Phenome-wide association study to explore relationships between immune system related genetic loci and complex traits and diseases

CITATION: Verma, A., et al. 2016. Phenome-wide association study to explore relationships between immune system related genetic loci and complex traits and diseases. PLoS ONE, 11(8):e0160573, doi:10.1371/journal. pone.0160573.The original publication is available at http://journals.plos.org/plosoneThis study highlights the utility of using PheWAS in conjunction with EHRs to discover new genotypic-phenotypic associations for immune-system related genetic loci.http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0160573Publisher's versio

Phenome wide association study of vitamin D genetic variants in the UK Biobank cohort

Introduction Vitamin D status is an important public health issue due to the high prevalence of vitamin D insufficiency and deficiency, especially in high latitude areas. Furthermore, it has been reported to be associated with a number of diseases. In a previous umbrella review of meta-analyses of randomized clinical trials (RCTs) and of observational studies, it was found that plasma/ serum 25-hydroxyvitamin D (25(OH)D) or supplemental vitamin D has been linked to more than 130 unique health outcomes. However, the majority of the studies yielded conflicting results and no association was convincing. Aim and Objectives The aim of my PhD was to comprehensively explore the association between vitamin D and multiple outcomes. The specific objectives were to: 1) update the umbrella review of meta-analysis of observational studies or randomized controlled trials on associations between vitamin D and health outcomes published between 2014 and 2018; 2) conduct a systematic literature review of previous Mendelian Randomization studies on causal associations between vitamin D and all outcomes; 3) conduct a systematic literature review of published phenome wide association studies, summarizing the methods, results and predictors; 4) create a polygenic risk score of vitamin D related genetic variants, weighted by their effect estimates from the most recent genome wide association study; 5) encode phenotype groups based on electronic medical records of participants; 6) study the associations between vitamin D related SNPs and the whole spectrum of health outcomes, defined by electronic medical records utilising the UK Biobank study; 7) explore the causal effect of 25- hydroxyvitamin D level on health outcomes by applying novel instrumental variable methods. Methods First I updated the vitamin D umbrella review published in 2015, by summarizing the evidence from meta-analyses of observational studies and meta-analyses of RCTs published between 2014 and 2018. I also performed a systematic literature review of all previous Mendelian Randomizations studies on the effect of vitamin D on all health outcomes, as well as a systematic review of all published PheWAS studies and the methodology they applied. Then I conducted original data analysis in a large prospective population-based cohort, the UK Biobank, which includes more than 500,000 participants. A 25(OH)D genetic risk score (weighted sum score of 6 serum 25(OH)D-related SNPs: rs3755967, rs12785878, rs10741657, rs17216707, rs10745742 and rs8018720, as identified by the largest genome wide association study of 25(OH)D levels) was constructed to be used as the instrumental variable. I used a phenotyping algorithm to code the electronic medical records (EMR) of UK Biobank participants into 1853 distinct disease categories and I then ran the PheWAS analysis to test the associations between the 25(OH)D genetic risk score and 950 disease outcome groups (i.e. outcomes with more than 200 cases). For phenotypes found to show a statistically significant association with 25(OH)D levels in the PheWAS or phenotypes which were found to be convincing or highly suggestive in previous studies, I developed an extended case definition by incorporating self-reported data collected by UK Biobank baseline questionnaire and interview. The possible causal effect of vitamin D on those outcomes was then explored by the MR two-stage method, inverse variance weighted MR and Egger’s regression, followed by sensitivity analyses. Results In the updated systematic literature review of meta-analyses of observational studies or RCTs, only studies on new outcomes which had not been covered by the previous umbrella review were included. A total of 