Yes / We report a genome-wide association scan in over 6,000 Latin Americans for features of scalp hair (shape, colour, greying, balding) and facial hair (beard thickness, monobrow, eyebrow thickness). We found 18 signals of association reaching genome-wide significance (P values 5 × 10−8 to 3 × 10−119), including 10 novel associations. These include novel loci for scalp hair shape and balding, and the first reported loci for hair greying, monobrow, eyebrow and beard thickness. A newly identified locus influencing hair shape includes a Q30R substitution in the Protease Serine S1 family member 53 (PRSS53). We demonstrate that this enzyme is highly expressed in the hair follicle, especially the inner root sheath, and that the Q30R substitution affects enzyme processing and secretion. The genome regions associated with hair features are enriched for signals of selection, consistent with proposals regarding the evolution of human hair.

Yes / Appeals have been made for eye care professionals to start prescribing anti-myopia therapies as part of their routine management of myopic children. 1–3 These calls are fuelled by two key considerations. Firstly, that interventions to slow myopia progression have shown success in randomized controlled trials (RCTs) 4–7, and secondly, appreciation that the risk of sight-threatening complications rises dose-dependently with the level of myopia. 8,9 Notwithstanding existing gaps in knowledge regarding the efficacy of current treatments (see below), these considerations argue that myopia control interventions should be widely adopted, and that they should be instigated at an early age – especially in children most at risk – in order to reduce the final level of myopia. Therefore in managing a child with myopia, an eye care professional would have to decide not only which therapy to recommend, but at what age to start treatment. In this review we discuss the future role of genetic prediction in helping clinicians treat myopia. / NIHR Senior Research Fellowship. Grant Number: SRF‐2015‐08‐005

Fusarium verticillioides è l’agente responsabile della Fusariosi della Spiga del mais, contamina la granella con fumonisine, micotossine responsabili di diverse patologie umane e animali. Per la resistenza alla fusariosi e all’accumulo di fumonisine esiste variabilità tra genotipi diversi ma non sono ancora disponibili ibridi immuni. L’obiettivo di questo lavoro è stato quello di individuare marcatori associati alla resistenza a F. verticillioides. Mediante un bioassay è stato testato un association panel per la resistenza a F. verticillioides. Al fine di identificare i marcatori di resistenza sono stati applicati un approccio GWAS e uno per geni candidati. L’analisi GWAS è stata eseguita con 227K SNPs restituendo 206 marcatori significativi. Da un lavoro di RNASequencing sono stati individuati i geni coinvolti nella risposta a F. verticillioides mentre i geni R sono stati recuperati della letteratura scientifica. Genotipi resistenti (CO433 e CO441) e suscettibili (CO354 e CO389) sono stati scelti per individuare polimorfismi nei geni candidati da associare ai fenotipi rilevati mediante il bioassay. Quattro marcatori sono risultati significativi. Infine, la correlazione tra l’incidenza della fusariosi rilevata in campo e mediante bioassay è stata analizzata in una popolazione di 172 RIL derivanti da CO441 x CO354, tuttavia, non è stata individuata alcuna corrispondenza. / Fusarium verticillioides is the causal agent of Fusarium ear rot (FER) in maize and contaminates grains with fumonisin, a family of mycotoxins involved in several human and animal diseases. Quantitative genetic variation exists for resistance to FER and fumonisin contamination among genotypes, however, resistant maize hybrids are currently not available. The aim of this work was the identification of genetic markers associated to resistance against F. verticillioides. A bioassay was used to screen inbred lines of the maize association population for FER resistance, GWAS and candidate gene approaches were applied to identify markers. GWAS was performed using a 227K SNP matrix and resulting in 206 significant markers. Genes involved in F. verticillioides response in developing maize kernels were retrieved from a previous RNASequencing study while maize R genes were retrieved from scientific literature. Resistant (CO433 and CO441) and susceptible genotypes (CO389 and CO354) were selected to amplify and sequence candidate genes. Polymorphisms detected were used to find association with phenotypes scored using the bioassay. Four significant markers were found. Finally, the correlation between FER phenotypes scored in field experiments and bioassay phenotypes was investigated. A population of 172 RILs (CO441 x CO354), was tested. No correlation was found.

