Contribution of Nutritional, Lifestyle, and Metabolic Risk Factors to Parkinson's Disease

BACKGROUND

Modifiable risk factors for Parkinson's disease (PD) are poorly known.

OBJECTIVES

The aim is to evaluate independent associations of different nutritional components, physical activity, and sedentary behavior and metabolic factors with the risk of PD.

METHODS

In this population-based prospective cohort study using the data of the United Kingdom Biobank (from 2006-2010), 502,017 men and women who were free from PD (International Classification of Diseases 10th edition; "G20") at baseline were included. We implemented a Cox proportion hazard's model to evaluate the associations of different levels of physical activity, sitting time, sleep habits, diet quality, alcohol and coffee consumption, smoking, and body mass index with PD risk, adjusting for several confounding variables.

RESULTS

During a median follow-up of 12.8 years, lifestyle factors including vigorous physical activity (hazard ration [HR] = 0.84; 95% confidence interval [CI], 0.75-0.94), low-to-moderate sitting time (HR = 0.89; 95% CI, 0.81-0.97), and high sleep quality (HR = 0.89; 95% CI, 0.80-0.99) were associated with a reduced risk of PD. Small amounts of coffee (HR = 0.88; 95% CI, 0.82-0.95), red meat (HR = 0.86; 95% CI, 0.76-0.97), and current smoking (HR = 0.65; 95% CI, 0.56-0.75) were also associated with a lower risk of PD, whereas alcohol intake (HR = 1.29; 95% CI, 1.06-1.56) with higher PD risk. Secondary analysis, including metabolic risk factors, confirmed these findings and highlighted the potential protective effect of plasma vitamin D and uric acid, but of low-density lipoprotein-cholesterol, triglycerides, and C-reactive protein as well.

CONCLUSIONS

Vigorous physical activity, reduced sitting time, good sleep quality together with small coffee intake and vitamin D supplementation are potentially neuroprotective lifestyle interventions for the prevention of PD. © 2024 International Parkinson and Movement Disorder Society.

Identification of the VLDLR locus associated with giant cell arteritis and the possible causal role of low-density lipoprotein cholesterol in its pathogenesis

OBJECTIVES

To elucidate the association between genetic variants and the risk of giant cell arteritis (GCA) via large-scale genome-wide association studies (GWAS). In addition, to assess the causal effect of a specific molecule by employing the obtained GWAS results as genetic epidemiological tools.

METHODS

We applied additional variant quality control to the publicly available GWAS results from the biobank of the United Kingdom (UKBB) and Finnish (FinnGen), which comprised 532 cases vs 408 565 controls and 884 cases vs 332 115 controls, respectively. We further meta-analyzed these two sets of results. We performed two-sample Mendelian randomization (MR) to test the causal effect of low-density lipoprotein (LDL) cholesterol on the risk of GCA.

RESULTS

The MHC class II region showed significant associations in UKBB, FinnGen, and the meta-analysis. The VLDLR region was associated with GCA risk in the meta-analysis. The T allele of rs7044155 increased the expression of VLDLR, decreased the LDL cholesterol level, and decreased the disease risk. The subsequent MR results indicated that a 1-standard deviation increase in LDL cholesterol was associated with an increased risk of GCA (odds ratio [OR] 1.21, 95% confidence interval [CI] 1.01-1.45; p = 0.04).

CONCLUSIONS

Our study identified associations between GCA risk and the MHC class II and VLDLR regions. Moreover, LDL cholesterol was suggested to have a causal effect on the risk of developing GCA.

Genome-wide association studies and polygenic risk score phenome-wide association studies across complex phenotypes in the human phenotype project

BACKGROUND

Genome-wide association studies (GWASs) associate phenotypes and genetic variants across a study cohort. GWASs require large-scale cohorts with both phenotype and genetic sequencing data, limiting studied phenotypes. The Human Phenotype Project is a longitudinal study that has measured a wide range of clinical and biomolecular features from a self-assignment cohort over 5 years. The phenotypes collected are quantitative traits, providing higher-resolution insights into the genetics of complex phenotypes.

METHODS

We present the results of GWASs and polygenic risk score phenome-wide association studies with 729 clinical phenotypes and 4,043 molecular features from the Human Phenotype Project. This includes clinical traits that have not been previously associated with genetics, including measures from continuous sleep monitoring, continuous glucose monitoring, liver ultrasound, hormonal status, and fundus imaging.

FINDINGS

In GWAS of 8,706 individuals, we found significant associations between 169 clinical traits and 1,184 single-nucleotide polymorphisms. We found genes associated with both glycemic control and mental disorders, and we quantify the strength of genetic signals in serum metabolites. In polygenic risk score phenome-wide association studies for clinical traits, we found 16,047 significant associations.

CONCLUSIONS

The entire set of findings, which we disseminate publicly, provides newfound resolution into the genetic architecture of complex human phenotypes.

FUNDING

E.S. is supported by the Minerva foundation with funding from the Federal German Ministry for Education and Research and by the European Research Council and the Israel Science Foundation.

