Findings from genome-wide association studies have facilitated the generation of genetic predictors for many common human phenotypes. Stratifying individuals misaligned to a genetic predictor based ...on common variants may be important for follow-up studies that aim to identify alternative causal factors. Using genome-wide imputed genetic data, we aimed to classify 158,951 unrelated individuals from the UK Biobank as either concordant or deviating from two well-measured phenotypes. We first applied our methods to standing height: our primary analysis classified 244 individuals (0.15%) as misaligned to their genetically predicted height. We show that these individuals are enriched for self-reporting being shorter or taller than average at age 10, diagnosed congenital malformations, and rare loss-of-function variants in genes previously catalogued as causal for growth disorders. Secondly, we apply our methods to LDL cholesterol (LDL-C). We classified 156 (0.12%) individuals as misaligned to their genetically predicted LDL-C and show that these individuals were enriched for both clinically actionable cardiovascular risk factors and rare genetic variants in genes previously shown to be involved in metabolic processes. Individuals whose LDL-C was higher than expected based on the genetic predictor were also at higher risk of developing coronary artery disease and type-two diabetes, even after adjustment for measured LDL-C, BMI and age, suggesting upward deviation from genetically predicted LDL-C is indicative of generally poor health. Our results remained broadly consistent when performing sensitivity analysis based on a variety of parametric and non-parametric methods to define individuals deviating from polygenic expectation. Our analyses demonstrate the potential importance of quantitatively identifying individuals for further follow-up based on deviation from genetic predictions.
Full text
Available for:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Genetic variants that severely alter protein products (e.g. nonsense, frameshift) are often associated with disease. For some genes, these predicted loss-of-function variants (pLoFs) are observed ...throughout the gene, whilst in others, they occur only at specific locations. We hypothesised that, for genes linked with monogenic diseases that display incomplete penetrance, pLoF variants present in apparently unaffected individuals may be limited to regions where pLoFs are tolerated. To test this, we investigated whether pLoF location could explain instances of incomplete penetrance of variants expected to be pathogenic for Mendelian conditions.
We used exome sequence data in 454,773 individuals in the UK Biobank (UKB) to investigate the locations of pLoFs in a population cohort. We counted numbers of unique pLoF, missense, and synonymous variants in UKB in each quintile of the coding sequence (CDS) of all protein-coding genes and clustered the variants using Gaussian mixture models. We limited the analyses to genes with ≥ 5 variants of each type (16,473 genes). We compared the locations of pLoFs in UKB with all theoretically possible pLoFs in a transcript, and pathogenic pLoFs from ClinVar, and performed simulations to estimate the false-positive rate of non-uniformly distributed variants.
For most genes, all variant classes fell into clusters representing broadly uniform variant distributions, but genes in which haploinsufficiency causes developmental disorders were less likely to have uniform pLoF distribution than other genes (P < 2.2 × 10
). We identified a number of genes, including ARID1B and GATA6, where pLoF variants in the first quarter of the CDS were rescued by the presence of an alternative translation start site and should not be reported as pathogenic. For other genes, such as ODC1, pLoFs were located approximately uniformly across the gene, but pathogenic pLoFs were clustered only at the end, consistent with a gain-of-function disease mechanism.
Our results suggest the potential benefits of localised constraint metrics and that the location of pLoF variants should be considered when interpreting variants.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Vasomotor symptoms (VMS) can often significantly impact women's quality of life at menopause. In vivo studies have shown that increased neurokinin B (NKB) / neurokinin 3 receptor (NK3R) signalling ...contributes to VMS, with previous genetic studies implicating the TACR3 gene locus that encodes NK3R. Large-scale genomic analyses offer the possibility of biological insights but few such studies have collected data on VMS, while proxy phenotypes such as hormone replacement therapy (HRT) use are likely to be affected by changes in clinical practice. We investigated the genetic basis of VMS by analysing routinely-collected health records.
We performed a GWAS of VMS derived from linked primary-care records and cross-sectional self-reported HRT use in up to 153,152 women from UK Biobank, a population-based cohort. In a subset of this cohort (n = 39,356), we analysed exome-sequencing data to test the association with VMS of rare deleterious genetic variants. Finally, we used Mendelian randomisation analysis to investigate the reasons for HRT use over time.
