Genome-wide association studies (GWAS) have revealed that the genetic contribution to certain complex diseases is well-described by Fisher’s infinitesimal model in which a vast number of ...polymorphisms each confer a small effect. Under Fisher’s model, variants have
additive
effects both across loci and within loci. However, the latter assumption is at odds with the common observation of dominant or recessive rare alleles responsible for monogenic disorders. Here, we searched for evidence of non-additive (dominant or recessive) effects for GWAS variants known to confer susceptibility to the highly heritable quantitative trait, refractive error. Of 146 GWAS variants examined in a discovery sample of 228,423 individuals whose refractive error phenotype was inferred from their age-of-onset of spectacle wear, only 8 had even nominal evidence (
p
< 0.05) of non-additive effects. In a replication sample of 73,577 individuals who underwent direct assessment of refractive error, 1 of these 8 variants had robust independent evidence of non-additive effects (rs7829127 within
ZMAT4
,
p
= 4.76E−05) while a further 2 had suggestive evidence (rs35337422 in
RD3L
,
p
= 7.21E−03 and rs12193446 in
LAMA2
,
p
= 2.57E−02). Accounting for non-additive effects had minimal impact on the accuracy of a polygenic risk score for refractive error (
R
2
= 6.04% vs. 6.01%). Our findings demonstrate that very few GWAS variants for refractive error show evidence of a departure from an additive mode of action and that accounting for non-additive risk variants offers little scope to improve the accuracy of polygenic risk scores for myopia.
Myopia most often develops during school age, with the highest incidence in countries with intensive education systems. Interactions between genetic variants and educational exposure are hypothesized ...to confer susceptibility to myopia, but few such interactions have been identified. Here, we aimed to identify genetic variants that interact with education level to confer susceptibility to myopia. Two groups of unrelated participants of European ancestry from UK Biobank were studied. A 'Stage-I' sample of 88,334 participants whose refractive error (avMSE) was measured by autorefraction and a 'Stage-II' sample of 252,838 participants who self-reported their age-of-onset of spectacle wear (AOSW) but who did not undergo autorefraction. Genetic variants were prioritized via a 2-step screening process in the Stage-I sample: Step 1 was a genome-wide association study for avMSE; Step 2 was a variance heterogeneity analysis for avMSE. Genotype-by-education interaction tests were performed in the Stage-II sample, with University education coded as a binary exposure. On average, participants were 58 years-old and left full-time education when they were 18 years-old; 35% reported University level education. The 2-step screening strategy in the Stage-I sample prioritized 25 genetic variants (GWAS P < 1e-04; variance heterogeneity P < 5e-05). In the Stage-II sample, 19 of the 25 (76%) genetic variants demonstrated evidence of variance heterogeneity, suggesting the majority were true positives. Five genetic variants located near GJD2, RBFOX1, LAMA2, KCNQ5 and LRRC4C had evidence of a genotype-by-education interaction in the Stage-II sample (P < 0.002) and consistent evidence of a genotype-by-education interaction in the Stage-I sample. For all 5 variants, University-level education was associated with an increased effect of the risk allele. In this cohort, additional years of education were associated with an enhanced effect of genetic variants that have roles including axon guidance and the development of neuronal synapses and neural circuits.
A genetic contribution to refractive error has been confirmed by the discovery of more than 150 associated variants in genome-wide association studies (GWAS). Environmental factors such as education ...and time outdoors also demonstrate strong associations. Currently however, the extent of gene-environment or gene-gene interactions in myopia is unknown. We tested the hypothesis that refractive error-associated variants exhibit effect size heterogeneity, a hallmark feature of genetic interactions. Of 146 variants tested, evidence of non-uniform, non-linear effects were observed for 66 (45%) at Bonferroni-corrected significance (
< 1.1 × 10
) and 128 (88%) at nominal significance (
< 0.05).
variant rs12193446, for example, had an effect size varying from -0.20 diopters (95% CI -0.18 to -0.23) to -0.89 diopters (95% CI -0.71 to -1.07) in different individuals. SNP effects were strongest at the phenotype extremes and weaker in emmetropes. A parsimonious explanation for these findings is that gene-environment or gene-gene interactions in myopia are pervasive.
Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry
. Here, in cross-ancestry ...GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis
, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach
, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry
. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.
Integrated analyses of plasma proteomics and genetic data in prospective studies can help assess the causal relevance of proteins, improve risk prediction, and discover novel protein drug targets for ...type 2 diabetes (T2D).
We measured plasma levels of 2,923 proteins using Olink Explore among ∼2,000 randomly selected participants from China Kadoorie Biobank (CKB) without prior diabetes at baseline. Cox regression assessed associations of individual protein with incident T2D (n = 92 cases). Proteomic-based risk models were developed with discrimination, calibration, reclassification assessed using area under the curve (AUC), calibration plots, and net reclassification index (NRI), respectively. Two-sample Mendelian randomization (MR) analyses using cis-protein quantitative trait loci identified in a genome-wide association study of CKB and UK Biobank for specific proteins were conducted to assess their causal relevance for T2D, along with colocalization analyses to examine shared causal variants between proteins and T2D.
