and smoking. Conversely, in the angiographic cohort, the CHD PRS was strongly associated with multivessel stenosis (OR = 1.65; p = 4.9 × 10- 4) and increased number of major stenotic lesions (OR = 1.35; p = 9.4 × 10- 3). CONCLUSIONS: Polygenic predisposition to CHD is strongly associated with atherosclerotic burden in individuals with type 2 diabetes and this effect is largely independent of traditional clinical risk factors. This suggests that genetic risk for CHD acts through atherosclerosis with little effect on most traditional risk factors, providing the opportunity to explore new biological pathways.

Large differences in adiponectin levels have no clear effect on multiple sclerosis risk: A Mendelian randomization study.

BACKGROUND: Mendelian randomization (MR) studies have demonstrated strong support for an association between genetically increased body mass index and risk of multiple sclerosis (MS). The adipokine adiponectin may be a potential mechanism linking body mass to risk of MS. OBJECTIVE: To evaluate whether genetically increased adiponectin levels influence risk of MS. METHODS: Using genome-wide significant single nucleotide polymorphisms (SNPs) for adiponectin, we undertook an MR study to estimate the effect of adiponectin on MS. This method prevents bias due to reverse causation and minimizes bias due to confounding. Sensitivity analyses were performed to evaluate the assumptions of MR. RESULTS: MR analyses did not support a role for genetically elevated adiponectin in risk of MS (odds ratio (OR) = 0.93 per unit increase in natural-log-transformed adiponectin, equivalent to a two-standard deviation increase in adiponectin on the absolute scale; 95% confidence interval (CI) = 0.66-1.33; p = 0.61). Further MR analysis suggested that genetic variation at the adiponectin gene, which influences adiponectin level, does not impact MS risk. Sensitivity analyses, including MR-Egger regression, suggested no bias due to pleiotropy. CONCLUSION: Lifelong genetically increased adiponectin levels in humans have no clear effect on risk of MS. Other biological factors driving the association between body mass and MS should be investigated.

Mendelian randomisation applied to drug development in cardiovascular disease: a review.

Despite increased expenditure, productivity of the pharmaceutical industry has decreased and currently 90% of developed molecules entering phase II and phase III clinical trials fail to gain regulatory approval. Most of these failures are due to lack of therapeutic efficacy rather than lack of safety, suggesting that drug development failures may often be due to poor drug target validation. Currently, drug targets are largely validated using in vitro assays and animal models which may not translate well to human disease. Emerging methods from human genetics, such as Mendelian randomisation (MR), can enable the validation of putative biomarker drug targets in humans prior to the initiation of clinical trials. MR studies can provide evidence as to whether genetically determined levels of a biomarker influence disease aetiology, enabling investigators to infer whether the biomarker is causal. We review the extent to which MR techniques may be helpful in biomarker validation by assessing the concordance between the results from MR studies and phase III clinical trials for lipid therapy in cardiovascular disease. Our findings show that concordance is highest when MR provides evidence suggesting that a biomarker is not causal. In contrast, there are many examples of clinical trials that still failed despite targeting confirmed causal biomarkers. We discuss why such trials may not succeed, despite evidence for causality in MR studies, and outline important limitations when using MR for biomarker validation in drug development. Nonetheless, given the current inefficiencies in drug development, MR methods have potential to improve the success rate of drug development and ultimately the delivery of new molecules to clinical care.

Vitamin D and Risk of Multiple Sclerosis: A Mendelian Randomization Study.

BACKGROUND: Observational studies have demonstrated an association between decreased vitamin D level and risk of multiple sclerosis (MS); however, it remains unclear whether this relationship is causal. We undertook a Mendelian randomization (MR) study to evaluate whether genetically lowered vitamin D level influences the risk of MS. METHODS AND FINDINGS: We identified single nucleotide polymorphisms (SNPs) associated with 25-hydroxyvitamin D (25OHD) level from SUNLIGHT, the largest (n = 33,996) genome-wide association study to date for vitamin D. Four SNPs were genome-wide significant for 25OHD level (p-values ranging from 6 × 10-10 to 2 × 10-109), and all four SNPs lay in, or near, genes strongly implicated in separate mechanisms influencing 25OHD. We then ascertained their effect on 25OHD level in 2,347 participants from a population-based cohort, the Canadian Multicentre Osteoporosis Study, and tested the extent to which the 25OHD-decreasing alleles explained variation in 25OHD level. We found that the count of 25OHD-decreasing alleles across these four SNPs was strongly associated with lower 25OHD level (n = 2,347, F-test statistic = 49.7, p = 2.4 × 10-12). Next, we conducted an MR study to describe the effect of genetically lowered 25OHD on the odds of MS in the International Multiple Sclerosis Genetics Consortium study, the largest genetic association study to date for MS (including up to 14,498 cases and 24,091 healthy controls). Alleles were weighted by their relative effect on 25OHD level, and sensitivity analyses were performed to test MR assumptions. MR analyses found that each genetically determined one-standard-deviation decrease in log-transformed 25OHD level conferred a 2.0-fold increase in the odds of MS (95% CI: 1.7-2.5; p = 7.7 × 10-12; I2 = 63%, 95% CI: 0%-88%). This result persisted in sensitivity analyses excluding SNPs possibly influenced by population stratification or pleiotropy (odds ratio [OR] = 1.7, 95% CI: 1.3-2.2; p = 2.3 × 10-5; I2 = 47%, 95% CI: 0%-85%) and including only SNPs involved in 25OHD synthesis or metabolism (ORsynthesis = 2.1, 95% CI: 1.6-2.6, p = 1 × 10-9; ORmetabolism = 1.9, 95% CI: 1.3-2.7, p = 0.002). While these sensitivity analyses decreased the possibility that pleiotropy may have biased the results, residual pleiotropy is difficult to exclude entirely. CONCLUSIONS: A genetically lowered 25OHD level is strongly associated with increased susceptibility to MS. Whether vitamin D sufficiency can delay, or prevent, MS onset merits further investigation in long-term randomized controlled trials.