Our GWAS of health-records derived VMS identified a genetic signal near TACR3 associated with a lower risk of VMS (OR=0.76 (95% CI 0.72,0.80) per A allele, P=3.7x10
), which was consistent with previous studies, validating this approach. Conditional analyses demonstrated independence of genetic signals for puberty timing and VMS at the TACR3 locus, including a rare variant predicted to reduce functional NK3R levels that was associated with later menarche (P = 5 × 10
) but showed no association with VMS (P = 0.6). Younger menopause age was causally-associated with greater HRT use before 2002 but not after.
We provide support for TACR3 in the genetic basis of VMS but unexpectedly find that rare genomic variants predicted to lower NK3R levels did not modify VMS, despite the proven efficacy of NK3R antagonists. Using genomics we demonstrate changes in genetic associations with HRT use over time, arising from a change in clinical practice since the early 2000s, which is likely to reflect a switch from preventing post-menopausal complications in women with earlier menopause to primarily treating VMS. Our study demonstrates that integrating routinely-collected primary care health records and genomic data offers great potential for exploring the genetic basis of symptoms.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize ...Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Introduction & Objective: Hundreds of common genetic variants have been associated with type 2 diabetes and glycated haemoglobin (HbA1c). However, the vast majority of these variants lie in regions ...of the genome which are not protein coding, making it difficult to identify biological pathways. We aimed to identify rare non-coding variants to aid in pinpointing causal genes and variants. Methods: We performed a whole-genome sequencing association analysis of non-coding variation in 200,000 UK Biobank participants. We stratified our analysis by three genetically-inferred ancestries: European-like (EUR), African-like (AFR) and South Asian-like (SAS). Results: We identified 4 rare (MAF<0.1%) variants associated with HbA1c, downstream of the haemoglobin alpha gene-cluster based on an analysis of EUR-like participants. In our analysis of 3,184 AFR-like individuals, only one variant (16:715289:T:C) showed evidence of replication. This likely-causal variant lies in the first element of the kozak sequence of meteorin (METRN), and was associated with substantially increased HbA1c levels (beta = 4.87mmol/mol 3.54, 6.21, P = 8.14e-13). We observed no evidence of association with common blood cell traits, circulating glucose, or haemoglobin. We replicated our result in the recently released additional 300,000 UKB WGS samples (beta = 6.02mmol/mol 4.83, 7.20, P = 2.93e-17). We attempted to replicate our findings in All of Us (N = 250,000), but found that the allele was substantially less frequent than in UKB (MAF = 3.7e-6 vs. 1.9e-4). The alternate allele was not present in individuals in TOPMed with HbA1c measures. Conclusion: Our results suggest that this variant may be a founder effect in the UK population acting through an alteration of glucose uptake to red blood cells. Identification of a novel variant in only 200k individuals with whole-genome sequences suggests a high yield of novel variants and biological pathways from upcoming releases of millions whole-genomes. Disclosure G. Hawkes: None. K.A. Patel: None. I. Barroso: Stock/Shareholder; GlaxoSmithKline plc, NeoGenomics (NASDAQ: NEO). T.M. Frayling: None. A. Manning: None. M.N. Weedon: None. Funding Innovative Medicines Initiative 2 Joint Undertaking (875534)
Higher BMI during childhood is associated with an increased likelihood of remaining overweight later in life, leading to higher risk of developing type 2 diabetes (T2D). Using a Mendelian ...randomisation approach, a recent study found no evidence that childhood BMI has a direct causal effect on T2D. However, the extent to which high BMI in childhood directly alters insulin secretion and sensitivity in later life requires further investigation.
We aimed to use genetic variants associated with differential effects on childhood and adult BMI to test their separate effects on insulin secretion and insulin sensitivity. We first generated a measure of childhood BMI aged 10 using self-reported categories in the UK Biobank, which we approximated to a normal distribution. We then performed separate genome wide association studies (GWAS) of childhood and adult BMI. This approach increased the number of genetic instruments by a factor of two as compared to previous methods. We used a multivariable Mendelian Randomisation approach, with childhood and adult BMI as exposure variables, and 5 measures of insulin secretion and insulin sensitivity in nondiabetic adults from previous GWAS studies as outcome variables.