95 meta-analyses met the inclusion criteria. Among the included studies there were 66 meta-analyses of observational studies, and 29 meta-analyses of RCTs. Eighty-five new outcomes were explored by meta-analyses of observational studies, and 59 new outcomes were covered by meta-analyses of RCTs. In the systematic review of published Mendelian Randomization studies on vitamin D, a total of 29 studies were included. A causal role of 25(OH)D level was supported by MR analysis for the following outcomes: type 2 diabetes, total adiponectin, diastolic blood pressure, risk of hypertension, multiple sclerosis, Alzheimer’s disease, all-cause mortality, cancer mortality, mortality excluding cancer and cardiovascular events, ovarian cancer, HDL-cholesterol, triglycerides and cognitive functions. For the systematic literature review of published PheWAS studies and their methodology, a total of 45 studies were included. The processes for implementing a PheWAS study include the following steps: sample selection, predictor selection, phenotyping, statistical analysis and result interpretation. One of the main challenges is the definitions of the phenotypes (i.e., the method of binning participants into different phenotype groups). In the phenotyping step, an ICD curated phenotyping was widely used by previous PheWAS, which I also used in my own analysis. By applying the ICD curated phenotyping, 1853 phenotype groups were defined in the participants I used. In PheWAS, only phenotype groups with more than 200 cases were analysed (920 phenotypes). In the PheWAS, only associations between rs17216707 (CYP24A1) and “calculus of ureter” (beta = -0.219, se = 0.045, P = 1.14*10-6), “urinary calculus” (beta = -0.129, se = 0.027, P = 1.31*10-6), “alveolar and parietoalveolar pneumonopathy” (beta = 0.418, se = 0.101, P = 3.53*10-5) survived Bonferroni correction. Nine outcomes, including systolic blood pressure, diastolic blood pressure, body mass index, risk of hypertension, type 2 diabetes, ischemic heart disease, depression, non-vertebral fracture and all-cause mortality were explored in MR analyses. The MR analysis had more than 80% power for detecting a true odds ratio of 1.2 or larger for binary outcomes. None of explored outcomes were statistically significant. Results from multiple MR methods and sensitivity analyses were consistent. Discussion Vitamin D and its association with multiple outcomes has been widely studied. More than 230 outcomes have been linked with vitamin D by meta-analyses of observational studies and RCTs. On the contrary, evidence from Mendelian Randomization studies is lacking. In particular I identified only 20 existing MR studies and only 13 outcomes were suggested to be causally related to vitamin D. In the systematic literature review of previous PheWAS studies, I summarized the applied methods, predictors and results. Although phenotyping based on ICD codes provided good performance and was widely applied by previous PheWAS studies, phenotyping can be improved if lab data, imaging data and medical notes can be incorporated. Alternative algorithms, which takes advantage of deep learning and thus enable high precision phenotyping, needs to be developed. From the PheWAS analysis, the score of vitamin D related genetic variants was not statistically significantly associated with any of the 920 phenotypes tested. In the single variant analysis, only rs17216707 (CYP24A1) was shown to be associated with calculus outcomes statistically significantly. Previous studies reported associations between vitamin D and hypercalcemia, hypercalciuria, nephrolithiasis and nephrocalcinosis, may be due to the role of vitamin D in calcium homeostasis. In the MR analysis, I found no evidence of large to moderate (OR>1.2) causal associations of vitamin D on a very wide range of health outcomes. These included SBP, DBP, hypertension, T2D, IHD, BMI, depression, non-vertebral fracture and allcause mortality which have previously been proposed to be influenced by low vitamin D levels. Further, even larger studies, probably involving the joint analysis of data from several large biobanks with future IVs that explain a higher proportion of the trait variance, will be required to exclude smaller causal effects which could have public health importance because of the high population prevalence of low vitamin D levels in some populations

Computational and Statistical Approaches for Large-Scale Genome-Wide Association Studies