In 2007, a genome wide association study identified a SNP in intron 1 of FTO with increased BMI. Homozygous risk allele carriers are on average three kg heavier than those homozygous for the protective allele. Mouse models have been made, including a conditional knockout, which is lean when globally expressed, as well as a conditional overexpression allele, which has increased body weight when globally expressed. The results from these and other studies suggest that the FTO SNPs lead to weight gain by increasing FTO activity and/or expression. Adult inactivation of Fto using the tamoxifen inducible Cre demonstrated that removal of Fto may be as deleterious as overexpression, with the adult knockout mice having increased fat mass and decreased lean mass. It also supported the role FTO plays in development as adult inactivation of Fto did not increase mortality rates as seen in the global Fto-/- pups. This study also revealed the importance of effective energy expenditure analysis in the mouse. I have confirmed a link between Fto-/- and increased mortality, which may be caused by alterations to developmental processes. Fto-/- reduces cilia formation in MEFs and results in dysregulated cilia formation in specific tissues in Fto-/- embryos. Levels of FTO also appear to affect adipogenic differentiation, which could be due to altered WNT/β-CATENIN signalling. Pharmacological inhibition of FTO was a success in vitro and a compound screen identified FG2216, which could be used in vivo to inhibit FTO. The in vivo effects of FG2216 at 60 mg/kg/2days did not affect body weight or composition in the mouse. My research suggests that there is dysregulation of gut hormones and neuronal signalling pathways in the FTO overexpression mice, which could cause the hyperphagia and increased body weight. These studies add to our current knowledge of FTO function, and suggest a role for FTO in control of body composition, development, and satiety signalling.

<p>Cerebrovascular disease (stroke), especially ischemic stroke, is a major cause of death and neurological disability in adults. Because of its clinical heterogeneity, stroke is considered as a multi-factorial and polygenic disorder. Most current genetic studies of ischemic stroke focus on genetic susceptibility rather than factors determining stroke outcome. The genetic components of ischemic stroke outcome are difficult to study in humans due to environmental factors and medical intervention. Thus, we proposed to use a surgically induced, permanent, focal cerebral ischemic stroke mouse model to investigate genetic factors of ischemic stroke outcome measured by infarct volume. This model is the middle cerebral artery occlusion (MCAO) model. First, we screened infarct volumes across 32 inbred mouse strains. The infarct volume varies between strains, and this strongly suggests that infarct volume is genetically determined. To identify these genetic factors, we used genome-wide association study [Efficient Mixed-Model Association (EMMA) analysis] on infarct volume from 32 inbred mouse strains. Using the EMMA analysis, we identified 11 infarct volume-associated loci; however, most loci were mapped with missing alleles. This suggests that these loci might be false positives. Thus, we used specifically designed scripts of EMMA analysis with updated mouse SNP database to correct for potential false positives. The loci identified by the updated EMMA analyses will led us to the identification of genes involved in ischemic stroke outcome. </p><p> There are two major mechanisms were proposed to be determinants of infarct volume, the extent of native collateral circulation and neuroprotection. Using the infarct volume screening panel from 32 inbred strains, we observed that infarct volume is inversely correlated with the native collateral vessel number. However, among these inbred strains, we also observed several strains differ significantly in infarct volumes but harbor similar collateral numbers. In order to identify genetic factors determining infarct volume in a collateral-independent manner (neuroprotection), we used quantitative trait locus (QTL) mapping on mouse strains that exhibit the most difference in infarct volumes but the least difference in collateral numbers (C57BL/6J and C3H/HeJ). From the F2 B6 x C3H cross, we mapped 4 loci determining infarct volume (cerebral infarct volume QTL 4 to 7, Civq4 to Civq7). The Civq4 locus is the strongest locus (LOD 9.8) that contributes 21% of phenotypic variance in infarct volume. We also used a parallel F2 B6 x C3H cross to perform a QTL mapping on collateral vessel traits to further verify these collateral-independent loci. Among these 4 loci, the Civq4 and Civq7 loci appear to be truly collateral-independent. Based on strain-specific sequence variants and mRNA expression differences, we proposed Msr1 and Mtmr7 are the potential candidate genes of the Civq4 locus. Identification of the collateral-independent genetic factors will help to understand the genetic architecture, disease pathophysiology and potential therapeutic targets for of ischemic stroke</p> / Dissertation

The case-control design is one of the most commonly used designs in genome- wide asociation studies. When we increase the sample size of either the controls or, more importantly, the cases, the power of whatever test we use will certainly increase. However increasing the sample size, means that addi- tional individuals need to be genotyped and this implies extra financial costs. However, nowadays with the emergence of genetic studies, a large number of genetic data are available at low or no extra cost. Even though those data may not be completely relevant to the current study, they can still be used to increase the probability to identify true associations. Furthermore, additional information, non-necessarily genetic, can also be used to improve the power of a method. In this thesis we extend the case-control design in order to take ad- vantage of such types of additional data and/or information. We discuss three designs; the case-cohort-control, the kin-cohort and the super-case– case–control–super-control designs. For each of these, we present methods that are adjusted or modified versions of standard case-control methods but we also propose novel ones developed with those extended designs in mind. Ultimately, we describe how those methods can be used in order to increase the power of association tests, especially compared to similar methods of the case-control design.

