Yann Ilboudo

Background: Observational studies have found that vitamin D supplementation is associated with improved cognition. Further, recent Mendelian randomization (MR) studies have shown that higher vitamin D levels, 25(OH)D, may protect against Alzheimer’s disease. Thus, it is possible that 25(OH)D may protect against Alzheimer’s disease by improving cognition. Objective: We assessed this hypothesis, by examining the relationship between 25(OH)D levels and seven cognitive measurements. Methods: To mitigate bias from confounding, we performed two-sample MR analyses. We used instruments from three publications: Manousaki et al. (2020), Sutherland et al. (2022), and the Emerging Risk Factors Collaboration/EPIC-CVD/Vitamin D Studies Collaboration (2021). Results: Our observational studies suggested a protective association between 25(OH)D levels and cognitive measures. An increase in the natural log of 25(OH)D by 1 SD was associated with a higher PACC score (BetaPACC score = 0.06, 95% CI = (0.04-0.08); p = 1.8×10-10). However, in the MR analyses, the estimated effect of 25(OH)D on cognitive measures was null. Specifically, per 1 SD increase in genetically estimated natural log of 25(OH)D, the PACC scores remained unchanged in the overall population, (BetaPACC score = -0.01, 95% CI (-0.06 to 0.03); p = 0.53), and amongst individuals aged over 60 (BetaPACC score = 0.03, 95% CI (-0.028 to 0.08); p = 0.35). Conclusions: In conclusion, our MR study found no clear evidence to support a protective role of increased 25(OH)D concentrations on cognitive performance in European ancestry individuals. However, our study cannot entirely dismiss the potential beneficial effect on PACC for individuals over the age of 60.

Context: Trinucleotide repeats in the androgen receptor have been proposed to influence testosterone signaling in men, but the clinical relevance of these trinucleotide repeats remains controversial. Objective: To examine how androgen receptor trinucleotide repeat lengths affect androgen-related traits and disease risks and whether they influence the clinical importance of circulating testosterone levels. Methods: We quantified CAG and GGC repeat lengths in the androgen receptor (AR) gene of European-ancestry male participants in UK Biobank from whole-genome and whole-exome sequence data using ExpansionHunter, and tested associations with androgen-related traits and diseases. We also examined whether the associations between testosterone levels and these outcomes were affected by adjustment for the repeat lengths. Results: We successfully quantified the repeat lengths from whole-genome and/or whole-exome sequence data in 181,217 males. Both repeat lengths were shown to be positively associated with circulating total testosterone level and bone mineral density, whereas CAG repeat length was negatively associated with male-pattern baldness, but their effects were relatively small and were not associated with most of the other outcomes. Circulating total testosterone level was associated with various outcomes, but this relationship was not affected by adjustment for the repeat lengths. Conclusion: In this large-scale study, we found that longer CAG and GGC repeats in the AR gene influence androgen resistance, elevate circulating testosterone level via a feedback loop and play a role in some androgen-targeted tissues. Generally, however, circulating testosterone level is a more important determinant of androgen action in males than repeat lengths.

Context: A novel algorithm, AlphaMissense, has been shown to have an improved ability to predict the pathogenicity of rare missense genetic variants. However, it is not known whether AlphaMissense improves the ability of gene-based testing to identify disease-influencing genes. Using whole-exome sequencing data from the UK Biobank, we compared gene-based association analysis strategies including sets of deleterious variants: predicted loss-of-function (pLoF) variants only, pLoF plus AlphaMissense pathogenic variants, pLoF with missense variants predicted to be deleterious by any of five commonly utilized annotation methods (Missense (1/5)) or only variants predicted to be deleterious by all five methods (Missense (5/5)). We measured performance to identify 519 previously identified positive control genes, which can lead to Mendelian diseases, or are the targets of successfully developed medicines. These strategies identified 0.85 million pLoF variants and 5 million deleterious missense variants, including 22,131 likely pathogenic missense variants identified exclusively by AlphaMissense. The gene-based association tests found 608 significant gene associations (at p < 1.25 × 10−7) across 24 common traits and diseases. Compared with pLoFs plus Missense (5/5), tests using pLoFs and AlphaMissense variants found slightly more significant gene-disease and gene-trait associations, albeit with a marginally lower proportion of positive control genes. Nevertheless, their overall performance was similar. Merging AlphaMissense with Missense (5/5), whether through their intersection or union, did not yield any further enhancement in performance. In summary, employing AlphaMissense to select deleterious variants for gene-based testing did not improve the ability to identify genes that are known to influence disease.

