Advancing drug development for atrial fibrillation by prioritising findings from human genetic association studies.

BACKGROUND: Drug development for atrial fibrillation (AF) has failed to yield new approved compounds. We sought to identify and prioritise potential druggable targets with support from human genetics, by integrating the available evidence with bioinformatics sources relevant for AF drug development. METHODS: Genetic hits for AF and related traits were identified through structured search of MEDLINE. Genes derived from each paper were cross-referenced with the OpenTargets platform for drug interactions. Confirmation/validation was demonstrated through structured searches and review of evidence on MEDLINE and ClinialTrials.gov for each drug and its association with AF. FINDINGS: 613 unique drugs were identified, with 21 already included in AF Guidelines. Cardiovascular drugs from classes not currently used for AF (e.g. ranolazine and carperitide) and anti-inflammatory drugs (e.g. dexamethasone and mehylprednisolone) had evidence of potential benefit. Further targets were considered druggable but remain open for drug development. INTERPRETATION: Our systematic approach, combining evidence from different bioinformatics platforms, identified drug repurposing opportunities and druggable targets for AF. FUNDING: KK is supported by Barts Charity grant G-002089 and is mentored on the AFGen 2023-24 Fellowship funded by the AFGen NIH/NHLBI grant R01HL092577. RP is supported by the UCL BHF Research Accelerator AA/18/6/34223 and NIHR grant NIHR129463. AFS is supported by the BHF grants PG/18/5033837, PG/22/10989 and UCL BHF Accelerator AA/18/6/34223 as well as the UK Research and Innovation (UKRI) under the UK government's Horizon Europe funding guarantee EP/Z000211/1 and by the UKRI-NIHR grant MR/V033867/1 for the Multimorbidity Mechanism and Therapeutics Research Collaboration. AF is supported by UCL BHF Accelerator AA/18/6/34223. CF is supported by UCL BHF Accelerator AA/18/6/34223.

Adiposity and grip strength: a Mendelian randomisation study in UK Biobank.

BACKGROUND: Muscle weakness, which increases in prevalence with age, is a major public health concern. Grip strength is commonly used to identify weakness and an improved understanding of its determinants is required. We aimed to investigate if total and central adiposity are causally associated with grip strength. METHODS: Up to 470,786 UK Biobank participants, aged 38-73 years, with baseline data on four adiposity indicators (body mass index (BMI), body fat percentage (BF%), waist circumference (WC) and waist-hip-ratio (WHR)) and maximum grip strength were included. We examined sex-specific associations between each adiposity indicator and grip strength. We explored whether associations varied by age, by examining age-stratified associations (< 50 years, 50-59 years, 60-64 years,65 years +). Using Mendelian randomisation (MR), we estimated the strength of the adiposity-grip strength associations using genetic instruments for each adiposity trait as our exposure. RESULTS: In males, observed and MR associations were generally consistent: higher BMI and WC were associated with stronger grip; higher BF% and WHR were associated with weaker grip: 1-SD higher BMI was associated with 0.49 kg (95% CI: 0.45 kg, 0.53 kg) stronger grip; 1-SD higher WHR was associated with 0.45 kg (95% CI:0.41 kg, 0.48 kg) weaker grip (covariate adjusted observational analyses). Associations of BMI and WC with grip strength were weaker at older ages: in males aged < 50 years and 65 years + , 1-SD higher BMI was associated with 0.93 kg (95% CI: 0.84 kg, 1.01 kg) and 0.13 kg (95% CI: 0.05 kg, 0.21 kg) stronger grip, respectively. In females, higher BF% was associated with weaker grip and higher WC was associated with stronger grip; other associations were inconsistent. CONCLUSIONS: Using different methods to triangulate evidence, our findings suggest causal links between adiposity and grip strength. Specifically, higher BF% (in both sexes) and WHR (males only) were associated with weaker grip strength.

Insights into the genetic architecture of haematological traits from deep phenotyping and whole-genome sequencing for two Mediterranean isolated populations.