Over the past decade, genome-wide association studies (GWAS) have proven successful at shedding light on the underlying genetic variations that affect the risk of human complex diseases, which can be translated to novel preventative and therapeutic strategies. My research aims at identifying novel disease-associated genetic variants through large-scale GWAS and developing computational and statistical pipelines and methods to improve power and accuracy of GWAS. Bicuspid aortic valve (BAV) is a congenital heart defect characterized by fusion of two of the normal three leaflets of the aortic valve. As the most common cardiovascular malformation in humans, BAV is moderately heritable and is an important risk factor for valvulopathy and aortopathy, but its genetic origins remain elusive. In Chapter 2, we present the first large-scale GWAS study to identify novel genetic variants associated with BAV. We report association with a non-coding variant 151kb from the gene encoding the cardiac-specific transcription factor, GATA4, and near-significance for p.Ser377Gly in GATA4. We used multiple bioinformatics approaches to demonstrate that the GATA4 gene is a plausible biological candidate. In the subsequent functional follow-up, GATA4 was interrupted by CRISPR-Cas9 in induced pluripotent stem cells from healthy donors. The disruption of GATA4 significantly impaired the transition from endothelial cells into mesenchymal cells, a critical step in heart valve development. Genotype imputation is widely used in GWAS to perform in silico genotyping, leading to higher power to identify novel genetic signals. When multiple reference panels are not consented to combine together, it is unclear how to combine the imputation results to optimize the power of genetic association tests. In Chapter 3, we compared the accuracy of 9,265 Norwegian genomes imputed from three reference panels – 1000 Genomes Phase 3 (1000G), Haplotype Reference Consortium (HRC), and a reference panel containing 2,201 Norwegian participants from the HUNT study with low-pass genome sequencing. We observed that the overall imputation accuracy from the population-specific panel was substantially higher than 1000G and was comparable with HRC, despite HRC being 15-fold larger. We also evaluated different strategies to utilize multiple sets of imputed genotypes to increase the power of association studies. We propose that testing association for all variants imputed from any panel results in higher power to detect association than the alternative strategy of testing only the version of each genetic variant with the highest imputation quality metric. In phenome-wide GWAS by large biobanks, most binary traits have substantially fewer cases than controls. Both of the widely used approaches, linear mixed model and the recently proposed logistic mixed model, perform poorly -- producing large type I error rates -- in the analysis of phenotypes with unbalanced case-control ratios. In Chapter 4, we propose a scalable and accurate generalized mixed model association test that uses the saddlepoint approximation (SPA) to calibrate the distribution of score test statistics. This method, SAIGE, provides accurate p-values even when case-control ratios are extremely unbalanced. It utilizes state-of-art optimization strategies to reduce computational time and memory cost of generalized mixed model. The computation cost linearly depends on sample size, and hence can be applicable to GWAS for thousands of phenotypes by large biobanks. Through the analysis of UK Biobank data of 408,961 white British European-ancestry samples for 1,403 dichotomous phenotypes, we show that SAIGE can efficiently analyze large sample data, controlling for unbalanced case-control ratios and sample relatedness.PHDBioinformaticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144097/1/zhowei_1.pd

Phenome-wide association study (PheWAS) on the genetic determinants of serum urate level and disease outcomes in UK Biobank