Background: Preventive measures and treatments for psychiatric disorders are limited. Circulating metabolites are potential candidates for biomarker and therapeutic target identification, given their measurability and essential roles in biological processes. Methods: Leveraging large-scale genome-wide association studies, we conducted Mendelian randomization analyses to assess the associations between circulating metabolite abundances and the risks of bipolar disorder, schizophrenia, and depression. Genetic instruments were selected for 94 metabolites measured in the Canadian Longitudinal Study on Aging cohort (N = 8299). We repeated Mendelian randomization analyses based on the UK Biobank, INTERVAL, and EPIC (European Prospective Investigation into Cancer)-Norfolk studies. Results: After validating Mendelian randomization assumptions and colocalization evidence, we found that a 1 SD increase in genetically predicted circulating abundances of eicosapentaenoate and docosapentaenoate was associated with odds ratios of 0.72 (95% CI, 0.65-0.79) and 0.63 (95% CI, 0.55-0.72), respectively, for bipolar disorder. Genetically increased Ω-3 unsaturated fatty acids abundance and Ω-3-to-total fatty acids ratio, as well as genetically decreased Ω-6-to-Ω-3 ratio, were negatively associated with the risk of bipolar disorder in the UK Biobank. Genetically increased circulating abundances of 3 N-acetyl-amino acids were associated with an increased risk of schizophrenia with a maximum odds ratio of 1.31 (95% CI, 1.18-1.44) per 1 SD increase. Furthermore, a 1 SD increase in genetically predicted circulating abundance of hypotaurine was associated with an odds ratio of 0.85 (95% CI, 0.78-0.93) for depression. Conclusions: The biological mechanisms that underlie Ω-3 unsaturated fatty acids, NAT8-catalyzed N-acetyl-amino acids, and hypotaurine warrant exploration to identify new biomarkers and potential therapeutic targets.

The outcome for patients with sepsis-associated acute kidney injury in the intensive care unit (ICU) remains poor. Low serum uromodulin (sUMOD) protein levels have been proposed as a causal mediator of this effect. We investigated the effect of different levels of sUMOD on the risk of sepsis and severe pneumonia and outcomes in these conditions. A two-sample Mendelian randomization (MR) study was performed. Single-nucleotide polymorphisms (SNPs) associated with increased levels of sUMOD were identified and used as instrumental variables for association with outcomes. Data from different cohorts were combined based on disease severity and meta-analyzed. Five SNPs associated with increased sUMOD levels were identified and tested in six datasets from two biobanks. There was no protective effect of increased levels of sUMOD on the risk of sepsis [two cohorts, odds ratio (OR) 0.99 (95% confidence interval 0.95-1.03), P = 0.698, and OR 0.95 (0.91-1.00), P = 0.060, respectively], risk of sepsis requiring ICU admission [OR 1.04 (0.93-1.16), P = 0.467], ICU mortality in sepsis [OR 1.00 (0.74-1.37), P = 0.987], risk of pneumonia requiring ICU admission [OR 1.05 (0.98-1.14), P = 0.181], or ICU mortality in pneumonia [OR 1.17 (0.98-1.39), P = 0.079]. Meta-analysis of hospital-admitted and ICU-admitted patients separately yielded similar results [OR 0.98 (0.95-1.01), P = 0.23, and OR 1.05 (0.99-1.12), P = 0.86, respectively]. Among patients with sepsis and severe pneumonia, there was no protective effect of different levels of sUMOD. Results were consistent regardless of geographic origins and not modified by disease severity. NEW & NOTEWORTHY The presence of acute kidney injury in severe infections increases the likelihood of poor outcome severalfold. A decrease in serum uromodulin (sUMOD), synthetized in the kidney, has been proposed as a mediator of this effect. Using the Mendelian randomization technique, we tested the hypothesis that increased sUMOD is protective in severe infections. Analyses, however, showed no evidence of a protective effect of higher levels of sUMOD in sepsis or severe pneumonia.

The human leukocyte antigen (HLA) region on chromosome 6 is strongly associated with many immune-mediated and infection-related diseases. Due to its highly polymorphic nature and complex linkage disequilibrium patterns, traditional genetic association studies of single nucleotide polymorphisms do not perform well in this region. Instead, the field has adopted the assessment of the association of HLA alleles (i.e., entire HLA gene haplotypes) with disease. Often based on genotyping arrays, these association studies impute HLA alleles, decreasing accuracy and thus statistical power for rare alleles and in non-European ancestries. Here, we use whole-exome sequencing (WES) from 454,824 UK Biobank (UKB) participants to directly call HLA alleles using the HLA-HD algorithm. We show this method is more accurate than imputing HLA alleles and harness the improved statistical power to identify 360 associations for 11 auto-immune phenotypes (at least 129 likely novel), leading to better insights into the specific coding polymorphisms that underlie these diseases. We show that HLA alleles with synonymous variants, often overlooked in HLA studies, can significantly influence these phenotypes. Lastly, we show that HLA sequencing may improve polygenic risk scores accuracy across ancestries. These findings allow better characterization of the role of the HLA region in human disease.