Haematological traits are linked to cardiovascular, metabolic, infectious and immune disorders, as well as cancer. Here, we examine the role of genetic variation in shaping haematological traits in two isolated Mediterranean populations. Using whole-genome sequencing data at 22× depth for 1457 individuals from Crete (MANOLIS) and 1617 from the Pomak villages in Greece, we carry out a genome-wide association scan for haematological traits using linear mixed models. We discover novel associations (p < 5 × 10-9) of five rare non-coding variants with alleles conferring effects of 1.44-2.63 units of standard deviation on red and white blood cell count, platelet and red cell distribution width. Moreover, 10.0% of individuals in the Pomak population and 6.8% in MANOLIS carry a pathogenic mutation in the Haemoglobin Subunit Beta (HBB) gene. The mutational spectrum is highly diverse (10 different mutations). The most frequent mutation in MANOLIS is the common Mediterranean variant IVS-I-110 (G>A) (rs35004220). In the Pomak population, c.364C>A ("HbO-Arab", rs33946267) is most frequent (4.4% allele frequency). We demonstrate effects on haematological and other traits, including bilirubin, cholesterol, and, in MANOLIS, height and gestation age. We find less severe effects on red blood cell traits for HbS, HbO, and IVS-I-6 (T>C) compared to other b+ mutations. Overall, we uncover allelic diversity of HBB in Greek isolated populations and find an important role for additional rare variants outside of HBB.

Type 2 diabetes risks and determinants in second-generation migrants and mixed ethnicity people of South Asian and African Caribbean descent in the UK.

AIMS/HYPOTHESIS: Excess risks of type 2 diabetes in UK South Asians (SA) and African Caribbeans (AC) compared with Europeans remain unexplained. We studied risks and determinants of type 2 diabetes in first- and second-generation (born in the UK) migrants, and in those of mixed ethnicity. METHODS: Data from the UK Biobank, a population-based cohort of ~500,000 participants aged 40-69 at recruitment, were used. Type 2 diabetes was assigned using self-report and HbA1c. Ethnicity was both self-reported and genetically assigned using admixture level scores. European, mixed European/South Asian (MixESA), mixed European/African Caribbean (MixEAC), SA and AC groups were analysed, matched for age and sex to enable comparison. In the frames of this cross-sectional study, we compared type 2 diabetes in second- vs first-generation migrants, and mixed ethnicity vs non-mixed groups. Risks and explanations were analysed using logistic regression and mediation analysis, respectively. RESULTS: Type 2 diabetes prevalence was markedly elevated in SA (599/3317 = 18%) and AC (534/4180 = 13%) compared with Europeans (140/3324 = 4%). Prevalence was lower in second- vs first-generation SA (124/1115 = 11% vs 155/1115 = 14%) and AC (163/2200 = 7% vs 227/2200 = 10%). Favourable adiposity (i.e. lower waist/hip ratio or BMI) contributed to lower risk in second-generation migrants. Type 2 diabetes in mixed populations (MixESA: 52/831 = 6%, MixEAC: 70/1045 = 7%) was lower than in comparator ethnic groups (SA: 18%, AC: 13%) and higher than in Europeans (4%). Greater socioeconomic deprivation accounted for 17% and 42% of the excess type 2 diabetes risk in MixESA and MixEAC compared with Europeans, respectively. Replacing self-reported with genetically assigned ethnicity corroborated the mixed ethnicity analysis. CONCLUSIONS/INTERPRETATION: Type 2 diabetes risks in second-generation SA and AC migrants are a fifth lower than in first-generation migrants. Mixed ethnicity risks were markedly lower than SA and AC groups, though remaining higher than in Europeans. Distribution of environmental risk factors, largely obesity and socioeconomic status, appears to play a key role in accounting for ethnic differences in type 2 diabetes risk.

Pleiotropic associations of heterozygosity for the SERPINA1 Z allele in the UK Biobank.