IntroductionElevated serum uric acid (SUA) concentration, known as hyperuricaemia, is a common abnormity in individuals with metabolic disorders. There is increasing evidence supporting the link between high SUA level and the increased risk of a wide range of clinical disorders, including hypertension, cardiovascular diseases (CVD), chronic renal diseases and metabolic syndrome. Although there are considerable research efforts in understanding the pathogenic pathways of high SUA level and the related clinical consequences, their causal relationships have not been established except for gout. Like other complex traits, genetic determinants play a substantial role (an estimated heritability of 40-70%) in the regulation of SUA level. Investigating the role of genetic variants related to SUA in various diseases might provide evidence for the above hypothesis which links uric acid to clinical disorders. Method Umbrella review was carried out first to provide a comprehensive overview on the range of health outcomes in relation to SUA level by incorporating evidence from systematic reviews and meta-analyses of observational studies, meta-analyses of randomised controlled trials (RCTs), and Mendelian randomisation (MR) studies. The umbrella review summarised the range of related health outcomes, the magnitude, direction and significance of identified associations and effects, and classified the evidence into four categories (class I [convincing], II [highly suggestive], III [suggestive], and IV [weak]) with assessment of multiple sources of biases. Then, a MR-PheWAS (Phenome-wide association study incorporated with Mendelian randomisation [MR]) was performed to investigate the associations between the 31 SUA genetic risk variants and a very wide range of disease outcomes by using the interim release data of UK Biobank (n=120,091). The SUA genetic risk loci were employed as instruments individually. The framework of phenome was defined by the PheCODE schema using the International Classification of Diseases (ICD) diagnosis codes documented in the health records of UK Biobank. Phenome-wide association test was performed first to identify any association across the SUA genetic risk loci and the phenome; MR design and HEIDI (heterogeneity in dependent instruments) tests were then applied to distinguish the PheWAS associations that were due to causality, pleiotropy or genetic linkage.To validate the MR-PheWAS findings, an enlarged Phenome-wide Mendelian randomisation (PWMR) analysis were performed by using data from the full UK Biobank cohort (n=339,256). A weighted polygenic risk score (GRS), incorporating effect estimates of multiple genetic risk loci, was employed as a proxy of the SUA level. The framework of phenome was defined by both the PheCODE schema and an alternative Tree-structured phenotypic model (TreeWAS) for analysis. Significant associations from these analyses were taken forward for replication in different populations by analysing data from various GWAS consortia documented in the MR-base database. Sensitivity analyses examining the pleiotropic effects of urate genetic risk loci on a set of metabolic traits were performed to explore any causal effects and pleiotropic associations.ResultsThe umbrella review included 101 articles and comprised 144 meta-analyses of observational studies, 31 meta-analyses of randomised controlled trials and 107 Mendelian randomisation studies. This remarkable assembly of evidence explored 136 unique health outcomes and reported convincing (class I) evidence for the causal role of SUA in gout and nephrolithiasis. Furthermore, highly suggestive (class II) evidence was reported for five health outcomes, in which high SUA level was associated with increased risk of heart failure, hypertension, impaired fasting glucose or diabetes, chronic kidney disease, and coronary heart disease mortality in the general population. The remaining 129 associations were classified as either suggestive or weak. The MR-PheWAS (using the interim release cohort) identified 25 disease groups/ outcomes to be associated with SUA genetic risk loci after multiple testing correction (p<8.6 ×10-5). The MR IVW (inverse variance weighted) analysis implicated a causal role of SUA level in three disease groups: inflammatory polyarthropathies (OR=1.22, 95% CI: 1.11 to 1.34), hypertensive disease (OR=1.08, 95% CI: 1.03 to 1.14) and disorders of metabolism (OR=1.07, 95% CI: 1.01 to 1.14); and four disease outcomes: gout (OR=4.88, 95% CI: 3.91 to 6.09), essential hypertension (OR=1.08, 95% CI: 1.03 to 1.14), myocardial infarction (OR=1.16, 95% CI: 1.03 to 1.30) and coeliac disease (OR=1.41, 95% CI: 1.05 to 1.89). After balancing pleiotropic effects in MR Egger analysis, only gout and its encompassing disease group of inflammatory polyarthropathies were considered to be causally associated with SUA level. The analysis also highlighted