Mapping genomic loci implicates genes and synaptic biology in schizophrenia.

Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies.

Mitigating type 1 error inflation and power loss in GxE PRS: Genotype-environment interaction in polygenic risk score models.

The use of polygenic risk score (PRS) models has transformed the field of genetics by enabling the prediction of complex traits and diseases based on an individual's genetic profile. However, the impact of genotype-environment interaction (GxE) on the performance and applicability of PRS models remains a crucial aspect to be explored. Currently, existing genotype-environment interaction polygenic risk score (GxE PRS) models are often inappropriately used, which can result in inflated type 1 error rates and compromised results. In this study, we propose novel GxE PRS models that jointly incorporate additive and interaction genetic effects although also including an additional quadratic term for nongenetic covariates, enhancing their robustness against model misspecification. Through extensive simulations, we demonstrate that our proposed models outperform existing models in terms of controlling type 1 error rates and enhancing statistical power. Furthermore, we apply the proposed models to real data, and report significant GxE effects. Specifically, we highlight the impact of our models on both quantitative and binary traits. For quantitative traits, we uncover the GxE modulation of genetic effects on body mass index by alcohol intake frequency. In the case of binary traits, we identify the GxE modulation of genetic effects on hypertension by waist-to-hip ratio. These findings underscore the importance of employing a robust model that effectively controls type 1 error rates, thus preventing the occurrence of spurious GxE signals. To facilitate the implementation of our approach, we have developed an innovative R software package called GxEprs, specifically designed to detect and estimate GxE effects. Overall, our study highlights the importance of accurate GxE modeling and its implications for genetic risk prediction, although providing a practical tool to support further research in this area.

Cross-ancestry genetic architecture and prediction for cholesterol traits.

While cholesterol is essential, a high level of cholesterol is associated with the risk of cardiovascular diseases. Genome-wide association studies (GWASs) have proven successful in identifying genetic variants that are linked to cholesterol levels, predominantly in white European populations. However, the extent to which genetic effects on cholesterol vary across different ancestries remains largely unexplored. Here, we estimate cross-ancestry genetic correlation to address questions on how genetic effects are shared across ancestries. We find significant genetic heterogeneity between ancestries for cholesterol traits. Furthermore, we demonstrate that single nucleotide polymorphisms (SNPs) with concordant effects across ancestries for cholesterol are more frequently found in regulatory regions compared to other genomic regions. Indeed, the positive genetic covariance between ancestries is mostly driven by the effects of the concordant SNPs, whereas the genetic heterogeneity is attributed to the discordant SNPs. We also show that the predictive ability of the concordant SNPs is significantly higher than the discordant SNPs in the cross-ancestry polygenic prediction. The list of concordant SNPs for cholesterol is available in GWAS Catalog. These findings have relevance for the understanding of shared genetic architecture across ancestries, contributing to the development of clinical strategies for polygenic prediction of cholesterol in cross-ancestral settings.

Host genetic determinants of COVID-19 susceptibility and severity: A systematic review and meta-analysis.

Genome-wide association studies (GWASs) have identified single nucleotide polymorphisms (SNPs) associated with susceptibility and severity of coronavirus disease 2019 (COVID-19). However, identified SNPs are inconsistent across studies, and there is no compelling consensus that COVID-19 status is determined by genetic factors. Here, we conducted a systematic review and meta-analysis to determine the effect of genetic factors on COVID-19. A random-effect meta-analysis was performed to estimate pooled odds ratios (ORs) of SNP effects, and SNP-based heritability (SNP-h2 ) of COVID-19. The analyses were performed using meta-R package, and Stata version 17. The meta-analysis included a total of 96,817 COVID-19 cases and 6,414,916 negative controls. The meta-analysis showed that a cluster of highly correlated 9 SNPs (R2  > 0.9) at 3p21.31 gene locus covering LZTFL1 and SLC6A20 genes was significantly associated with COVID-19 severity, with a pooled OR of 1.8 [1.5-2.0]. Meanwhile, another 3 SNPs (rs2531743-G, rs2271616-T, and rs73062389-A) within the locus was associated with COVID-19 susceptibility, with pooled estimates of 0.95 [0.93-0.96], 1.23 [1.19-1.27] and 1.15 [1.13-1.17], respectively. Interestingly, SNPs associated with susceptibility and SNPs associated with severity in this locus are in linkage equilibrium (R2  < 0.026). The SNP-h2 on the liability scale for severity and susceptibility was estimated at 7.6% (Se = 3.2%) and 4.6% (Se = 1.5%), respectively. Genetic factors contribute to COVID-19 susceptibility and severity. In the 3p21.31 locus, SNPs that are associated with susceptibility are not in linkage disequilibrium (LD) with SNPs that are associated with severity, indicating within-locus heterogeneity.

