Biology subjects

Hattersley, A. T.

Publications and source records attributed to Hattersley, A. T..

7 recordsLinked to original sources

bioRxiv2020

Fetal alleles predisposing to metabolically favourable adiposity are associated with higher birth weight

BackgroundHigher birth weight is associated with higher adult body mass index (BMI). If genetic variants can be identified with alleles that predispose to both greater fetal growth and to greater adult adiposity, such shared genetic effects might indicate biological processes important in the early patterning of adiposity. However, variants identified in genome-wide association studies of adult BMI have overall been only weakly associated with birth weight. Genetic variants have recently been identified where one allele is associated with higher adult body fat percentage, but lower risk of metabolic disease, likely due to a favourable body fat distribution. The effect of these adult metabolically favourable adiposity alleles on an individuals own birth weight is unknown. AimWe aimed to test the effect on birth weight of a fetal genetic predisposition to higher metabolically favourable adult adiposity and to compare this with the effects of a fetal genetic predisposition to higher adult BMI. We also aimed to examine the effects of a genetic predisposition to higher metabolically favourable adult adiposity or BMI on other birth anthropometric traits (length, ponderal index, head circumference and skinfold thickness) and on cord-blood insulin, leptin and adiponectin. MethodsWe used published GWAS data from up to 406,063 individuals to estimate the fetal effects on birth weight of alleles that are robustly associated with higher metabolically favourable adult adiposity or BMI. We additionally used 9,350 mother-child pairs from four cohorts to test the effects of the same alleles on other birth anthropometric traits and cord-blood markers. In all analyses, we adjusted for potential confounding due to the maternal genotype. We used inverse-variance weighted meta-analyses to combine summary data across SNPs. ResultsFetal genetic predisposition to higher metabolically favourable adult adiposity was associated with higher birth weight (10 grams (95% CI: 7 to 13) higher mean birth weight per 1 SD pooled "genetic score"). Fetal genetic predisposition to higher adult BMI was also associated with higher birth weight, but with a smaller magnitude of effect (4 grams (95% CI: 0 to 8) higher mean birth weight per 1 SD pooled "genetic score") and with higher heterogeneity across SNPs. Effects on other birth anthropometric outcomes were consistent with the effect on birth weight but with wider confidence intervals. There was no strong evidence for an effect on cord-blood markers. ConclusionsSome genetic variants previously linked to adult adiposity influence birth weight. Alleles that predispose to higher metabolically favourable adult adiposity collectively have a stronger effect on birth weight than those predisposing to higher BMI. This suggests that the early accumulation of a metabolically favourable fat distribution might underlie part of the observed association between higher birth weight and higher adult BMI. Larger samples are needed to clarify the effects on other birth anthropometric measures and cord-blood markers.

genetics↗

bioRxiv2020

Common maternal and fetal genetic variants show expected polygenic effects on the probability of being born small- or large-for-gestational-age (SGA or LGA), except in the smallest 3% of babies

Babies born clinically Small- or Large-for-Gestational-Age (SGA or LGA; sex- and gestational age-adjusted birth weight (BW) <10th or >90th percentile, respectively), are at higher risks of complications. SGA and LGA include babies who have experienced growth-restriction or overgrowth, respectively, and babies who are naturally small or large. However, the relative proportions within each group are unclear. We aimed to assess the extent to which the genetics of normal variation in birth weight influence the probability of SGA/LGA. We calculated independent fetal and maternal genetic scores (GS) for BW in 12,125 babies and 5,187 mothers. These scores capture the direct fetal and indirect maternal (via intrauterine environment) genetic contributions to BW, respectively. We also calculated maternal fasting glucose (FG) and systolic blood pressure (SBP) GS. We tested associations between each GS and probability of SGA or LGA. For the BW GS, we used simulations to assess evidence of deviation from an expected polygenic model. Higher BW GS were strongly associated with lower odds of SGA and higher odds of LGA (ORfetal=0.65 (0.60,0.71) and 1.47 (1.36,1.59); ORmaternal=0.80 (0.76,0.87) and 1.23 (1.15,1.31), respectively per 1 decile higher GS). Associations were in accordance with a polygenic model except in the smallest 3% of babies (Pfetal=0.0034, Pmaternal=0.023). Higher maternal GS for FG and SBP were associated with higher odds of LGA and SGA respectively (both P<0.01). While lower maternal FG and SBP are generally considered healthy in pregnancy, we found some evidence of association with higher odds of SGA (P=0.015) and LGA (P=0.14) respectively. We conclude that common genetic variants contribute to risk of SGA and LGA, but that additional factors become more important for risk of SGA in the smallest 3% of babies. Naturally low maternal glucose and blood pressure levels may additionally contribute to risk of SGA and LGA, respectively. Author SummaryBabies in the lowest or highest 10% of the population distribution of birth weight (BW) for a given gestational age are referred to as Small- or Large-for-Gestational-Age (SGA or LGA) respectively. These babies have higher risks of complications compared to babies with BW closer to the mean. SGA and LGA babies may have experienced growth restriction or overgrowth, respectively, but may alternatively just be at the tail ends of the normal growth distribution. The relative proportions of normal vs. sub-optimal growth within these groups is unclear. To examine the role of common genetic variation in SGA and LGA, we tested their associations with a fetal genetic score (GS) for BW in 12,125 European-ancestry individuals. We also tested associations with maternal GS (5,187 mothers) for offspring BW, fasting glucose and systolic blood pressure, each of which influences fetal growth via the in utero environment. We found all fetal and maternal GS were associated with SGA and LGA, supporting strong maternal and fetal genetic contributions to birth weight in both tails of the distribution. However, within the smallest 3% of babies, the maternal and fetal GS for BW were higher than expected, suggesting factors additional to common genetic variation are more important in determining birth weight in these very small babies.