a locus (ATXN2/S2HB3) that may influence SUA level and multiple cardiovascular and autoimmune diseases via pleiotropy.The PWMR analysis, using data from the full UK Biobank cohort (n=339,256), examining the association with 1,431 disease outcomes, identified 13 phecodes that were associated with the weighted GRS of SUA level with the p value passing the significance threshold of PheWAS (p<3.4×10-4). These phecodes represent 4 disease groups: inflammatory polyarthropathies (OR=1.28; 95% CI: 1.21 to 1.35; p=4.97×10-19), hypertensive disease (OR=1.08; 95% CI: 1.05 to 1.11; p=6.02×10-7), circulatory disease (OR=1.05; 95% CI: 1.02 to 1.07; p=3.29×10-4) and metabolic disorders (OR=1.07; 95% CI: 1.03 to 1.11; p= 3.33×10-4), and 9 disease outcomes: gout (OR=5.37; 95% CI: 4.67 to 6.18; p= 4.27×10-123), gouty arthropathy (OR=5.11; 95% CI: 2.45 to 10.66; p=1.39×10-5), pyogenic arthritis (OR=2.10; 95% CI: 1.41 to 3.14; p=2.87×10-4), essential hypertension (OR=1.08; 95% CI: 1.05 to 1.11; p=6.62×10-7), coronary atherosclerosis (OR=1.10; 95% CI: 1.05 to 1.15; p=1.17×10-5), ischaemic heart disease (OR=1.10, 95% CI: 1.05 to 1.15; p=1.73×10-5), chronic ischaemic heart disease (OR=1.10, 95% CI: 1.05 to 1.15; p=1.52×10-5), myocardial infarction (OR=1.15, 95% CI=1.07 to 1.23, p=5.23×10-5), and hypercholesterolaemia (OR=1.08, 95% CI: 1.04 to 1.13, p=3.34×10-4). Findings from the TreeWAS analysis were generally consistent with that of PheWAS, with a number of more sub-phenotypes being identified. Results from IVW MR suggested that genetically determined high serum urate level was associated with increased risk of gout (OR=4.53, 95%CI: 3.64-5.64, p=9.66×10-42), CHD (OR=1.10, 95%CI: 1.02 to 1.19, p=0.009), myocardial infarction (OR=1.11, 95%CI:1.02 to 1.20, p=0.011) and decreased level of HDL-c (OR=0.93, 95%CI:0.88 to 0.98, p=0.004), but had no effect on RA (OR=0.92, 95%CI: 0.84 to 1.01, p=0.085) and ischaemic stroke (OR=1.03, 95%CI: 0.93 to 1.14, P= 0.582). Egger MR indicated pleiotropic effects on the causal estimates of DBP (P_pleiotropy=0.014), SBP (P_pleiotropy=0.003), CHD (P_pleiotropy=0.008), myocardial infarction (P_pleiotropy=0.008) and HDL-c (P_pleiotropy=0.016). When balancing out the potential pleiotropic effects in Egger MR, a causal effect can only be verified for gout (OR=4.17, 95%CI: 3.03 to 5.74, P_effect=1.27×〖10〗^(-9); P_pleiotropy=0.485). Sensitivity analyses on the GRSs of different groups of pleiotropic loci support an inference that pleiotropic effects of genetic variants on urate and metabolic traits contribute to the observed associations with cardiovascular/metabolic diseases. ConclusionsThis thesis presents a comprehensive investigation on the health outcomes in relation to SUA level. The causal relationship between high SUA level and gout is robustly verified in this thesis with consistent evidence from the umbrella review, the MR-PheWAS and the PWMR. The association of high SUA level with hypertension and heart diseases is supported by both the evidence from umbrella review and analyses conducted in this thesis, however, given the caveat of pleiotropy in the causal inference, a conclusion of causality on hypertension and heart diseases is not robust enough based on the current findings. Furthermore, the epidemiological evidence from the umbrella review indicated that high SUA level was associated with several components of metabolic disorders, and the analyses of the UK Biobank data identified a significant association with metabolic disorders and a sub-phenotype (hypercholesterolaemia). The causal inference in this study is limited by the common difficulty of pleiotropy caused by the use of multiple genetic instruments. Although we have performed sensitivity analysis by excluding the key pleiotropic locus, unmeasured pleiotropy and biases are still possible. In particular, unbalanced pleiotropy is recognised as an issue for the causal connections on the association between SUA level and hypertension. Other potential causal relevance of SUA level with respiratory diseases and ocular diseases is also worthy of further investigation. Overall, when taken together the findings from umbrella review, MR-PheWAS, PheWAS/TreeWAS analysis, MR replication and sensitivity analysis conducted in this thesis, I conclude that there are robust associations between urate and several disease groups, including gout, hypertensive diseases, heart diseases and metabolic disorders, but the causal role of urate only exists in gout. This study indicates that the observed associations between urate and cardiovascular/metabolic diseases are probably derived from the pleiotropic effects of genetic variants on urate and metabolic traits. Further investigation of therapies targeting the shared biological pathways between urate and metabolic traits may be beneficial for the treatment of gout and the primary prevention of cardiovascular/metabolic diseases