Urinary neopterin: A novel biomarker of disease progression in amyotrophic lateral sclerosis.

BACKGROUND AND PURPOSE: The aim was to evaluate urinary neopterin, a marker of pro-inflammatory state, as a potential biomarker of disease prognosis and progression in amyotrophic lateral sclerosis (ALS); and to compare its utility to urinary neurotrophin receptor p75 extracellular domain (p75ECD ). METHODS: This was an observational study including 21 healthy controls and 46 people with ALS, 29 of whom were sampled longitudinally. Neopterin and p75ECD were measured using enzyme-linked immunoassays. Baseline and longitudinal changes in clinical measures, neopterin and urinary p75ECD were examined, and prognostic utility was explored by survival analysis. RESULTS: At baseline, urinary neopterin was higher in ALS compared to controls (181.7 ± 78.9 µmol/mol creatinine vs. 120.4 ± 60.8 µmol/mol creatinine, p = 0.002, Welch's t test) and correlated with the Revised ALS Functional Rating Scale (r = -0.36, p = 0.01). Combining previously published urinary p75ECD results from 22 ALS patients with a further 24 ALS patients, baseline urinary p75ECD was also higher compared to healthy controls (6.0 ± 2.7 vs. 3.2 ± 1.0 ng/mg creatinine, p < 0.0001) and correlated with the Revised ALS Functional Rating Scale (r = -0.36, p = 0.01). Urinary neopterin and p75ECD correlated with each other at baseline (r = 0.38, p = 0.009). In longitudinal analysis, urinary neopterin increased on average (±SE) by 6.8 ± 1.1 µmol/mol creatinine per month (p < 0.0001) and p75ECD by 0.19 ± 0.02 ng/mg creatinine per month (p < 0.0001) from diagnosis in 29 ALS patients. CONCLUSION: Urinary neopterin holds promise as marker of disease progression in ALS and is worthy of future evaluation for its potential to predict response to anti-inflammatory therapies.

Associations of genetically determined iron status across the phenome: A mendelian randomization study.

BACKGROUND: Iron is integral to many physiological processes, and variations in its levels, even within the normal range, can have implications for health. The objective of this study was to explore the broad clinical effects of varying iron status. METHODS AND FINDINGS: Genome-wide association study (GWAS) summary data obtained from 48,972 European individuals (55% female) across 19 cohorts in the Genetics of Iron Status Consortium were used to identify 3 genetic variants (rs1800562 and rs1799945 in the hemochromatosis gene [HFE] and rs855791 in the transmembrane protease serine 6 gene [TMPRSS6]) that associate with increased serum iron, ferritin, and transferrin saturation and decreased transferrin levels, thus serving as instruments for systemic iron status. Phenome-wide association study (PheWAS) of these instruments was performed on 424,439 European individuals (54% female) in the UK Biobank who were aged 40-69 years when recruited from 2006 to 2010, with their genetic data linked to Hospital Episode Statistics (HES) from April, 1995 to March, 2016. Two-sample summary data mendelian randomization (MR) analysis was performed to investigate the effect of varying iron status on outcomes across the human phenome. MR-PheWAS analysis for the 3 iron status genetic instruments was performed separately and then pooled by meta-analysis. Correction was made for testing of multiple correlated phenotypes using a 5% false discovery rate (FDR) threshold. Heterogeneity between MR estimates for different instruments was used to indicate possible bias due to effects of the genetic variants through pathways unrelated to iron status. There were 904 distinct phenotypes included in the MR-PheWAS analyses. After correcting for multiple testing, the 3 genetic instruments for systemic iron status demonstrated consistent evidence of a causal effect of higher iron status on decreasing risk of traits related to anemia (iron deficiency anemia: odds ratio [OR] scaled to a standard deviation [SD] increase in genetically determined serum iron levels 0.72, 95% confidence interval [CI] 0.64-0.81, P = 4 × 10-8) and hypercholesterolemia (hypercholesterolemia: OR 0.88, 95% CI 0.83-0.93, P = 2 × 10-5) and increasing risk of traits related to infection of the skin and related structures (cellulitis and abscess of the leg: OR 1.25, 95% CI 1.10-1.42, P = 6 × 10-4). The main limitations of this study relate to possible bias from pleiotropic effects of the considered genetic variants and misclassification of diagnoses in the HES data. Furthermore, this work only investigated participants with European ancestry, and the findings may not be applicable to other ethnic groups. CONCLUSIONS: Our findings offer novel, to our knowledge, insight into previously unreported effects of iron status, highlighting a potential protective effect of higher iron status on hypercholesterolemia and a detrimental role on risk of skin and skin structure infections. Given the modifiable and variable nature of iron status, these findings warrant further investigation.

