Mendelian randomization to evaluate the effect of plasma vitamin C levels on the risk of Alzheimer’s disease

Objective Until now, observational studies have explored the impact of vitamin C intake on Alzheimer’s disease (AD) risk, however, reported ambiguous findings. To develop effective therapies or prevention, the causal link between vitamin C levels and AD should be established. Methods Here, we selected 11 plasma vitamin C genetic variants from a large-scale plasma vitamin C GWAS dataset (N = 52,018) as the potential instrumental variables. We extracted their corresponding summary statistics from large-scale IGAP clinically diagnosed AD GWAS dataset (N = 63,926) and UK Biobank AD proxy phenotype GWAS dataset (N = 314,278), as well as two UK Biobank subgroups including the maternal AD group (27,696 cases of maternal AD and 260,980 controls) and paternal AD group (14,338 cases of paternal AD and 245,941 controls). We then performed a Mendelian randomization (MR) study to evaluate the causal association between plasma vitamin C levels and the risk of AD and AD proxy phenotype. Meanwhile, we further verified these findings using a large-scale cognitive performance GWAS dataset (N = 257,841). Results In IGAP, we found no significant causal association between plasma vitamin C levels and the risk of AD. In UK Biobank, we found that per 1 SD increase in plasma vitamin C levels (about 20.2 μmol/l) was significantly associated with the reduced risk of AD proxy phenotype (OR = 0.93, 95% CI 0.88–0.98, P = 7.00E−03). A subgroup MR analysis in UK Biobank indicated that per 1 SD increase in plasma vitamin C levels could significantly reduce the risk of AD proxy phenotype in the maternal AD group (OR = 0.89, 95% CI 0.84–0.94, P = 7.29E−05), but not in the paternal AD group (OR = 1.02, 95% CI 0.92–1.12, P = 7.59E−01). The leave-one-out permutation further showed that the SLC23A1 rs33972313 variant largely changed the precision of the overall MR estimates in all these four GWAS datasets. Meanwhile, we did not observe any significant causal effect of plasma vitamin C levels on the cognitive performance. Conclusion We demonstrated that there may be no causal association between plasma vitamin C levels and the risk of AD in people of European descent. The insistent findings in clinically diagnosed AD and AD proxy phenotype may be caused by the phenotypic heterogeneity.

A novel computational methodology for GWAS multi-locus analysis based on graph theory and machine learning

Background: Current form of genome-wide association studies (GWAS) is inadequate to accurately explain the genetics of complex traits due to the lack of sufficient statistical power. It explores each variant individually, but current studies show that multiple variants with varying effect sizes actually act in a concerted way to develop a complex disease. To address this issue, we have developed an algorithmic framework that can effectively solve the multi-locus problem in GWAS with a very high level of confidence. Our methodology consists of three novel algorithms based on graph theory and machine learning. It identifies a set of highly discriminating variants that are stable and robust with little (if any) spuriousness. Consequently, likely these variants should be able to interpret missing heritability of a convoluted disease as an entity. Results: To demonstrate the efficacy of our proposed algorithms, we have considered astigmatism case-control GWAS dataset. Astigmatism is a common eye condition that causes blurred vision because of an error in the shape of the cornea. The cause of astigmatism is not entirely known but a sizable inheritability is assumed. Clinical studies show that developmental disorders (such as, autism) and astigmatism co-occur in a statistically significant number of individuals. By performing classical GWAS analysis, we didn't find any genome-wide statistically significant variants. Conversely, we have identified a set of stable, robust, and highly predictive variants that can together explain the genetics of astigmatism. We have performed a set of biological enrichment analyses based on gene ontology (GO) terms, disease ontology (DO) terms, biological pathways, network of pathways, and so forth to manifest the accuracy and novelty of our findings. Conclusions: Rigorous experimental evaluations show that our proposed methodology can solve GWAS multi-locus problem effectively and efficiently. It can identify signals from the GWAS dataset having small number of samples with a high level of accuracy. We believe that the proposed methodology based on graph theory and machine learning is the most comprehensive one compared to any other machine learning based tools in this domain.

An Updated Mendelian Randomization Analysis of the Association Between Serum Calcium Levels and the Risk of Alzheimer’s Disease

It has been a long time that the relationship between serum calcium levels and Alzheimer’s disease (AD) remains unclear. Until recently, observational studies have evaluated the association between serum calcium levels and the risk of AD, however, reported inconsistent findings. Meanwhile, a Mendelian randomization (MR) study had been conducted to test the causal association between serum calcium levels and AD risk, however, only selected 6 serum calcium SNPs as the instrumental variables. Hence, these findings should be further verified using additional more genetic variants and large-scale genome-wide association study (GWAS) dataset to increase the statistical power. Here, we conduct an updated MR analysis of the causal association between serum calcium levels and the risk of AD using a two-stage design. In discovery stage, we conducted a MR analysis using 14 SNPs from serum calcium GWAS dataset (N = 61,079), and AD GWAS dataset (N = 63,926, 21,982 cases, 41,944 cognitively normal controls). All four MR methods including IVW, weighted median, MR-Egger, and MR-PRESSO showed a reduced trend of AD risk with the increased serum calcium levels. In the replication stage, we performed a MR analysis using 166 SNPs from serum calcium GWAS dataset (N = 305,349), and AD GWAS dataset (N = 63,926, 21,982 cases, 41,944 cognitively normal controls). Only the weighted median indicated that genetically increased serum calcium level was associated with the reduced risk of AD. Hence, additional studies are required to investigate these findings.