Genetic mapping of metabolic biomarkers of cardiometabolic diseases

Cardiometabolic disorders (CMDs) are a major public health problem worldwide. The main goal of this thesis is to characterize the genetic architecture of CMD-related metabolites in a Lebanese cohort. In order to maximise the extraction of meaningful biological information from this dataset, an important part of this thesis focuses on the evaluation and subsequent improvement of the standard methods currently used for molecular epidemiology studies. First, I describe MetaboSignal, a novel network-based approach to explore the genetic regulation of the metabolome. Second, I comprehensively compare the recovery of metabolic information in the different 1H NMR strategies routinely used for metabolic profiling of plasma (standard 1D, spin-echo and JRES). Third, I describe a new method for dimensionality reduction of 1H NMR datasets prior to statistical modelling. Finally, I use all this methodological knowledge to search for molecular biomarkers of CMDs in a Lebanese population. Metabolome-wide association analyses identified a number of metabolites associated with CMDs, as well as several associations involving N-glycan units from acute-phase glycoproteins. Genetic mapping of these metabolites validated previously reported gene-metabolite associations, and revealed two novel loci associated with CMD-related metabolites. Collectively, this work contributes to the ongoing efforts to characterize the molecular mechanisms underlying complex human diseases.Open Acces

A longitudinal study of the experiences and psychological well-being of Indian surrogates

Study question: What is the psychological well-being of Indian surrogates during and after the surrogacy pregnancy? Summary answer: Surrogates were similar to a matched group of expectant mothers on anxiety and stress. However, they scored higher on depression during and after pregnancy. What is known already: The recent ban on trans-national commercial surrogacy in India has led to urgent policy discussions regarding surrogacy. Whilst previous studies have reported the motivations and experiences of Indian surrogates no studies have systematically examined the psychological well-being of Indian surrogates, especially from a longitudinal perspective. Previous research has shown that Indian surrogates are motivated by financial payment and may face criticism from their family and community due to negative social stigma attached to surrogacy. Indian surrogates often recruited by agencies and mainly live together in a “surrogacy house.” Study design, size, duration: A longitudinal study was conducted comparing surrogates to a matched group of expectant mothers over two time points: (a) during pregnancy (Phase1: 50 surrogates, 70 expectant mothers) and (b) 4–6 months after delivery (Phase 2: 45 surrogates, 49 expectant mothers). The Surrogates were recruited from a fertility clinic in Mumbai and the matched comparison group was recruited from four public hospitals in Mumbai and Delhi. Data collection was completed over 2 years. Participants/materials, setting, methods: Surrogates and expectant mothers were aged between 23 and 36 years. All participants were from a low socio-economic background and had left school before 12–13 years of age. In-depth faceto-face semi-structured interviews and a psychological questionnaire assessing anxiety, stress and depression were administered in Hindi to both groups. Interviews took place in a private setting. Audio recordings of surrogate interviews were later translated and transcribed into English. Main results and the role of chance: Stress and anxiety levels did not significantly differ between the two groups for both phases of the study. For depression, surrogates were found to be significantly more depressed than expectant mothers at phase 1 (p = 0.012) and phase 2 (p = 0.017). Within the surrogacy group, stress and depression did not change during and after pregnancy. However, a non-significant trend was found showing that anxiety decreased after delivery (p = 0.086). No participants reported being coerced into surrogacy, however nearly all kept it a secret from their wider family and community and hence did not face criticism. Surrogates lived at the surrogate house for different durations. During pregnancy, 66% (N = 33/50) reported their experiences of the surrogate house as positive, 24% (N = 12/50) as negative and 10% (N = 5/50) as neutral. After delivery, most surrogates (66%, N = 30/45) reported their experiences of surrogacy to be positive, with the remainder viewing it as neutral (28%) or negative (4%). In addition, most (66%, N = 30/45) reported that they had felt “socially supported and loved” during the surrogacy arrangement by friends in the surrogate hostel, clinic staff or family. Most surrogates did not meet the intending parents (49%, N = 22/45) or the resultant child (75%, N = 34/45). Limitations, reasons for caution: Since the surrogates were recruited from only one clinic, the findings may not be representative of all Indian surrogates. Some were lost to follow-up which may have produced sampling bias. Wider implications of the findings: This is the first study to examine the psychological well-being of surrogates in India. This research is of relevance to current policy discussions in India regarding legislation on surrogacy. Moreover, the findings are of relevance to clinicians, counselors and other professionals involved in surrogacy. Trial registration number: N/A