Identification of novel loci affecting circulating chromogranins and related peptides.

Chromogranins are pro-hormone secretory proteins released from neuroendocrine cells, with effects on control of blood pressure. We conducted a genome-wide association study for plasma catestatin, the catecholamine release inhibitory peptide derived from chromogranin A (CHGA), and other CHGA- or chromogranin B (CHGB)-related peptides, in 545 US and 1252 Australian subjects. This identified loci on chromosomes 4q35 and 5q34 affecting catestatin concentration (P = 3.40 × 10-30 for rs4253311 and 1.85 × 10-19 for rs2731672, respectively). Genes in these regions include the proteolytic enzymes kallikrein (KLKB1) and Factor XII (F12). In chromaffin cells, CHGA and KLKB1 proteins co-localized in catecholamine storage granules. In vitro, kallikrein cleaved recombinant human CHGA to catestatin, verified by mass spectrometry. The peptide identified from this digestion (CHGA360-373) selectively inhibited nicotinic cholinergic stimulated catecholamine release from chromaffin cells. A proteolytic cascade involving kallikrein and Factor XII cleaves chromogranins to active compounds both in vivo and in vitro.

Serum iron level and kidney function: a Mendelian randomization study.

Background: Iron depletion is a known consequence of chronic kidney disease (CKD), but there is contradicting epidemiological evidence on whether iron itself affects kidney function and whether its effect is protective or detrimental in the general population. While epidemiological studies tend to be affected by confounding and reverse causation, Mendelian randomization (MR) can provide unconfounded estimates of causal effects by using genes as instruments. Methods: We performed an MR study of the effect of serum iron levels on estimated glomerular filtration rate (eGFR), using genetic variants known to be associated with iron. MR estimates of the effect of iron on eGFR were derived based on the association of each variant with iron and eGFR from two large genome-wide meta-analyses on 48 978 and 74 354 individuals. We performed a similar MR analysis for ferritin, which measures iron stored in the body, using variants associated with ferritin. Results: A combined MR estimate across all variants showed a 1.3% increase in eGFR per standard deviation increase in iron (95% confidence interval 0.4­2.1%; P = 0.004). The results for ferritin were consistent with those for iron. Secondary MR analyses of the effects of iron and ferritin on CKD did not show significant associations but had very low statistical power. Conclusions: Our study suggests a protective effect of iron on kidney function in the general population. Further research is required to confirm this causal association, investigate it in study populations at higher risk of CKD and explore its underlying mechanism of action.

Novel approach identifies SNPs in SLC2A10 and KCNK9 with evidence for parent-of-origin effect on body mass index.

The phenotypic effect of some single nucleotide polymorphisms (SNPs) depends on their parental origin. We present a novel approach to detect parent-of-origin effects (POEs) in genome-wide genotype data of unrelated individuals. The method exploits increased phenotypic variance in the heterozygous genotype group relative to the homozygous groups. We applied the method to >56,000 unrelated individuals to search for POEs influencing body mass index (BMI). Six lead SNPs were carried forward for replication in five family-based studies (of ∼4,000 trios). Two SNPs replicated: the paternal rs2471083-C allele (located near the imprinted KCNK9 gene) and the paternal rs3091869-T allele (located near the SLC2A10 gene) increased BMI equally (beta = 0.11 (SD), P<0.0027) compared to the respective maternal alleles. Real-time PCR experiments of lymphoblastoid cell lines from the CEPH families showed that expression of both genes was dependent on parental origin of the SNPs alleles (P<0.01). Our scheme opens new opportunities to exploit GWAS data of unrelated individuals to identify POEs and demonstrates that they play an important role in adult obesity.

Common genetic variants associated with cognitive performance identified using the proxy-phenotype method.