Accounting for age of onset and family history improves power in genome-wide association studies

Genome-wide association studies (GWASs) have revolutionized human genetics, allowing researchers to identify thousands of disease-related genes and possible drug targets. However, case-control status does not account for the fact that not all controls may have lived through their period of risk for the disorder of interest. This can be quantified by examining the age-of-onset distribution and the age of the controls or the age of onset for cases. The age-of-onset distribution may also depend on information such as sex and birth year. In addition, family history is not routinely included in the assessment of control status. Here, we present LT-FH++, an extension of the liability threshold model conditioned on family history (LT-FH), which jointly accounts for age of onset and sex as well as family history. Using simulations, we show that, when family history and the age-of-onset distribution are available, the proposed approach yields statistically significant power gains over LT-FH and large power gains over genome-wide association study by proxy (GWAX). We applied our method to four psychiatric disorders available in the iPSYCH data and to mortality in the UK Biobank and found 20 genome-wide significant associations with LT-FH++, compared to ten for LT-FH and eight for a standard case-control GWAS. As more genetic data with linked electronic health records become available to researchers, we expect methods that account for additional health information, such as LT-FH++, to become even more beneficial.

Minor Allele Frequencies and Molecular Pathways Differences for SNPs Associated with Amyotrophic Lateral Sclerosis in Subjects Participating in the UKBB and 1000 Genomes Project

Amyotrophic lateral sclerosis (ALS) is a complex disease with a late onset and is characterized by the progressive loss of muscular and respiratory functions. Although recent studies have partially elucidated ALS's mechanisms, many questions remain such as what the most important molecular pathways involved in ALS are and why there is such a large difference in ALS onset among different populations. In this study, we addressed this issue with a bioinformatics approach, using the United Kingdom Biobank (UKBB) and the European 1000 Genomes Project (1KG) in order to analyze the most ALS-representative single nucleotide polymorphisms (SNPs) that differ for minor allele frequency (MAF) between the United Kingdom population and some European populations including Finnish in Finland, Iberian population in Spain, and Tuscans in Italy. We found 84 SNPs associated with 46 genes that are involved in different pathways including: "Ca²⁺ activated K⁺ channels", "cGMP effects", "Nitric oxide stimulates guanylate cyclase", "Proton/oligopeptide cotransporters", and "Signaling by MAPK mutants". In addition, we revealed that 83% of the 84 SNPs can alter transcription factor-motives binding sites of 224 genes implicated in "Regulation of beta-cell development", "Transcription-al regulation by RUNX3", "Transcriptional regulation of pluripotent stem cells", and "FOXO-mediated transcription of cell death genes". In conclusion, the genes and pathways analyzed could explain the cause of the difference of ALS onset.

Genome-wide Study Identifies Association between HLA-B∗55:01 and Self-Reported Penicillin Allergy

Hypersensitivity reactions to drugs are often unpredictable and can be life threatening, underscoring a need for understanding their underlying mechanisms and risk factors. The extent to which germline genetic variation influences the risk of commonly reported drug allergies such as penicillin allergy remains largely unknown. We extracted data from the electronic health records of more than 600,000 participants from the UK, Estonian, and Vanderbilt University Medical Center's BioVU biobanks to study the role of genetic variation in the occurrence of self-reported penicillin hypersensitivity reactions. We used imputed SNP to HLA typing data from these cohorts to further fine map the human leukocyte antigen (HLA) association and replicated our results in 23andMe's research cohort involving a total of 1.12 million individuals. Genome-wide meta-analysis of penicillin allergy revealed two loci, including one located in the HLA region on chromosome 6. This signal was further fine-mapped to the HLA-B∗55:01 allele (OR 1.41 95% CI 1.33-1.49, p value 2.04 × 10-31) and confirmed by independent replication in 23andMe's research cohort (OR 1.30 95% CI 1.25-1.34, p value 1.00 × 10-47). The lead SNP was also associated with lower lymphocyte counts and in silico follow-up suggests a potential effect on T-lymphocytes at HLA-B∗55:01. We also observed a significant hit in PTPN22 and the GWAS results correlated with the genetics of rheumatoid arthritis and psoriasis. We present robust evidence for the role of an allele of the major histocompatibility complex (MHC) I gene HLA-B in the occurrence of penicillin allergy.

Corrigendum: Pediatric Acute Myeloid Leukemia (AML): From Genes to Models Toward Targeted Therapeutic Intervention

[This corrects the article DOI: 10.3389/fped.2019.00401.].

Pediatric Acute Myeloid Leukemia (AML): From Genes to Models Toward Targeted Therapeutic Intervention

This review aims to provide an overview of the current knowledge of the genetic lesions driving pediatric acute myeloid leukemia (AML), emerging biological concepts, and strategies for therapeutic intervention. Hereby, we focus on lesions that preferentially or exclusively occur in pediatric patients and molecular markers of aggressive disease with often poor outcome including fusion oncogenes that involve epigenetic regulators like KMT2A, NUP98, or CBFA2T3, respectively. Functional studies were able to demonstrate cooperation with signaling mutations leading to constitutive activation of FLT3 or the RAS signal transduction pathways. We discuss the issues faced to faithfully model pediatric acute leukemia in mice. Emerging experimental evidence suggests that the disease phenotype is dependent on the appropriate expression and activity of the driver fusion oncogenes during a particular window of opportunity during fetal development. We also highlight biochemical studies that deciphered some molecular mechanisms of malignant transformation by KMT2A, NUP98, and CBFA2T3 fusions, which, in some instances, allowed the development of small molecules with potent anti-leukemic activities in preclinical models (e.g., inhibitors of the KMT2A-MENIN interaction). Finally, we discuss other potential therapeutic strategies that not only target driver fusion-controlled signals but also interfere with the transformed cell state either by exploiting the primed apoptosis or vulnerable metabolic states or by increasing tumor cell recognition and elimination by the immune system.