Overall, 33 proteins were significantly associated (false discovery rate <0.05) with risk of incident T2D, including IGFBP1, GHR, and amylase. The addition of these 33 proteins to a conventional risk prediction model improved AUC from 0.77 (0.73-0.82) to 0.88 (0.85-0.91) and NRI by 38%, with predicted risks well calibrated with observed risks. MR analyses provided support for the causal relevance for T2D of ENTR1, LPL, and PON3, with replication of ENTR1 and LPL in Europeans using different genetic instruments. Moreover, colocalization analyses showed strong evidence (pH4 > 0.6) of shared genetic variants of LPL and PON3 with T2D.
Proteomic analyses in Chinese adults identified novel associations of multiple proteins with T2D with strong genetic evidence supporting their causal relevance and potential as novel drug targets for prevention and treatment of T2D.
Alcohol consumption accounts for ~3 million annual deaths worldwide, but uncertainty persists about its relationships with many diseases. We investigated the associations of alcohol consumption with ...207 diseases in the 12-year China Kadoorie Biobank of >512,000 adults (41% men), including 168,050 genotyped for ALDH2- rs671 and ADH1B- rs1229984 , with >1.1 million ICD-10 coded hospitalized events. At baseline, 33% of men drank alcohol regularly. Among men, alcohol intake was positively associated with 61 diseases, including 33 not defined by the World Health Organization as alcohol-related, such as cataract (n = 2,028; hazard ratio 1.21; 95% confidence interval 1.09-1.33, per 280 g per week) and gout (n = 402; 1.57, 1.33-1.86). Genotype-predicted mean alcohol intake was positively associated with established (n = 28,564; 1.14, 1.09-1.20) and new alcohol-associated (n = 16,138; 1.06, 1.01-1.12) diseases, and with specific diseases such as liver cirrhosis (n = 499; 2.30, 1.58-3.35), stroke (n = 12,176; 1.38, 1.27-1.49) and gout (n = 338; 2.33, 1.49-3.62), but not ischemic heart disease (n = 8,408; 1.04, 0.94-1.14). Among women, 2% drank alcohol resulting in low power to assess associations of self-reported alcohol intake with disease risks, but genetic findings in women suggested the excess male risks were not due to pleiotropic genotypic effects. Among Chinese men, alcohol consumption increased multiple disease risks, highlighting the need to strengthen preventive measures to reduce alcohol intake.
Motivated by the release of the UK Biobank data and the lack of documented gene-environment (GxE) and gene-gene (GxG) interactions in myopia, I sought to apply various statistical tools to provide a ...quantitative assessment of the interplay between environmental and genetic risk factors shaping refractive error. The comparison between the two different risk measurement scales with which GxE interactions can be identified suggested that the additive risk scale can lead to a more informative perspective about refractive error aetiology. The evaluation of two indirect methods for detecting genetic variants affecting refractive error via interaction effects suggested the enrichment of GxG and GxE among the variants that display marginal SNP effects. For genetic variants already known from prior GWAS studies to influence refractive error, genetic effect sizes were highly non-uniform; individuals from the tails of the refractive error distribution (i.e. high myopes and hyperopes) displayed much larger effects compared to individuals in the middle of the distribution (i.e. emmetropes). Prediction of refractive error using GxE interactions indicated that although some of the variance of refractive error could be explained by a risk score constructed using interaction effects, the contribution of GxE was already accounted for by a risk score constructed using marginal SNP effects only. Although a handful of candidate genes were identified using multifactor dimensionality reduction technique, none displayed compelling evidence of involvement in a GxG interaction. There was, however, suggestive evidence that the candidate genes constitute a genetic interaction network which is regulated by hub gene ZMAT4. In summary, the analyses reported in this thesis provide further support for the challenging nature of definitively identifying loci involved in GxE and GxG interactions. The thesis provides several guidelines that future studies could take into account to obtain more insightful results regarding the extent of interactions in refractive error.
Adiposity is associated with multiple diseases and traits, but little is known about the causal relevance and mechanisms underlying these associations. Large-scale proteomic profiling, especially ...when integrated with genetic data, can clarify mechanisms linking adiposity with disease outcomes. We examined the associations of adiposity with plasma levels of 1463 proteins in 3977 Chinese adults, using measured and genetically-instrumented BMI. We further used two-sample bi-directional MR analyses to assess if certain proteins influenced adiposity, along with other (e.g. enrichment) analyses to clarify possible mechanisms underlying the observed associations. Overall, the mean (SD) baseline BMI was 23.9 (3.3) kg/m
2
, with only 6% being obese (i.e. BMI ≥ 30 kg/m
2
). Measured and genetically-instrumented BMI was significantly associated at FDR < 0.05 with levels of 1096 (positive/inverse: 826/270) and 307 (positive/inverse: 270/37) proteins, respectively, with FABP4, LEP, IL1RN, LSP1, GOLM2, TNFRSF6B, and ADAMTS15 showing the strongest positive and PON3, NCAN, LEPR, IGFBP2 and MOG showing the strongest inverse genetic associations. These associations were largely linear, in adiposity-to-protein direction, and replicated (> 90%) in Europeans of UKB (mean BMI 27.4 kg/m
2
). Enrichment analyses of the top > 50 BMI-associated proteins demonstrated their involvement in atherosclerosis, lipid metabolism, tumour progression and inflammation. Two-sample bi-directional MR analyses using
cis
-pQTLs identified in CKB GWAS found eight proteins (ITIH3, LRP11, SCAMP3, NUDT5, OGN, EFEMP1, TXNDC15, PRDX6) significantly affect levels of BMI, with NUDT5 also showing bi-directional association. The findings among relatively lean Chinese adults identified novel pathways by which adiposity may increase disease risks and novel potential targets for treatment of obesity and obesity-related diseases.