genetics↗

bioRxiv2019

Very rare pathogenic genetic variants detected by SNP-chips are usually false positives: implications for direct-to-consumer genetic testing

ObjectivesTo determine the analytical validity of SNP-chips for genotyping very rare genetic variants. DesignRetrospective study using data from two publicly available resources, the UK Biobank and the Personal Genome Project. SettingResearch biobanks and direct-to-consumer genetic testing in the UK and USA. Participants49,908 individuals recruited to UK Biobank, and 21 individuals who purchased consumer genetic tests and shared their data online via the Personal Genomes Project. Main outcome measuresWe assessed the analytical validity of genotypes from SNP-chips (index test) with sequencing data (reference standard). We evaluated the genotyping accuracy of the SNP-chips and split the results by variant frequency. We went on to select rare pathogenic variants in the BRCA1 and BRCA2 genes as an exemplar for detailed analysis of clinically-actionable variants in UK Biobank, and assessed BRCA-related cancers (breast, ovarian, prostate and pancreatic) in participants using cancer registry data. ResultsSNP-chip genotype accuracy is high overall; sensitivity, specificity and precision are all >99% for 108,574 common variants directly genotyped by the UK Biobank SNP-chips. However, the likelihood of a true positive result reduces dramatically with decreasing variant frequency; for variants with a frequency <0.001% in UK Biobank the precision is very low and only 16% of 4,711 variants from the SNP-chips confirm with sequencing data. Results are similar for SNP-chip data from the Personal Genomes Project, and 20/21 individuals have at least one rare pathogenic variant that has been incorrectly genotyped. For pathogenic variants in the BRCA1 and BRCA2 genes, the overall performance metrics of the SNP-chips in UK Biobank are sensitivity 34.6%, specificity 98.3% and precision 4.2%. Rates of BRCA-related cancers in individuals in UK Biobank with a positive SNP-chip result are similar to age-matched controls (OR 1.28, P=0.07, 95% CI: 0.98 to 1.67), while sequence-positive individuals have a significantly increased risk (OR 3.73, P=3.5x10-12, 95% CI: 2.57 to 5.40). ConclusionSNP-chips are extremely unreliable for genotyping very rare pathogenic variants and should not be used to guide health decisions without validation. SUMMARY BOXO_ST_ABSSection 1: What is already known on this topicC_ST_ABSSNP-chips are an accurate and affordable method for genotyping common genetic variants across the genome. They are often used by direct-to-consumer (DTC) genetic testing companies and research studies, but there several case reports suggesting they perform poorly for genotyping rare genetic variants when compared with sequencing. Section 2: What this study addsOur study confirms that SNP-chips are highly inaccurate for genotyping rare, clinically-actionable variants. Using large-scale SNP-chip and sequencing data from UK Biobank, we show that SNP-chips have a very low precision of <16% for detecting very rare variants (i.e. the majority of variants with population frequency of <0.001% are false positives). We observed a similar performance in a small sample of raw SNP-chip data from DTC genetic tests. Very rare variants assayed using SNP-chips should not be used to guide health decisions without validation.

genetics↗

bioRxiv2019

Women with isolated fasting hyperglycemia in pregnancy are at a higher genetic risk for type 2 diabetes

BackgroundUsing genetic scores for fasting plasma glucose (FPG GS) and type 2 diabetes (T2D GS), we investigated whether the fasting, 1-hour and 2-hour glucose thresholds from the WHO 2013 criteria for gestational diabetes (GDM) have different implications for genetic susceptibility to raised fasting glucose and type 2 diabetes in women from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) and Atlantic Diabetes in Pregnancy (DIP) studies. MethodsCases were divided into three subgroups: (i) FPG [≥]5.1 mmol/L only, n=222; (ii) 1-hour glucose post 75 g oral glucose load [≥]10 mmol/L only, n=154 (iii) 2-hour glucose [≥]8.5 mmol/L only, n=73); and (iv) both FPG [≥]5.1 mmol/L and either of a 1-hour glucose [≥]10 mmol/L or 2-hour glucose [≥]8.5 mmol/L, n=172. We compared the FPG and T2D GS of these groups with controls (n=3,091) in HAPO and DIP separately. ResultsIn HAPO and DIP, the mean FPG GS in women with a FPG [≥]5.1 mmol/L, either on its own or with 1-hour glucose [≥]10 mmol/L or 2-hour glucose [≥]8.5 mmol/L, was higher than controls (all P <0.01). Mean T2D GS in women with a raised FPG alone or with either a raised 1-hour or 2-hour glucose was higher than controls (all P <0.05). GDM defined by 1-hour or 2-hour hyperglycaemia only was also associated with a higher T2D GS than controls (all P <0.05). ConclusionsThe different diagnostic categories that are part of the WHO 2013 criteria for GDM identify women with a genetic predisposition to type 2 diabetes as well as a risk for adverse pregnancy outcomes.