The aims of this study were to analyse known and potential biomarkers of common and genetically complex human disorders and to identify genetic and environmental variation associated with plasma biomarker concentrations. Two groups of protein biomarkers were analysed. First, plasma complement factor H (CFH) was selected as a potential biomarker for age-related macular degeneration (AMD), since common variants in the CFH gene show strong association with this disorder. Secondly, two isoforms of amyloid-β (Aβ40 and Aβ42) were selected as biomarkers for Alzheimer disease (AD) since Aβ deposits are major constituents of the amyloid plaques characteristic of this disorder. Physiological and anthropometric measurements and samples of human and genomic DNA were collected from a population sample of 1,021 individuals from the Croatian island of Vis. Quantitative determination of plasma Aβ40 and Aβ42 concentrations was performed using enzyme-linked immunosorbent assays. Heritabilities and significant covariate effects were estimated for each trait in the Croatian data set. Genome-wide linkage and association analyses were conducted for the biomarker traits. A novel finding was the genome-wide significant association between a CFH and several polymorphisms close to and within the CFH gene. The strongest association was with an intronic SNP within CFH, which explained 28% of the total trait variance (P < 10-50). The association was also replicated in a Dutch sample set. A SNP haplotype was identified which accounted for a higher proportion of the phenotypic variance. Conditional haplotype analysis showed that the effect of this haplotype on plasma CFH concentration was independent of the CFH Y402H variant, and significantly stronger than a deletion of the adjacent CFHR3/CFHR1 which was already known to affect AMD susceptibility. Genetic analysis of 382 AMD cases and 201 controls was consistent with the CFH Y402H variant being the strongest AMD susceptibility locus. Variation in plasma CFH concentration was found to explain up to 1.8% of the variation in susceptibility to AMD with an odds 2.1 (95% C.I. 1.3-3.4, P = 0.003). SNPs that were strongly associated with a CFH concentration also influenced AMD susceptibility (P < 0.05) independently of the CFH Y402H polymorphism. Functional analysis of genomic regions associated with plasma CFH is needed to identify the causal variants. Associations were observed between plasma Aβ40 concentration and several novel candidate loci, spanning regions of approximately 0.2 Mb, on chromosomes 9 and X. Similarly, novel associations with plasma Aβ42 were found in several regions, each spanning 0.2-0.4 Mb, on chromosomes 2, 5, 9, 15 and 20. The proportion of the phenotypic variance in plasma Aβ42 explained by these putative associations ranged between 1.8 and 2.8%. However, none of the associated SNPs was significant after correction for multiple testing, therefore replication is required. Finally, attempts were made to identify and quantitate new protein biomarkers of disease in human plasma using mass spectrometry. Development and optimisation of techniques was initially undertaken to deplete high-abundance plasma proteins and improve signal:noise ratio. This allowed the assessment of downstream proteomic approaches including MALDI-TOF mass spectrometry (MS), capillary electrophoresis (CE) and ion exchange chromatography (IEC), each with the potential for large-scale quantitation of plasma proteins. Although the analysis of single protein analytes, using CE and IEC proved promising, the results highlighted the difficulty associated with MALDI-TOF and protein ionisation techniques in analysing complex mixtures such as plasma.

Sleep disturbances and insomnia are prevalent, with around 33% of adults indicating that they experience at least one main symptom of insomnia, and bidirectional relationships exist with common psychopathology, particularly major depressive disorder (MDD). However, genetic and environmental (e.g., traumatic event exposure) contributions to the etiology of these phenotypes are not yet well understood. A genetically informative sample of approximately 12,000 Han Chinese women aged 30-60 (50% with recurrent MDD) was used to address several gaps within the sleep literature. Sleep disturbances were assessed in all individuals using a general item addressing sleeplessness (GS). A sleep within depression sum score (SDS) was also created in MDD cases, combining information from the GS and two insomnia items within MDD. A total of 11 traumatic events were assessed and additional information on childhood sexual abuse (CSA) was also obtained. First, factor analyses were conducted to determine trauma factor structure. The best-fit solution included 3 factors: interpersonal, child interpersonal, and non-assaultive, and composite variables were constructed accordingly. A series of hierarchical regressions were run to examine differential effects of trauma type and timing on sleeplessness. All traumatic events predicted sleeplessness at similar magnitudes, although population models indicated that childhood interpersonal trauma may be particularly potent. An association between CSA and sleeplessness was also replicated. A series of genetic analyses demonstrated that the single nucleotide polymorphism-based heritability of sleep phenotypes did not differ significantly from zero. Further, association analyses did not identify any genome-wide significant loci. However, using a liberal false discovery rate threshold of 0.5, two genes of interest, KCNK9 and ALDH1A2, emerged for the SDS. Polygenic risk score (PRS) analyses demonstrated genetic overlap between the SDS in MDD cases and GS in MDD controls, with PRSs explaining 0.2-0.3% of the variance. A final combined model of both genetic and environmental risk indicated that both PRS and traumatic events were significant predictors of sleeplessness. While genetic results should be interpreted with caution given the lack of heritability, additional research into the genetic and environmental contributions to insomnia, utilizing more standardized phenotypes and properly ascertained samples, is clearly warranted.