We found no evidence (at p<0.05) that higher BMI in childhood has a direct adverse effect on type 2 diabetes (OR 0.94, 95%CI 0.82-1.08), fasting insulin (OR 1.00, 0.95 - 1.05), insulin sensitivity (OR 1.11, 0.97-1.27) or sensitivity-index adjusted acute insulin response (OR 1.11, 0.88-1.42) in adults. There was some evidence of a protective effect, with higher childhood BMI associated with lower fasting glucose (OR 0.96, 0.93 - 1.00) and insulin secretion (OR 1.30, 1.04 - 1.63). Crucially, our results are consistent with no adverse direct effect of higher childhood BMI on adult type 2 diabetes, insulin secretion or sensitivity.
Disclosure
G. Hawkes: None. T. G. Richardson: None. G. M. Power: None. G. Davey smith: None. T. M. Frayling: None.
Funding
Innovative Medicines Initiative 2 Joint Undertaking (875534)
Magnetic helicity, the measure of entanglement within a magnetic field, has the capability to further our knowledge of the magnetic fields which are ubiquitous across the physical universe. ...Discovered half a century ago by Lodewijk Woltjer in 1958, it was only given physical meaning by Keith Moffatt in 1969. Progress was initially slow due to the constraints on its calculation: it is assumed that the volume within which we wish to measure helicity does not have any magnetic field crossing its boundaries. But, in 1984, Mitchell Berger and George Field provided a resolution to this problem which allowed it to be applied to open astrophysical fields. From there, and particularly in the last two decades, interest in magnetic helicity has grown exponentially within the research community, resulting in this thesis.We will begin by providing a semi–formal introduction to the topic, in particular that of magnetohydrodynamics, which describes how a magnetic field and associated plasma co-interact. We provide a mathematical introduction to magnetic helicity, and demonstrate that unsolved problems remain in our understanding of the Sun’s magnetic field that are associated with its magnetic helicity.With this knowledge in hand, we first tackle the topic of predicting the Solar Cycle, which has been an unachieved goal of the solar physics community for longer than we care to remember. We show that magnetic helicity, which is intrinsically linked to the emergence of sunspots, is a statistically stronger candidate for the predictor of activity than that of the polar field strength, which is the current ’best of the worst’ of the known predictors.We then, for the first time, measure how much helicity is generated on the solar surface due to shear motions in a surface flux transport model, which is a method of modelling the magnetic field on the surface of the sun. We show that the results are not as obvious as we expect, and indeed that the flux of magnetic helicity within each hemisphere is carefully balanced between latitudes. We also provide an estimate of how much helicity is produced in a solar cycle, and correlate this with the dipole strength of that cycle.This is followed by the main result of the thesis: we demonstrate that helicity can be completely generalised for any physical system in terms of a two–point correlation, and fully described in terms of spatial scales and locality using wavelet analysis. In particular, we show that our generalised measure of helicity offers a physical meaning to this localisation. Our methods are demonstrated to have some notable advantages to that of Fourier analysis, which is shown to sometimes produce spurious results.Finally, we explore the hypothesis that the shape of a magnetic field domain can contribute to the magnetic helicity when using a toroidal–poloidal decomposition. Indeed, in some cases the asymmetry contains the entirety of the magnetic helicity, which we demonstrate numerically.
