Weak-Instrument and Pleiotropy-Robust Methods for Mendelian randomisation, with Applications to Mental Health

This PhD dissertation focused on developing and applying new methods for Mendelian Randomisation (MR), a technique that uses genetic variants as instrumental variables in order to assess causal effects of exposures on health outcomes. The major focus of the applied research is psychiatric research and mental health, with a range of analyses that address the topic of causal risk factors for depression with the use of these genetics-informed methods. The first contribution of this dissertation is the development of new methods for pleiotropy-robust MR by leveraging sex specificity of phenotypes. These methods allow for more accurate and robust estimation of causal effects by cancelling out potential pleiotropic effects of genetic instruments. The second contribution is a new method for appraising high-dimensional correlated variables in multivariable MR. This method allows for the inclusion of multiple correlated variables as exposures in MR analyses, through a transformation to groups of exposures that have attractive statistical properties and biological meaning. Finally, the dissertation provides an applied analysis of how inflammation and BMI affect a range of depression phenotypes with cutting-edge methods. This analysis replicates previous results on the harmful effects of overweight on mood and challenges the independent effect of inflammation as proxied by CRP. The introduction of the dissertation is divided into two parts. The first part provides a walkthrough of the epidemiological concepts of bias, randomisation, and causal inference with observational data. The second part is a specific introduction to MR, including its underlying assumptions and limitations, as well as detailed discussion of developments that make it more robust. Overall, this dissertation contributes new methods and applied analyses to the field of MR, with potential implications for researchers and practitioners

Sparse dimensionality reduction approaches in Mendelian randomization with highly correlated exposures.

Multivariable Mendelian randomization (MVMR) is an instrumental variable technique that generalizes the MR framework for multiple exposures. Framed as a linear regression problem, it is subject to the pitfall of multi-collinearity. The bias and efficiency of MVMR estimates thus depends heavily on the correlation of exposures. Dimensionality reduction techniques such as principal component analysis (PCA) provide transformations of all the included variables that are effectively uncorrelated. We propose the use of sparse PCA (sPCA) algorithms that create principal components of subsets of the exposures with the aim of providing more interpretable and reliable MR estimates. The approach consists of three steps. We first apply a sparse dimension reduction method and transform the variant-exposure summary statistics to principal components. We then choose a subset of the principal components based on data-driven cutoffs, and estimate their strength as instruments with an adjusted F-statistic. Finally, we perform MR with these transformed exposures. This pipeline is demonstrated in a simulation study of highly correlated exposures and an applied example using summary data from a genome-wide association study of 97 highly correlated lipid metabolites. As a positive control, we tested the causal associations of the transformed exposures on CHD. Compared to the conventional inverse-variance weighted MVMR method and a weak-instrument robust MVMR method (MR GRAPPLE), sparse component analysis achieved a superior balance of sparsity and biologically insightful grouping of the lipid traits

Effects of physical activity and sedentary time on depression, anxiety and well-being: a bidirectional Mendelian randomisation study.

Background: Mental health conditions represent one of the major groups of non-transmissible diseases. Physical activity (PA) and sedentary time (ST) have been shown to affect mental health outcomes in opposite directions. In this study, we use accelerometery-derived measures of PA and ST from the UK Biobank (UKB) and depression, anxiety and well-being data from the UKB mental health questionnaire as well as published summary statistics to explore the causal associations between these phenotypes. Methods: We used MRlap to test if objectively measured PA and ST associate with mental health outcomes using UKB data and summary statistics from published genome-wide association studies. We also tested for bidirectional associations. We performed sex stratified as well as sensitivity analyses. Results: Genetically instrumented higher PA was associated with lower odds of depression (OR = 0.92; 95% CI: 0.88, 0.97) and depression severity (beta =  − 0.11; 95% CI: − 0.18, − 0.04), Genetically instrumented higher ST was associated higher odds of anxiety (OR = 2.59; 95% CI: 1.10, 4.60). PA was associated with higher well-being (beta = 0.11, 95% CI: 0.04; 0.18) and ST with lower well-being (beta =  − 0.18; 95% CI: − 0.32, − 0.03). Similar findings were observed when stratifying by sex. There was evidence for a bidirectional relationship, with higher genetic liability to depression associated with lower PA (beta =  − 0.25, 95% CI: − 0.42; − 0.08) and higher well-being associated with higher PA (beta = 0.15; 95% CI: 0.05, 0.25). Conclusions: We have demonstrated the bidirectional effects of both PA and ST on a range of mental health outcomes using objectively measured predictors and MR methods for causal inference. Our findings support a causal role for PA and ST in the development of mental health problems and in affecting well-being.BACKGROUND: Mental health conditions represent one of the major groups of non-transmissible diseases. Physical activity (PA) and sedentary time (ST) have been shown to affect mental health outcomes in opposite directions. In this study, we use accelerometery-derived measures of PA and ST from the UK Biobank (UKB) and depression, anxiety and well-being data from the UKB mental health questionnaire as well as published summary statistics to explore the causal associations between these phenotypes. METHODS: We used MRlap to test if objectively measured PA and ST associate with mental health outcomes using UKB data and summary statistics from published genome-wide association studies. We also tested for bidirectional associations. We performed sex stratified as well as sensitivity analyses. RESULTS: Genetically instrumented higher PA was associated with lower odds of depression (OR = 0.92; 95% CI: 0.88, 0.97) and depression severity (beta =  - 0.11; 95% CI: - 0.18, - 0.04), Genetically instrumented higher ST was associated higher odds of anxiety (OR = 2.59; 95% CI: 1.10, 4.60). PA was associated with higher well-being (beta = 0.11, 95% CI: 0.04; 0.18) and ST with lower well-being (beta =  - 0.18; 95% CI: - 0.32, - 0.03). Similar findings were observed when stratifying by sex. There was evidence for a bidirectional relationship, with higher genetic liability to depression associated with lower PA (beta =  - 0.25, 95% CI: - 0.42; - 0.08) and higher well-being associated with higher PA (beta = 0.15; 95% CI: 0.05, 0.25). CONCLUSIONS: We have demonstrated the bidirectional effects of both PA and ST on a range of mental health outcomes using objectively measured predictors and MR methods for causal inference. Our findings support a causal role for PA and ST in the development of mental health problems and in affecting well-being.National Institute for Health Research (NIHR