Evidence is sparse and inconclusive on the association between long-term fine (≤2.5 μm) particulate matter (PM2.5) exposure and esophageal cancer. We aimed to assess the association of PM2.5 with ...esophageal cancer risk and compared the esophageal cancer risk attributable to PM2.5 exposure and other established risk factors.
This study included 510,125 participants without esophageal cancer at baseline from China Kadoorie Biobank. A high-resolution (1 × 1 km) satellite-based model was used to estimate PM2.5 exposure during the study period. Hazard ratios (HR) and 95% CIs of PM2.5 with esophageal cancer incidence were estimated using Cox proportional hazard model. Population attributable fractions for PM2.5 and other established risk factors were estimated.
There was a linear concentration–response relationship between long-term PM2.5 exposure and esophageal cancer. For each 10-μg/m3 increase in PM2.5, the HR was 1.16 (95% CI, 1.04–1.30) for esophageal cancer incidence. Compared with the first quarter of PM2.5 exposure, participants in the highest quarter had a 1.32-fold higher risk for esophageal cancer, with an HR of 1.32 (95% CI, 1.01–1.72). The population attributable risk because of annual average PM2.5 concentration ≥35 μg/m3 was 23.3% (95% CI, 6.6%–40.0%), higher than the risks attributable to lifestyle risk factors.
This large prospective cohort study of Chinese adults found that long-term exposure to PM2.5 was associated with an elevated risk of esophageal cancer. With stringent air pollution mitigation measures in China, a large reduction in the esophageal cancer disease burden can be expected.
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Long-term exposure to high levels of fine (≤2.5 μm) particulate matter is associated with an increased risk of esophageal cancer.
Over 3.5 billion individuals worldwide are exposed to household air pollution from solid fuel use. There is limited evidence from cohort studies on associations of solid fuel use with risks of major ...eye diseases, which cause substantial disease and economic burden globally.
The China Kadoorie Biobank recruited 512,715 adults aged 30 to 79 years from 10 areas across China during 2004 to 2008. Cooking frequency and primary fuel types in the 3 most recent residences were assessed by a questionnaire. During median (IQR) 10.1 (9.2 to 11.1) years of follow-up, electronic linkages to national health insurance databases identified 4,877 incident conjunctiva disorders, 13,408 cataracts, 1,583 disorders of sclera, cornea, iris, and ciliary body (DSCIC), and 1,534 cases of glaucoma. Logistic regression yielded odds ratios (ORs) for each disease associated with long-term use of solid fuels (i.e., coal or wood) compared to clean fuels (i.e., gas or electricity) for cooking, with adjustment for age at baseline, birth cohort, sex, study area, education, occupation, alcohol intake, smoking, environmental tobacco smoke, cookstove ventilation, heating fuel exposure, body mass index, prevalent diabetes, self-reported general health, and length of recall period. After excluding participants with missing or unreliable exposure data, 486,532 participants (mean baseline age 52.0 SD 10.7 years; 59.1% women) were analysed. Overall, 71% of participants cooked regularly throughout the recall period, of whom 48% used solid fuels consistently. Compared with clean fuel users, solid fuel users had adjusted ORs of 1.32 (1.07 to 1.37, p < 0.001) for conjunctiva disorders, 1.17 (1.08 to 1.26, p < 0.001) for cataracts, 1.35 (1.10 to 1.66, p = 0.0046) for DSCIC, and 0.95 (0.76 to 1.18, p = 0.62) for glaucoma. Switching from solid to clean fuels was associated with smaller elevated risks (over long-term clean fuel users) than nonswitching, with adjusted ORs of 1.21 (1.07 to 1.37, p < 0.001), 1.05 (0.98 to 1.12, p = 0.17), and 1.21 (0.97 to 1.50, p = 0.088) for conjunctiva disorders, cataracts, and DSCIC, respectively. The adjusted ORs for the eye diseases were broadly similar in solid fuel users regardless of ventilation status. The main limitations of this study include the lack of baseline eye disease assessment, the use of self-reported cooking frequency and fuel types for exposure assessment, the risk of bias from delayed diagnosis (particularly for cataracts), and potential residual confounding from unmeasured factors (e.g., sunlight exposure).
Among Chinese adults, long-term solid fuel use for cooking was associated with higher risks of not only conjunctiva disorders but also cataracts and other more severe eye diseases. Switching to clean fuels appeared to mitigate the risks, underscoring the global health importance of promoting universal access to clean fuels.
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