Abstract
Whole genome sequencing (WGS) from large clinically unselected cohorts provides a unique opportunity to assess the penetrance and expressivity of rare and/or known pathogenic mitochondrial ...variants in population. Using WGS from 179 862 clinically unselected individuals from the UK Biobank, we performed extensive single and rare variant aggregation association analyses of 15 881 mtDNA variants and 73 known pathogenic variants with 15 mitochondrial disease-relevant phenotypes. We identified 12 homoplasmic and one heteroplasmic variant (m.3243A>G) with genome-wide significant associations in our clinically unselected cohort. Heteroplasmic m.3243A>G (MAF = 0.0002, a known pathogenic variant) was associated with diabetes, deafness and heart failure and 12 homoplasmic variants increased aspartate aminotransferase levels including three low-frequency variants (MAF ~0.002 and beta~0.3 SD). Most pathogenic mitochondrial disease variants (n = 66/74) were rare in the population (<1:9000). Aggregated or single variant analysis of pathogenic variants showed low penetrance in unselected settings for the relevant phenotypes, except m.3243A>G. Multi-system disease risk and penetrance of diabetes, deafness and heart failure greatly increased with m.3243A>G level ≥ 10%. The odds ratio of these traits increased from 5.61, 12.3 and 10.1 to 25.1, 55.0 and 39.5, respectively. Diabetes risk with m.3243A>G was further influenced by type 2 diabetes genetic risk. Our study of mitochondrial variation in a large-unselected population identified novel associations and demonstrated that pathogenic mitochondrial variants have lower penetrance in clinically unselected settings. m.3243A>G was an exception at higher heteroplasmy showing a significant impact on health making it a good candidate for incidental reporting.
Iterative advances in understanding of the genetics of type 1 diabetes have identified >70 genetic regions associated with risk of the disease, including strong associations across the HLA class II ...region that account for >50% of heritability. The increased availability of genetic data combined with the decreased costs of generating these data, have facilitated the development of polygenic scores that aggregate risk variants from associated loci into a single number: either a genetic risk score (GRS) or a polygenic risk score (PRS). PRSs incorporate the risk of many possibly correlated variants from across the genome, even if they do not reach genome-wide significance, whereas GRSs estimate the cumulative contribution of a smaller subset of genetic variants that reach genome-wide significance. Type 1 diabetes GRSs have utility in diabetes classification, aiding discrimination between type 1 diabetes, type 2 diabetes and MODY. Type 1 diabetes GRSs are also being used in newborn screening studies to identify infants at risk of future presentation of the disease. Most early studies of type 1 diabetes genetics have been conducted in European ancestry populations, but, to develop accurate GRSs across diverse ancestries, large case–control cohorts from non-European populations are still needed. The current barriers to GRS implementation within healthcare are mainly related to a lack of guidance and knowledge on integration with other biomarkers and clinical variables. Once these limitations are addressed, there is huge potential for ‘test and treat’ approaches to be used to tailor care for individuals with type 1 diabetes.
Graphical Abstract
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Aims/hypothesis
Determining how high BMI at different time points influences the risk of developing type 2 diabetes and affects insulin secretion and insulin sensitivity is critical.
Methods
By ...estimating childhood BMI in 441,761 individuals in the UK Biobank, we identified which genetic variants had larger effects on adulthood BMI than on childhood BMI, and vice versa. All genome-wide significant genetic variants were then used to separate the independent genetic effects of high childhood BMI from those of high adulthood BMI on the risk of type 2 diabetes and insulin-related phenotypes using Mendelian randomisation. We performed two-sample MR using external studies of type 2 diabetes, and oral and intravenous measures of insulin secretion and sensitivity.
Results
We found that a childhood BMI that was one standard deviation (1.97 kg/m
2
) higher than the mean, corrected for the independent genetic liability to adulthood BMI, was associated with a protective effect for seven measures of insulin sensitivity and secretion, including increased insulin sensitivity index (β=0
.
15; 95% CI 0.067, 0.225;
p
=2.79×10
−4
) and reduced fasting glucose levels (β=−0.053; 95% CI −0.089, −0.017;
p
=4.31×10
−3
). However, there was little to no evidence of a direct protective effect on type 2 diabetes (OR 0.94; 95% CI 0.85, 1.04;
p
=0.228) independently of genetic liability to adulthood BMI.
Conclusions/interpretation
Our results provide evidence of the protective effect of higher childhood BMI on insulin secretion and sensitivity, which are crucial intermediate diabetes traits. However, we stress that our results should not currently lead to any change in public health or clinical practice, given the uncertainty regarding the biological pathway of these effects and the limitations of this type of study.
Graphical Abstract
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