We identify common genetic variants associated with cognitive performance using a two-stage approach, which we call the proxy-phenotype method. First, we conduct a genome-wide association study of educational attainment in a large sample (n = 106,736), which produces a set of 69 education-associated SNPs. Second, using independent samples (n = 24,189), we measure the association of these education-associated SNPs with cognitive performance. Three SNPs (rs1487441, rs7923609, and rs2721173) are significantly associated with cognitive performance after correction for multiple hypothesis testing. In an independent sample of older Americans (n = 8,652), we also show that a polygenic score derived from the education-associated SNPs is associated with memory and absence of dementia. Convergent evidence from a set of bioinformatics analyses implicates four specific genes (KNCMA1, NRXN1, POU2F3, and SCRT). All of these genes are associated with a particular neurotransmitter pathway involved in synaptic plasticity, the main cellular mechanism for learning and memory.

Iron and hepcidin as risk factors in atherosclerosis: what do the genes say?

BACKGROUND: Previous reports suggested a role for iron and hepcidin in atherosclerosis. Here, we evaluated the causality of these associations from a genetic perspective via (i) a Mendelian randomization (MR) approach, (ii) study of association of atherosclerosis-related single nucleotide polymorphisms (SNPs) with iron and hepcidin, and (iii) estimation of genomic correlations between hepcidin, iron and atherosclerosis. RESULTS: Analyses were performed in a general population sample. Iron parameters (serum iron, serum ferritin, total iron-binding capacity and transferrin saturation), serum hepcidin and genome-wide SNP data were available for N = 1,819; non-invasive measurements of atherosclerosis (NIMA), i.e., presence of plaque, intima media thickness and ankle-brachial index (ABI), for N = 549. For the MR, we used 12 iron-related SNPs that were previously identified in a genome-wide association meta-analysis on iron status, and assessed associations of individual SNPs and quartiles of a multi-SNP score with NIMA. Quartile 4 versus quartile 1 of the multi-SNP score showed directionally consistent associations with the hypothesized direction of effect for all NIMA in women, indicating that increased body iron status is a risk factor for atherosclerosis in women. We observed no single SNP associations that fit the hypothesized directions of effect between iron and NIMA, except for rs651007, associated with decreased ferritin concentration and decreased atherosclerosis risk. Two of six NIMA-related SNPs showed association with the ratio hepcidin/ferritin, suggesting that an increased hepcidin/ferritin ratio increases atherosclerosis risk. Genomic correlations were close to zero, except for hepcidin and ferritin with ABI at rest [-0.27 (SE 0.34) and -0.22 (SE 0.35), respectively] and ABI after exercise [-0.29 (SE 0.34) and -0.30 (0.35), respectively]. The negative sign indicates an increased atherosclerosis risk with increased hepcidin and ferritin concentrations. CONCLUSIONS: Our results suggest a potential causal role for hepcidin and ferritin in atherosclerosis, and may indicate that iron status is causally related to atherosclerosis in women.

Sharing a Placenta is Associated With a Greater Similarity in DNA Methylation in Monochorionic Versus Dichorionic Twin Pars in Blood at Age 14.

Monozygotic (MZ) twins provide a natural system for investigating developmental plasticity and the potential epigenetic origins of disease. A major difference in the intrauterine environment between MZ pairs is whether they share a common placenta or have separate placentas. Using DNA methylation measured at >400,000 points in the genome on the Illumina HumanMethylation450 array, we demonstrate that the co-twins of MZ pairs (average age of 14) that shared a common placenta (n = 18 pairs) have more similar DNA methylation levels in blood throughout the genome relative to those with separate placentas (n = 16 pairs). Functional annotation of the genomic regions that show significantly different correlation between monochorionic (MC) and dichorionic (DC) MZ pairs found an over-representation of genes involved in the regulation of transcription, neuronal development, and cellular differentiation. These results support the idea that prenatal environmental exposures may have a lasting effect on an individual's epigenetic landscape, and the potential for these changes to have functional consequences.

Loci affecting gamma-glutamyl transferase in adults and adolescents show age × SNP interaction and cardiometabolic disease associations.

Serum gamma-glutamyl transferase (GGT) activity is a marker of liver disease which is also prospectively associated with the risk of all-cause mortality, cardiovascular disease, type 2 diabetes and cancers. We have discovered novel loci affecting GGT in a genome-wide association study (rs1497406 in an intergenic region of chromosome 1, P = 3.9 × 10(-8); rs944002 in C14orf73 on chromosome 14, P = 4.7 × 10(-13); rs340005 in RORA on chromosome 15, P = 2.4 × 10(-8)), and a highly significant heterogeneity between adult and adolescent results at the GGT1 locus on chromosome 22 (maximum P(HET) = 5.6 × 10(-12) at rs6519520). Pathway analysis of significant and suggestive single-nucleotide polymorphism associations showed significant overlap between genes affecting GGT and those affecting common metabolic and inflammatory diseases, and identified the hepatic nuclear factor (HNF) family as controllers of a network of genes affecting GGT. Our results reinforce the disease associations of GGT and demonstrate that control by the GGT1 locus varies with age.