Homozygosity for the SERPINA1 Z allele causes α1-antitrypsin deficiency, a rare condition that can cause lung and liver disease. However, the effects of Z allele heterozygosity on nonrespiratory phenotypes, and on lung function in the general population, remain unclear. We conducted a large, population-based study to determine Z allele effects on >2400 phenotypes in the UK Biobank (N=303 353). Z allele heterozygosity was strongly associated with increased height (ß=1.02 cm, p=3.91×10-68), and with other nonrespiratory phenotypes including increased risk of gall bladder disease, reduced risk of heart disease and lower blood pressure, reduced risk of osteoarthritis and reduced bone mineral density, increased risk of headache and enlarged prostate, as well as with blood biomarkers of liver function. Heterozygosity was associated with higher height-adjusted forced expiratory volume in 1 s (FEV1) (ß=19.36 mL, p=9.21×10-4) and FEV1/forced vital capacity (ß=0.0031, p=1.22×10-5) in nonsmokers, whereas in smokers, this protective effect was abolished. Furthermore, we show for the first time that sex modifies the association of the Z allele on lung function. We conclude that Z allele heterozygosity and homozygosity exhibit opposing effects on lung function in the UK population, and that these associations are modified by smoking and sex. In exploratory analyses, heterozygosity for the Z allele also showed pleiotropic associations with nonrespiratory health-related traits and disease risk.

Relationship Between Glycemia and Cognitive Function, Structural Brain Outcomes, and Dementia: A Mendelian Randomization Study in the UK Biobank.

We investigated the relationship between glycemia and cognitive function, brain structure and incident dementia using bidirectional Mendelian randomization (MR). Data were from the UK Biobank (n = ∼500,000). Our exposures were genetic instruments for type 2 diabetes (157 variants) and HbA1c (51 variants) and our outcomes were reaction time (RT), visual memory, hippocampal volume (HV), white matter hyperintensity volume (WMHV), and Alzheimer dementia (AD). We also investigated associations between genetic variants for RT (43 variants) and diabetes and HbA1c We used conventional inverse-variance-weighted (IVW) MR alongside MR sensitivity analyses. Using IVW, genetic liability to type 2 diabetes was not associated with RT (exponentiated ß [expß] = 1.00 [95% CI 1.00; 1.00]), visual memory (expß = 1.00 [95% CI 0.99; 1.00]), WMHV (expß = 0.99 [95% CI 0.97; 1.01]), HV (ß-coefficient mm3 = -2.30 [95% CI -12.39; 7.78]) or AD (odds ratio [OR] 1.15 [95% CI 0.87; 1.52]). HbA1c was not associated with RT (expß = 1.00 [95% CI 0.99; 1.02]), visual memory (expß = 0.99 [95% CI 0.96; 1.02]), WMHV (expß = 1.03 [95% CI 0.88; 1.22]), HV (ß = -21.31 [95% CI -82.96; 40.34]), or risk of AD (OR 1.09 [95% CI 0.42; 2.83]). IVW showed that reaction time was not associated with diabetes risk (OR 0.94 [95% CI 0.54; 1.65]), or with HbA1c (ß-coefficient mmol/mol = -0.88 [95% CI = -1.88; 0.13]) after exclusion of a pleiotropic variant. Overall, we observed little evidence of causal association between genetic instruments for type 2 diabetes or peripheral glycemia and some measures of cognition and brain structure in midlife.

HbA1c and brain health across the entire glycaemic spectrum.

AIM: To understand the relationship between HbA1c and brain health across the entire glycaemic spectrum. MATERIALS AND METHODS: We used data from the UK Biobank cohort consisting of 500,000 individuals aged 40-69 years. HbA1c and diabetes diagnosis were used to define baseline glycaemic categories. Our outcomes included incident all-cause dementia, vascular dementia (VD), Alzheimer's dementia (AD), hippocampal volume (HV), white matter hyperintensity (WMH) volume, cognitive function and decline. The reference group was normoglycaemic individuals (HbA1c ≥35 & <42 mmol/mol). Our maximum analytical sample contained 449,973 individuals with complete data. RESULTS: Prediabetes and known diabetes increased incident VD (HR 1.54; 95% CI = 1.04, 2.28 and HR 2.97; 95% CI = 2.26, 3.90, respectively). Known diabetes increased all-cause and AD risk (HR 1.91; 95% CI = 1.66, 2.21 and HR 1.84; 95% CI = 1.44, 2.36, respectively). Prediabetes and known diabetes elevated the risks of cognitive decline (OR 1.42; 1.48, 2.96 and OR 1.39; 1.04, 1.75, respectively). Prediabetes, undiagnosed and known diabetes conferred higher WMH volumes (3%, 22% and 7%, respectively) and lower HV (36, 80 and 82 mm3 , respectively), whereas low-normal HbA1c had 1% lower WMH volume and 12 mm3 greater HV. CONCLUSION: Both prediabetes and known diabetes are harmful in terms of VD, cognitive decline and AD risks, as well as lower HV. Associations appeared to be somewhat driven by antihypertensive medication, which implies that certain cardiovascular drugs may ameliorate some of the excess risk. Low-normal HbA1c levels, however, are associated with more favourable brain health outcomes and warrant more in-depth investigation.