Application of bone growth factors—the potential of different carrier systems

Aim The aim of the present review was to characterize the potential of different biomaterials as carriers for bone growth factors. Introduction Beyond mechanical and structural characteristics, one of the features that account for a potential carrier is the possibility to couple growth factor molecules to it. As simple adsorption of the growth factor to the carrier surface by soak loading produces a burst release of growth factors with rapid decrease of biological activity, the ability to accomplish controlled release of functional growth factor molecules is one of the crucial characteristics for an appropriate carrier material. Conclusion The variety of carrier materials requires different strategies to either couple growth factors to the material surface or to incorporate them into the carrier matrix. The present review outlines current technical approaches and discusses future trends in the use of carrier materials for bone growth factors

Production of scFv-Conjugated Affinity Silk Powder by Transgenic Silkworm Technology

Bombyx mori (silkworm) silk proteins are being utilized as unique biomaterials for medical applications. Chemical modification or post-conjugation of bioactive ligands expand the applicability of silk proteins; however, the processes are elaborate and costly. In this study, we used transgenic silkworm technology to develop single-chain variable fragment (scFv)-conjugated silk fibroin. The cocoons of the transgenic silkworm contain fibroin L-chain linked with scFv as a fusion protein. After dissolving the cocoons in lithium bromide, the silk solution was dialyzed, concentrated, freeze-dried, and crushed into powder. Immunoprecipitation analyses demonstrate that the scFv domain retains its specific binding activity to the target molecule after multiple processing steps. These results strongly suggest the promise of scFv-conjugated silk fibroin as an alternative affinity reagent, which can be manufactured using transgenic silkworm technology at lower cost than traditional affinity carriers

Order versus Disorder: in vivo bone formation within osteoconductive scaffolds

In modern biomaterial design the generation of an environment mimicking some of the extracellular matrix features is envisaged to support molecular cross-talk between cells and scaffolds during tissue formation/remodeling. In bone substitutes chemical biomimesis has been particularly exploited; conversely, the relevance of pre-determined scaffold architecture for regenerated bone outputs is still unclear. Thus we aimed to demonstrate that a different organization of collagen fibers within newly formed bone under unloading conditions can be generated by differently architectured scaffolds. An ordered and confined geometry of hydroxyapatite foams concentrated collagen fibers within the pores, and triggered their self-assembly in a cholesteric-banded pattern, resulting in compact lamellar bone. Conversely, when progenitor cells were loaded onto nanofibrous collagen-based sponges, new collagen fibers were distributed in a nematic phase, resulting mostly in woven isotropic bone. Thus specific biomaterial design relevantly contributes to properly drive collagen fibers assembly to target bone regeneration

Human Dental Pulp Stem Cells Hook into Biocoral Scaffold Forming an Engineered Biocomplex

The aim of this study was to evaluate the behavior of human Dental Pulp Stem Cells (DPSCs), as well as human osteoblasts, when challenged on a Biocoral scaffold, which is a porous natural hydroxyapatite. For this purpose, human DPSCs were seeded onto a three-dimensional (3D) Biocoral scaffold or on flask surface (control). Either normal or rotative (3D) cultures were performed. Scanning electron microscopic analyses, at 8, 24 and 48 h of culture showed that cells did not adhere on the external surface, but moved into the cavities inside the Biocoral structure. After 7, 15 and 30 days of culture, morphological and molecular analyses suggested that the Biocoral scaffold leads DPSCs to hook into the cavities where these cells quickly start to secrete the extra cellular matrix (ECM) and differentiate into osteoblasts. Control human osteoblasts also moved into the internal cavities where they secreted the ECM. Histological sections revealed a diffuse bone formation inside the Biocoral samples seeded with DPSCs or human osteoblasts, where the original scaffold and the new secreted biomaterial were completely integrated and cells were found within the remaining cavities. In addition, RT-PCR analyses showed a significant increase of osteoblast-related gene expression and, above all, of those genes highly expressed in mineralized tissues, including osteocalcin, OPN and BSP. Furthermore, the effects on the interaction between osteogenesis and angiogenesis were observed and substantiated by ELISA assays. Taken together, our results provide clear evidence that DPSCs differentiated into osteoblasts, forming a biocomplex made of Biocoral, ECM and differentiated cells