Worldwide obesity has more than doubled since 1980 and at least 2.8 million people die each year as a result of being overweight or obese. An elevated body weight is the result of the interplay between susceptibility gene variants and an obesogenic environment, and recent evidence shows that epigenetic processes are likely involved. The growing availability of high-throughput technologies has made it possible to assess quickly the entire epigenome of large samples at a relatively low cost. As a result, vast amounts of data have been generated and researchers are now confronted to both bioinformatic and biostatistic challenges to make sense of such data in the context of obesity and its complications. In this doctoral thesis, we explored associations between the human blood methylome and obesity-associated gene variants as well as dietary fat quality and quantity. We used well described preprocessing techniques and statistical methods, along with publicly available data from consortiums and other research groups, as well as tools for pathway enrichment and chromatin state inference. We found associations between obesityassociated SNPs and methylation levels at proximal promoters and enhancers, and some of these associations were replicated in multiple tissues. We also found that contrary to dietary fat quantity, dietary fat quality associates with methylation levels in the promoter of genes involved in metabolic pathways. Then, using a gene-targeted approach, we looked at the impact of an acute environmental stress (sleep loss) on the methylation and transcription levels of circadian clock genes in skeletal muscle and adipose tissue of healthy men. We found that a single night of wakefulness can alter the epigenetic and transcriptional profile of core circadian clock genes in a tissue-specific manner. Finally, we looked at the effects of chronic maternal obesity and subsequent weight loss on the transcription of epigenetic machinery genes in the fetus and placenta of mice. We found that the transcription of epigenetic machinery genes is highly sensitive to maternal weight trajectories, and particularly those of the histone acetylation pathway. Overall, this thesis demonstrated that genetics, obesogenic environment stimuli and maternal programming impact epigenetic marks at genomic locations relevant in the pathogenesis of obesity.

Lowering LDL-cholesterol with statin therapy produces substantial reductions in cardiovascular events, and larger cholesterol reductions may produce larger benefits. Rarely, myopathy occurs with statins, especially at higher doses and in combination with certain medications. Similarly strong associations might exist between myopathy with high-dose statin regimens and genetic variants, especially those affecting blood statin levels. This study aimed to find genetic variants associated with statin-induced myopathy. A feasibility study was completed to assess whether plausible effect sizes of 5 to10-fold higher risks per genetic variants could be detected among 50-100 cases with statin-induced myopathy and to consider the best study design. A genome-wide association study was then carried out using approximately 300,000 genetic markers (and additional fine-mapping) in 85 people with definite or incipient myopathy and 90 controls, who were all taking 80mg simvastatin daily in a 12,000 participant trial of 80mg vs 20mg simvastatin daily. The cases were also compared to 2,300 additional controls who had not been exposed to intensive-dose statin therapy. Replication of the myopathy result and lipid-lowering associations were tested in a 20,000 participant trial of 40mg simvastatin daily versus placebo. The genome-wide scan yielded a single strong association (p = 4x10^-9) of myopathy with the rs4363657 single nucleotide polymorphism (SNP) located within the SLCO1B1 gene on chromosome 12. This non-coding SNP was in nearly complete linkage disequilibrium (r²=0.97) with the non-synonymous rs4149056 SNP. The population prevalence of the rs4149056 C allele was 15%, and the odds ratio for myopathy was 4.5 (95% confidence interval 2.6 to 7.7) for each copy of the C allele and 16.9 (4.7 to 61.1) for CC vs TT homozygotes. Over 60% of these myopathy cases could be attributed to the C variant. The SLCO1B1 gene encodes the organic anion transport polypeptide OATP1B1, which has been shown to regulate hepatic uptake of statins. In literature reports, rs4149056 reduced statin transport and was associated with 37% (31% to 44%) higher systemic statin acid levels per C allele. The association of rs4149056 with myopathy was replicated in the trial of 40mg simvastatin daily, which also showed that it was associated with the cholesterol-lowering effects of simvastatin. No SNPs in any other region were clearly associated with myopathy (although comparison of the myopathy cases with the 2,300 controls identified a region of chromosome 1p12 that warrants further study). This study identified common variants in SLCO1B1 that influence the risks of statin-induced myopathy substantially. Genotyping these variants may be useful for tailoring both the statin dose and safety monitoring. More generally, such studies of the genetic determinants of serious adverse reactions with other drug classes may help to improve the balance between treatment efficacy and safety.