Risk of 16 cancers across the full glycemic spectrum: a population-based cohort study using the UK Biobank.

INTRODUCTION: Diabetes is observed to increase cancer risk, leading to hypothesized direct effects of either hyperglycemia or medication. We investigated associations between glycosylated hemoglobin (HbA1c) across the whole glycemic spectrum and incidence of 16 cancers in a population sample with comprehensive adjustment for risk factors and medication. RESEARCH DESIGN AND METHODS: Linked data from the UK Biobank and UK cancer registry for all individuals with baseline HbA1c and no history of cancer at enrollment were used. Incident cancer was based on International Classification of Diseases - 10th Edition diagnostic codes. Age-standardized incidence rates were estimated by HbA1c category. Associations between HbA1c, modeled as a restricted cubic spline, and cancer risk were estimated using Cox proportional hazards models. RESULTS: Among 378 253 individuals with average follow-up of 7.1 years, 21 172 incident cancers occurred. While incidence for many of the 16 cancers was associated with hyperglycemia in crude analyses, these associations disappeared after multivariable adjustment, except for pancreatic cancer (HR 1.55, 95% CI 1.22 to 1.98 for 55 vs 35 mmol/mol), and a novel finding of an inverse association between HbA1c and premenopausal breast cancer (HR 1.27, 95% CI 1.00 to 1.60 for 25 vs 35 mmol/mol; HR 0.71, 95% CI 0.54 to 0.94 for 45 vs 35 mmol/mol), not observed for postmenopausal breast cancer. Adjustment for diabetes medications had no appreciable impact on HRs for cancer. CONCLUSIONS: Apart from pancreatic cancer, we did not demonstrate any independent positive association between HbA1c and cancer risk. These findings suggest that the potential for a cancer-inducing, direct effect of hyperglycemia may be misplaced.

A Dietary Pattern with High Sugar Content Is Associated with Cardiometabolic Risk Factors in the Pomak Population.

The present study describes the geographically isolated Pomak population and its particular dietary patterns in relationship to cardiovascular risk factors. We collected a population-based cohort in a cross-sectional study, with detailed anthropometric, biochemical, clinical, and lifestyle parameter information. Dietary patterns were derived through principal component analysis based on a validated food-frequency questionnaire, administered to 1702 adult inhabitants of the Pomak villages on the Rhodope mountain range in Greece. A total of 69.9% of the participants were female with a population mean age of 44.9 years; 67% of the population were overweight or obese with a significantly different prevalence for obesity between men and women (17.5% vs. 37.5%, respectively, p < 0.001). Smoking was more prevalent in men (45.8% vs. 2.2%, p < 0.001), as 97.3% of women had never smoked. Four dietary patterns emerged as characteristic of the population, and were termed "high in sugars", "quick choices", "balanced", and "homemade". Higher adherence to the "high in sugars" dietary pattern was associated with increased glucose levels (p < 0.001) and increased risk of hypertension (OR (95% CI) 2.61 (1.55, 4.39), p < 0.001) and nominally associated with high blood glucose levels (OR (95% CI) 1.85 (1.11, 3.08), p = 0.018), compared to lower adherence. Overall, we characterize the dietary patterns of the Pomak population and describe associations with cardiovascular risk factors.

