Biology subjects

Walters, R. G.

Publications and source records attributed to Walters, R. G..

5 recordsLinked to original sources

bioRxiv2024

Natural selection exerted by historical coronavirus epidemic(s): comparative genetic analysis in China Kadoorie Biobank and UK Biobank

BackgroundPathogens have been one of the primary sources of natural selection affecting modern humans. The footprints of historical selection events - "selective sweeps" - can be detected in the genomes of present-day individuals. Previous analyses of 629 samples from the 1000 Genomes Project suggested that an ancient coronavirus epidemic [~]20,000 years ago drove multiple selective sweeps in the ancestors of present-day East Asians, but not in other worldwide populations. ResultsUsing a much larger genetic dataset of 76,719 unrelated individuals from each of the China Kadoorie Biobank (CKB) and UK Biobank (UKB) to identify regions of long-range linkage disequilibrium, we further investigated signatures of past selective sweeps and how they reflect previous viral epidemics. Using independently-curated lists of human host proteins which interact physically or functionally with viruses (virus-interacting proteins; VIPs), we found enrichment in CKB for regions of long-range linkage disequilibrium at genes encoding VIPs for coronaviruses, but not DNA viruses. By contrast, we found no clear evidence for any VIP enrichment in UKB. These findings were supported by additional analyses using saltiLASSi, a selection-scan method robust to false positives caused by demographic events. By contrast, for GWAS signals for SARS-Cov2 susceptibility (critical illness, hospitalisation, and reported infection), there was no difference between UKB and CKB in the number located at or near signals of selection, as expected for a novel virus which has had no opportunity to impact the CKB/UKB study populations. ConclusionsTogether, these results provide evidence of selection events consistent with historical coronavirus epidemic(s) originating in East Asia. These results show how biobank-scale datasets and evolutionary genomics theory can provide insight into the study of past epidemics. The results also highlights how historic infectious diseases epidemics can shape the genetic architecture of present-day human populations.

genomics↗

bioRxiv2023

Genetics of skeletal proportions in two different populations

Human height can be divided into sitting height and leg length, reflecting growth of different parts of the skeleton whose relative proportions are captured by the ratio of sitting to total height (as sitting height ratio, SHR). Height is a highly heritable trait, and its genetic basis has been well-studied. However, the genetic determinants of skeletal proportion are much less well-characterized. Expanding substantially on past work, we performed a genome-wide association study (GWAS) of SHR in [~]450,000 individuals with European ancestry and [~]100,000 individuals with East Asian ancestry from the UK and China Kadoorie Biobanks. We identified 565 loci independently associated with SHR, including all genomic regions implicated in prior GWAS in these ancestries. While SHR loci largely overlap height-associated loci (P < 0.001), the fine-mapped SHR signals were often distinct from height. We additionally used fine-mapped signals to identify 36 credible sets with heterogeneous effects across ancestries. Lastly, we used SHR, sitting height, and leg length to identify genetic variation acting on specific body regions rather than on overall human height.

genetics↗

bioRxiv2021

Multi-Ancestry Meta-Analysis yields novel genetic discoveries and ancestry-specific associations

We present a new method, Multi-Ancestry Meta-Analysis (MAMA), which combines genome-wide association study (GWAS) summary statistics from multiple populations to produce new summary statistics for each population, identifying novel loci that would not have been discovered in either set of GWAS summary statistics alone. In simulations, MAMA increases power with less bias and generally lower type-1 error rate than other multi-ancestry meta-analysis approaches. We apply MAMA to 23 phenotypes in East-Asian- and European-ancestry populations and find substantial gains in power. In an independent sample, novel genetic discoveries from MAMA replicate strongly.

genomics↗

bioRxiv2019

Lifelong genetically lowered sclerostin and risk of cardiovascular disease.

BackgroundInhibition of sclerostin is a novel therapeutic approach to lowering fracture risk. However, phase III randomised controlled trials (RCTs) of romosozumab, a monoclonal antibody that inhibits sclerostin, suggest an imbalance of serious cardiovascular events. MethodsWe used two independent genetic variants (rs7209826 and rs188810925) in SOST (encoding sclerostin) associated with bone mineral density (BMD) as proxies for therapeutic inhibition of sclerostin. We estimated the effects on risk of osteoporosis, fracture, coronary heart disease (CHD) and a further 22 cardiometabolic risk factors and diseases, by combining data from up to 478,967 participants of European ancestry from three prospective cohorts and up to 1,030,836 participants from nine GWAS consortia. In addition, we performed meta-analyses of cardiovascular outcome data from phase III RCTs of romosozumab. ResultsMeta-analysis of RCTs identified a higher risk of cardiac ischemic events in patients randomised to romosozumab (25 events among 4,298 individuals; odds ratio [OR] 2{middle dot}98; 95% confidence interval [CI], 1{middle dot}18 to 7{middle dot}55; P=0{middle dot}017). Scaled to the equivalent dose of romosozumab (210mg/month; 0{middle dot}09 g/cm2 higher BMD), the SOST variants associated with lower risk of fracture (OR, 0{middle dot}59; 95% CI, 0{middle dot}54-0{middle dot}66; P= 1{middle dot}4x10-24), and osteoporosis (OR, 0{middle dot}43; 95% CI, 0{middle dot}36-0{middle dot}52; P=2{middle dot}4x10-18). The SOST variants associated with higher risk of myocardial infarction and/or coronary revascularisation (69,649 cases; OR, 1{middle dot}18; 95% CI, 1{middle dot}06-1{middle dot}32; P=0{middle dot}003) and type 2 diabetes (OR 1{middle dot}15; 95% CI, 1{middle dot}05-1{middle dot}27; P=0{middle dot}003), higher systolic blood pressure (1{middle dot}3mmHg; 95% CI 0{middle dot}8-1{middle dot}9; P=5{middle dot}9x10-6) and waist-to-hip-ratio adjusted for BMI (0{middle dot}05 SDs; 95% CI, 0{middle dot}02 to 0{middle dot}08; P=8{middle dot}5x10-4). ConclusionsGenetically and therapeutically lowered sclerostin leads to higher risk of cardiovascular events. Rigorous evaluation of the cardiovascular safety of romosozumab and other sclerostin inhibitors is warranted.

genetics↗

bioRxiv2019

The transferability of lipid-associated loci across African, Asian and European cohorts

The under-representation of non-European samples in genome-wide association studies could ultimately restrict who benefits from medical advances through genomic science. Our aim was therefore to address the fundamental question whether causal variants for blood lipids are shared across populations.\n\nA polygenic score based on established LDL-cholesterol-associated loci from European discovery samples had consistent effects on serum levels in samples from the UK, Uganda and Greek population isolates (correlation coefficient r=0.23 to 0.28 per LDL standard deviation, p<1.9x10-14). Trans-ethnic genetic correlations between European ancestry, Chinese and Japanese cohorts did not differ significantly from 1 for HDL, LDL and triglycerides. In each study, >60% of major lipid loci displayed evidence of replication with one exception. There was evidence for an effect on serum levels in the Ugandan samples for only 10% of major triglyceride loci. The PRS was only weakly associated in this group (r=0.06, SE=0.013). We establish trans-ethnic colocalization as a method to distinguish shared from population-specific trait loci.\n\nOur results provide evidence for high levels of consistency of genetic associations for cholesterol biomarkers across populations. However, we also demonstrate that the degree of shared causal genetic architecture can be population-, trait- and locus-specific. Efforts to implement genetic risk prediction in clinical settings should account for this.

genetics↗