Gene-Based Tests of a Genome-Wide Association Study Dataset Highlight Novel Multiple Sclerosis Risk Genes

Multiple sclerosis (MS) is an autoimmune disorder influenced by genetic and environmental factors. Many studies have provided insights into genetic factors’ contribution to MS via large-scale genome-wide association study (GWAS) datasets. However, genetic variants identified to date do not adequately explain genetic risks for MS. This study hypothesized that novel MS risk genes could be identified by analyzing the MS-GWAS dataset using gene-based tests. We analyzed a GWAS dataset consisting of 9,772 MS cases and 17,376 healthy controls of European descent. We performed gene-based tests of 464,357 autosomal single nucleotide polymorphisms (SNPs) using two methods (PLINK and VEGAS2) and identified 28 shared genes satisfied p-value < 4.56 × 10–6. In further gene expression analysis, ten of the 28 genes were significantly differentially expressed in the MS case-control gene expression omnibus (GEO) database. GALC and HLA-DOB showed the most prominent differences in gene expression (two- and three-fold, respectively) between MS patients and healthy controls. In conclusion, our results reveal more information about MS hereditary characteristics and provide a basis for further studies.

Integrated Genetics and Micronutrient Data to Inform the Causal Association Between Serum Calcium Levels and Ischemic Stroke

There has been an increased interest for observational studies or randomized controlled trials exploring the impact of calcium intake on cardiovascular diseases (CVD) including coronary artery disease (CAD) and ischemic stroke (IS). However, a direct relationship between total calcium intake and CVD has not been well established and remains controversial. Mendelian randomization (MR) studies have been performed to evaluate the causal association between serum calcium levels and CAD risk and found that increased serum calcium levels could increase the risk of CAD. However, MR analysis found no significant association between genetically higher serum calcium levels and IS as well as its subtypes. Hence, three MR studies reported inconsistent effects of serum calcium levels on CAD and IS. Here, we performed an updated MR study to investigate the association of serum calcium levels with the risk of IS using large-scale genome-wide association study (GWAS) datasets. We selected 14 independent genetic variants as the potential instrumental variables from a large-scale serum calcium GWAS dataset and extracted summary statistics corresponding to the 14 serum calcium genetic variants from the MEGASTROKE Consortium IS GWAS dataset. Interestingly, we found a significant association between serum calcium levels and IS risk using the robust inverse-variance weighted (IVW) and penalized robust IVW methods, with β = 0.243 and P = 0.002. Importantly, the MR results from the robust MR-Egger and penalized robust MR-Egger methods further supported the causal association between serum calcium levels and IS risk, with β = 0.256 and P = 0.005. Meanwhile, the estimates from other MR methods are also consistent with the above findings.

Impact of serum calcium levels on local and total body bone mineral density: A Mendelian randomization study and an age stratum analysis

ObjectivesUntil recently, randomized controlled trials and meta-analyses have not demonstrated convincing conclusions regarding the association of calcium intake with bone mineral density (BMD). Until now, it remains unclear whether high serum calcium levels are causally associated with BMD. This study aimed to investigate the genetic association between serum calcium levels and BMD using a large-scale serum calcium GWAS dataset and four large-scale BMD GWAS datasets in individuals of European descent.MethodsWe performed a Mendelian randomization study to investigate the association of increased serum calcium levels with BMD using a large-scale serum calcium genome-wide association study (GWAS) dataset (including up to 61,079 individuals) and four large-scale BMD GWAS datasets (including minimum 4,180 individuals and maximum 142,487 individuals) regarding the total body, forearm, femoral neck, lumbar spine, and heel BMD. Here, we selected three Mendelian randomization methods including inverse-variance weighted meta-analysis (IVW), weighted median, and MR-Egger.ResultsIn specific site analysis, we found that increased serum calcium levels could reduce BMD at forearm (OR=0.59, 95% CI: 0.36-0.95, P=0.029) and lumbar spine (OR=0.65, 95% CI: 0.49-0.86, P=0.002). We did not identify any suggestive association of genetically increased serum calcium levels with BMD of total body, femoral neck, and heel BMD. In specific age stratum analysis, we found that genetically increased serum calcium levels were statistically significantly associated with reduced total body BMD in age stratum 60 or more years (OR=0.58, 95% CI: 0.41-0.82, P=0.002).ConclusionsWe provide genetic evidence that increased serum calcium levels could not improve BMD in the general population. The elevated serum calcium levels in generally healthy populations, especially adults older than 60 years, may even reduce the BMD, and further cause osteoporosis.