Very low-depth whole-genome sequencing in complex trait association studies.

MOTIVATION: Very low-depth sequencing has been proposed as a cost-effective approach to capture low-frequency and rare variation in complex trait association studies. However, a full characterization of the genotype quality and association power for very low-depth sequencing designs is still lacking. RESULTS: We perform cohort-wide whole-genome sequencing (WGS) at low depth in 1239 individuals (990 at 1× depth and 249 at 4× depth) from an isolated population, and establish a robust pipeline for calling and imputing very low-depth WGS genotypes from standard bioinformatics tools. Using genotyping chip, whole-exome sequencing (75× depth) and high-depth (22×) WGS data in the same samples, we examine in detail the sensitivity of this approach, and show that imputed 1× WGS recapitulates 95.2% of variants found by imputed GWAS with an average minor allele concordance of 97% for common and low-frequency variants. In our study, 1× further allowed the discovery of 140 844 true low-frequency variants with 73% genotype concordance when compared to high-depth WGS data. Finally, using association results for 57 quantitative traits, we show that very low-depth WGS is an efficient alternative to imputed GWAS chip designs, allowing the discovery of up to twice as many true association signals than the classical imputed GWAS design. AVAILABILITY AND IMPLEMENTATION: The HELIC genotype and WGS datasets have been deposited to the European Genome-phenome Archive (https://www.ebi.ac.uk/ega/home): EGAD00010000518; EGAD00010000522; EGAD00010000610; EGAD00001001636, EGAD00001001637. The peakplotter software is available at https://github.com/wtsi-team144/peakplotter, the transformPhenotype app can be downloaded at https://github.com/wtsi-team144/transformPhenotype. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Author Correction: Cohort-wide deep whole genome sequencing and the allelic architecture of complex traits.

The original version of this Article contained an error in Fig. 2. In panel a, the two legend items "rare" and "common" were inadvertently swapped. This has been corrected in both the PDF and HTML versions of the Article.

Cohort-wide deep whole genome sequencing and the allelic architecture of complex traits.

The role of rare variants in complex traits remains uncharted. Here, we conduct deep whole genome sequencing of 1457 individuals from an isolated population, and test for rare variant burdens across six cardiometabolic traits. We identify a role for rare regulatory variation, which has hitherto been missed. We find evidence of rare variant burdens that are independent of established common variant signals (ADIPOQ and adiponectin, P = 4.2 × 10-8; APOC3 and triglyceride levels, P = 1.5 × 10-26), and identify replicating evidence for a burden associated with triglyceride levels in FAM189B (P = 2.2 × 10-8), indicating a role for this gene in lipid metabolism.

Author Correction: Discovery and refinement of genetic loci associated with cardiometabolic risk using dense imputation maps.

In the version of the article published, the surname of author Aaron Isaacs is misspelled as Issacs.

The vitamin D binding protein axis modifies disease severity in lymphangioleiomyomatosis.

Lymphangioleiomyomatosis (LAM) is a rare disease of women. Decline in lung function is variable, making appropriate targeting of therapy difficult. We used unbiased serum proteomics to identify markers associated with outcome in LAM.101 women with LAM and 22 healthy controls were recruited from the National Centre for LAM in the UK. 152 DNA and serum samples with linked lung function and outcome data were obtained from patients in the National Heart, Lung and Blood Institute LAM Registry in the USA. Proteomic analysis was performed on a discovery cohort of 50 LAM and 20 control serum samples using a SCIEX SWATH mass spectrometric workflow. Protein levels were quantitated by ELISA and single nucleotide polymorphisms in GC (group-specific component) encoding vitamin D binding protein (VTDB) were genotyped.Proteomic analysis showed VTDB was 2.6-fold lower in LAM than controls. Serum VTDB was lower in progressive compared with stable LAM (p=0.001) and correlated with diffusing capacity of the lung for carbon monoxide (p=0.01). Median time to death or lung transplant was reduced by 46 months in those with CC genotypes at rs4588 and 38 months in those with non-A-containing haplotypes at rs7041/4588 (p=0.014 and 0.008, respectively).The VTDB axis is associated with disease severity and outcome, and GC genotype could help predict transplant-free survival in LAM.