genetics↗

bioRxiv2018

Assessing the pathogenicity, penetrance and expressivity of putative disease-causing variants in a population setting

Over 100,000 genetic variants are classified as disease-causing in public databases. However, the true penetrance of many of these rare alleles is uncertain and may be over-estimated by clinical ascertainment. As more people undergo genome sequencing there is an increasing need to assess the true penetrance of alleles. Until recently, this was not possible in a population-based setting. Here, we use data from 388,714 UK Biobank (UKB) participants of European ancestry to assess the pathogenicity and penetrance of putatively clinically important rare variants.\n\nAlthough rare variants are harder to genotype accurately than common variants, we were able to classify 1,244 of 4,585 (27%) putatively clinically relevant rare variants genotyped on the UKB microarray as high-quality. We defined \"rare\" as variants with a minor allele frequency of <0.01, and \"clinically relevant\" as variants that were either classified as pathogenic/likely pathogenic in ClinVar or are in genes known to cause two specific monogenic diseases in which we have some expertise: Maturity-Onset Diabetes of the Young (MODY) and severe developmental disorders (DD). We assessed the penetrance and pathogenicity of these high-quality variants by testing their association with 401 clinically-relevant traits available in UKB.\n\nWe identified 27 putatively clinically relevant rare variants associated with a UKB trait but that exhibited reduced penetrance or variable expressivity compared with their associated disease. For example, the P415A PER3 variant that has been reported to cause familial advanced sleep phase syndrome is present at 0.5% frequency in the population and associated with an odds ratio of 1.38 for being a morning person (P=2x10-18). We also observed novel associations with relevant traits for heterozygous carriers of some rare recessive conditions, e.g. heterozygous carriers of the R799W ERCC4 variant that causes Xeroderma pigmentosum were more susceptible to sunburn (one extra sunburn episode reported, P=2x10-8). Within our two disease subsets, we were able to refine the penetrance estimate for the R114W HNF4A variant in diabetes (only ~10% by age 40yrs) and refute the previous disease-association of RNF135 in developmental disorders.\n\nIn conclusion, this study shows that very large population-based studies will help refine the penetrance estimates of rare variants. This information will be important for anyone receiving information about their health based on putatively pathogenic variants.

genetics↗

bioRxiv2018

Meta-analysis of genome-wide association studies for body fat distribution in 694,649 individuals of European ancestry

One in four adults worldwide are either overweight or obese. Epidemiological studies indicate that the location and distribution of excess fat, rather than general adiposity, is most informative for predicting risk of obesity sequellae, including cardiometabolic disease and cancer. We performed a genome-wide association study meta-analysis of body fat distribution, measured by waist-to-hip ratio adjusted for BMI (WHRadjBMI), and identified 463 signals in 346 loci. Heritability and variant effects were generally stronger in women than men, and we found approximately one-third of all signals to be sexually dimorphic. The 5% of individuals carrying the most WHRadjBMI-increasing alleles were 1.62 times more likely than the bottom 5% to have a WHR above the thresholds used for metabolic syndrome. These data, made publicly available, will inform the biology of body fat distribution and its relationship with disease.

genetics↗

bioRxiv2017

Heterozygous RFX6 protein truncating variants cause Maturity-Onset Diabetes of the Young (MODY) with reduced penetrance

Finding new genetic causes of monogenic diabetes can help to understand development and function of the human pancreas. We aimed to find novel protein-truncating variants causing Maturity-Onset Diabetes of the Young (MODY), a subtype of monogenic diabetes. We used a combination of next-generation sequencing of MODY cases with unknown aetiology along with comparisons to the ExAC database to identify new MODY genes. In the discovery cohort of 36 European patients, we identified two probands with novel RFX6 heterozygous nonsense variants. RFX6 protein truncating variants were enriched in the MODY discovery cohort compared to the European control population within ExAC (odds ratio, OR=131, P=lxl0-4). We found similar results in non-Finnish European (n=348, OR=43, P=5xl0-5) and Finnish (n=80, OR=22, P=1xl0-6) replication cohorts. The overall meta-analysis OR was 34 (P=lxl0-16). RFX6 heterozygotes had reduced penetrance of diabetes compared to common HNF1A and HNF4A-MODY mutations (27%, 70% and 55% at 25 years of age, respectively). The hyperglycaemia resulted from beta-cell dysfunction and was associated with lower fasting and stimulated gastric inhibitory polypeptide (GIP) levels. Our study demonstrates that heterozygous RFX6 protein truncating variants are associated with MODY with reduced penetrance.

genetics↗