Identifying communities from multiplex biological networks by randomized optimization of modularity

The identification of communities, or modules, is a common operation in the analysis of large biological networks. The Disease Module Identification DREAM challenge established a framework to evaluate clustering approaches in a biomedical context, by testing the association of communities with GWAS-derived common trait and disease genes. We implemented here several extensions of the MolTi software that detects communities by optimizing multiplex (and monoplex) network modularity. In particular, MolTi now runs a randomized version of the Louvain algorithm, can consider edge and layer weights, and performs recursive clustering. On simulated networks, the randomization procedure clearly improves the detection of communities. On the DREAM challenge benchmark, the results strongly depend on the selected GWAS dataset and enrichment p-value threshold. However, the randomization procedure, as well as the consideration of weighted edges and layers generally increases the number of trait and disease community detected. The new version of MolTi and the scripts used for the DMI DREAM challenge are available at: https://github.com/gilles-didier/MolTi-DREAM.

Identifying communities from multiplex biological networks by randomized optimization of modularity

The identification of communities, or modules, is a common operation in the analysis of large biological networks. The Disease Module Identification DREAM challenge established a framework to evaluate clustering approaches in a biomedical context, by testing the association of communities with GWAS-derived common trait and disease genes. We implemented here several extensions of the MolTi software that detects communities by optimizing multiplex (and monoplex) network modularity. In particular, MolTi now runs a randomized version of the Louvain algorithm, can consider edge and layer weights, and performs recursive clustering. On simulated networks, the randomization procedure clearly improves the detection of communities. On the DREAM challenge benchmark, the results strongly depend on the selected GWAS dataset and enrichment p-value threshold. However, the randomization procedure, as well as the consideration of weighted edges and layers generally increases the number of trait and disease community detected. The new version of MolTi and the scripts used for the DMI DREAM challenge are available at: https://github.com/gilles-didier/MolTi-DREAM.

Genetically increased serum calcium levels reduce Alzheimer’s disease risk

IMPORTANCE Alzheimer’s disease (AD) is the leading cause of disability in the elderly. It has been a long time about the calcium hypothesis of AD on the basis of emerging evidence since 1994. However, most studies focused on the association between calcium homeostasis and AD, and concerned the intracellular calcium concentration. Only few studies reported reduced serum calcium levels in AD. Until now, it remains unclear whether serum calcium levels are genetically associated with AD risk.OBJECTIVE To evaluate the genetic association between increased serum calcium levels and AD riskDESIGN, SETTING, AND PARTICIPANTS We performed a Mendelian randomization study to investigate the association of increased serum calcium with AD risk using the genetic variants from the large-scale serum calcium genome-wide association study (GWAS) dataset (N=61,079 individuals of European descent) and the large-scale AD GWAS dataset (N=54,162 individuals including 17,008 AD cases and 37,154 controls of European descent). Inverse-variance weighted meta-analysis (IVW) was used to provide a combined estimate of the genetic association. Meanwhile, we selected the weighted median regression and MR-Egger regression as the complementary analysis methods to examine the robustness of the IVW estimate.EXPOSURES Genetic predisposition to increased serum calcium levelsMAIN OUTCOMES AND MEASURES The risk of AD.RESULTS We selected 6 independent genetic variants influencing serum calcium levels as the instrumental variables. IVW analysis showed that a genetically increased serum calcium level (per 1 standard deviation (SD) increase 0.5-mg/dL) was significantly associated with a reduced AD risk (OR=0.56, 95% CI: 0.34-0.94, P=5.00E-03). Meanwhile, both the weighted median estimate (OR=0.60, 95% CI: 0.34-1.06, P=0.08) and MR-Egger estimate (OR=0.66, 95% CI: 0.26-1.67, P=0.381) were consistent with the IVW estimate in terms of direction and magnitude.CONCLUSIONS AND RELEVANCE We provided evidence that genetically increased serum calcium levels could reduce the risk of AD. Meanwhile, randomized controlled study should be further conducted to assess the effect of serum calcium levels on AD risk, and further clarify whether diet calcium intake or calcium supplement, or both could reduce the risk of AD.Key PointsQuestion Is there a genetic relationship between elevated serum calcium levels and the risk of Alzheimer’s disease?Findings This Mendelian randomization study showed that the genetically increased serum calcium levels were associated with the reduced risk of Alzheimer’s disease.Meaning These findings provide evidence that genetically increased serum calcium levels could reduce the risk of Alzheimer’s disease.