Exome-wide association study of plasma lipids in >300,000 individuals.

We screened variants on an exome-focused genotyping array in >300,000 participants (replication in >280,000 participants) and identified 444 independent variants in 250 loci significantly associated with total cholesterol (TC), high-density-lipoprotein cholesterol (HDL-C), low-density-lipoprotein cholesterol (LDL-C), and/or triglycerides (TG). At two loci (JAK2 and A1CF), experimental analysis in mice showed lipid changes consistent with the human data. We also found that: (i) beta-thalassemia trait carriers displayed lower TC and were protected from coronary artery disease (CAD); (ii) excluding the CETP locus, there was not a predictable relationship between plasma HDL-C and risk for age-related macular degeneration; (iii) only some mechanisms of lowering LDL-C appeared to increase risk for type 2 diabetes (T2D); and (iv) TG-lowering alleles involved in hepatic production of TG-rich lipoproteins (TM6SF2 and PNPLA3) tracked with higher liver fat, higher risk for T2D, and lower risk for CAD, whereas TG-lowering alleles involved in peripheral lipolysis (LPL and ANGPTL4) had no effect on liver fat but decreased risks for both T2D and CAD.

New Blood Pressure-Associated Loci Identified in Meta-Analyses of 475 000 Individuals.

BACKGROUND: Genome-wide association studies have recently identified >400 loci that harbor DNA sequence variants that influence blood pressure (BP). Our earlier studies identified and validated 56 single nucleotide variants (SNVs) associated with BP from meta-analyses of exome chip genotype data. An additional 100 variants yielded suggestive evidence of association. METHODS AND RESULTS: Here, we augment the sample with 140 886 European individuals from the UK Biobank, in whom 77 of the 100 suggestive SNVs were available for association analysis with systolic BP or diastolic BP or pulse pressure. We performed 2 meta-analyses, one in individuals of European, South Asian, African, and Hispanic descent (pan-ancestry, ≈475 000), and the other in the subset of individuals of European descent (≈423 000). Twenty-one SNVs were genome-wide significant (P<5×10-8) for BP, of which 4 are new BP loci: rs9678851 (missense, SLC4A1AP), rs7437940 (AFAP1), rs13303 (missense, STAB1), and rs1055144 (7p15.2). In addition, we identified a potentially independent novel BP-associated SNV, rs3416322 (missense, SYNPO2L) at a known locus, uncorrelated with the previously reported SNVs. Two SNVs are associated with expression levels of nearby genes, and SNVs at 3 loci are associated with other traits. One SNV with a minor allele frequency <0.01, (rs3025380 at DBH) was genome-wide significant. CONCLUSIONS: We report 4 novel loci associated with BP regulation, and 1 independent variant at an established BP locus. This analysis highlights several candidate genes with variation that alter protein function or gene expression for potential follow-up.

Whole genome sequencing and imputation in isolated populations identify genetic associations with medically-relevant complex traits.

Next-generation association studies can be empowered by sequence-based imputation and by studying founder populations. Here we report ∼9.5 million variants from whole-genome sequencing (WGS) of a Cretan-isolated population, and show enrichment of rare and low-frequency variants with predicted functional consequences. We use a WGS-based imputation approach utilizing 10,422 reference haplotypes to perform genome-wide association analyses and observe 17 genome-wide significant, independent signals, including replicating evidence for association at eight novel low-frequency variant signals. Two novel cardiometabolic associations are at lead variants unique to the founder population sequences: chr16:70790626 (high-density lipoprotein levels beta -1.71 (SE 0.25), P=1.57 × 10-11, effect allele frequency (EAF) 0.006); and rs145556679 (triglycerides levels beta -1.13 (SE 0.17), P=2.53 × 10-11, EAF 0.013). Our findings add empirical support to the contribution of low-frequency variants in complex traits, demonstrate the advantage of including population-specific sequences in imputation panels and exemplify the power gains afforded by population isolates.

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.