Exploring brain structure and blood metabolic profiles using Alzheimer's pathway specific polygenic risk scores

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects older people. It is common, affecting around one in ten people over 65 years old. In addition to the autosomal dominant AD genes and Apolipoprotein E (APOE), genome wide association studies (GWAS) have identified a number of small risk loci. These can be combined into polygenic risk scores (PRS) which can predict AD relatively accurately and are associated with a number of neurodegeneration phenotypes. Pathway analyses of GWAS data have implicated a number of biological processes, including the immune response and lipid metabolism. How AD pathway specific genetic burden manifests in brain structure or serum metabolic profiles is not well understood. In this thesis, volumetric and diffusion MRI and serum lipid and inflammatory markers were used to investigate manifestations of AD polygenic risk in two large population cohorts. Specifically, these analyses sought to determine 1) whether AD polygenic risk scores were associated with neuroimaging and blood marker phenotypes linked to neurodegeneration in younger and older adult cohorts; and 2) whether PRS informed by disease pathways were associated with different patterns of alteration in brain structure, serum lipids or inflammatory markers. The relationships between PRS and phenotypes were explored using linear regression. There were significant associations between pathway specific PRS, grey matter volumes and white matter microstructure. Although some of these attenuated when the APOE region was excluded from the score, some were maintained, in particular cortical thickness in mature adults, which appeared to be independent of APOE. Increased pathway specific polygenic risk for AD was also associated with serum markers such as increased blood lipids, particularly low density lipoprotein (LDL) cholesterol and total cholesterol, and decreased C-Reactive Protein (CRP). However, these effects seemed to be driven by the APOE locus. Further longitudinal studies, combining advanced MRI techniques with cerebrospinal fluid and neuroradiology biomarkers, will be required to confirm these findings and assess their biological significance

Incorporating standardised drift-tube ion mobility to enhance non-targeted assessment of the wine metabolome (LC×IM-MS)

Liquid chromatography with drift-tube ion mobility spectrometry-mass spectrometry (LCxIM-MS) is emerging as a powerful addition to existing LC-MS workflows for addressing a diverse range of metabolomics-related questions [1,2]. Importantly, excellent precision under repeatability and reproducibility conditions of drift-tube IM separations [3] supports the development of non-targeted approaches for complex metabolome assessment such as wine characterisation [4]. In this work, fundamentals of this new analytical metabolomics approach are introduced and application to the analysis of 90 authentic red and white wine samples originating from Macedonia is presented. Following measurements, intersample alignment of metabolites using non-targeted extraction and three-dimensional alignment of molecular features (retention time, collision cross section, and high-resolution mass spectra) provides confidence for metabolite identity confirmation. Applying a fingerprinting metabolomics workflow allows statistical assessment of the influence of geographic region, variety, and age. This approach is a state-of-the-art tool to assess wine chemodiversity and is particularly beneficial for the discovery of wine biomarkers and establishing product authenticity based on development of fingerprint libraries