A Metabolome-Wide Mendelian Randomization Study Identifies Dysregulated Arachidonic Acid Synthesis as a Potential Causal Risk Factor for Bipolar Disorder.

BACKGROUND: Bipolar disorder (BPD) is a debilitating mood disorder with an unclear etiology. A better understanding of the underlying pathophysiological mechanisms will help to identify novel targets for improved treatment options and prevention strategies. In this metabolome-wide Mendelian randomization study, we screened for metabolites that may have a causal role in BPD. METHODS: We tested a total of 913 circulating metabolite exposures assessed in 14,296 Europeans using a mass spectrometry-based platform. For the BPD outcome, we used summary data from the largest and most recent genome-wide association study reported to date, including 41,917 BPD cases. RESULTS: We identified 33 metabolites associated with BPD (padjusted < 5.48 × 10-5). Most of them were lipids, including arachidonic acid (ß = -0.154, SE = 0.023, p = 3.30 × 10-11), a polyunsaturated omega-6 fatty acid, along with several complex lipids containing either an arachidonic or a linoleic fatty acid side chain. These associations did not extend to other closely related psychiatric disorders like schizophrenia or depression, although they may be involved in the regulation of lithium response. These lipid associations were driven by genetic variants within the FADS1/2/3 gene cluster, which is a robust BPD risk locus encoding a family of fatty acid desaturase enzymes that are responsible for catalyzing the conversion of linoleic acid into arachidonic acid. Statistical colocalization analyses indicated that 27 of the 33 metabolites shared the same genetic etiology with BPD at the FADS1/2/3 cluster, demonstrating that our findings are not confounded by linkage disequilibrium. CONCLUSIONS: Overall, our findings support the notion that arachidonic acid and other polyunsaturated fatty acids may represent potential targets for BPD.

In-silico functional analyses identify TMPRSS15-mediated intestinal absorption of lithium as a modulator of lithium response in bipolar disorder.

BACKGROUND: The therapeutic response to lithium in patients with bipolar disorder is highly variable and has a polygenic basis. Genome-wide association studies investigating lithium response have identified several relevant loci, though the precise mechanisms driving these associations are poorly understood. We aimed to prioritise the most likely effector gene and determine the mechanisms underlying an intergenic lithium response locus on chromosome 21 identified by the International Consortium on Lithium Genetics (ConLi+Gen). METHODS: We conducted in-silico functional analyses by integrating and synthesising information from several publicly available functional genetic datasets and databases including the Genotype-Tissue Expression (GTEx) project and HaploReg. RESULTS: The findings from this study highlighted TMPRSS15 as the most likely effector gene at the ConLi+Gen lithium response locus. TMPRSS15 encodes enterokinase, a gastrointestinal enzyme responsible for converting trypsinogen into trypsin and thus aiding digestion. Convergent findings from gene-based lookups in human and mouse databases as well as co-expression network analyses of small intestinal RNA-seq data (GTEx) implicated TMPRSS15 in the regulation of intestinal nutrient absorption, including ions like sodium and potassium, which may extend to lithium. LIMITATIONS: Although the findings from this study indicated that TMPRSS15 was the most likely effector gene at the ConLi+Gen lithium response locus, the evidence was circumstantial. Thus, the conclusions from this study need to be validated in appropriately designed wet-lab studies. CONCLUSIONS: The findings from this study are consistent with a model whereby TMPRSS15 impacts the efficacy of lithium treatment in patients with bipolar disorder by modulating intestinal lithium absorption.

IDeRare: a lightweight and extensible open-source phenotype and exome analysis pipeline for germline rare disease diagnosis.

Objectives: Diagnosing rare diseases is an arduous and challenging process in clinical settings, resulting in the late discovery of novel variants and referral loops. To help clinicians, we built IDeRare pipelines to accelerate phenotype-genotype analysis for patients with suspected rare diseases. Materials and Methods: IDeRare pipeline is separated into phenotype and genotype parts. The phenotype utilizes our handmade Python library, while the genotype part utilizes command line (bash) and Python script to combine bioinformatics executable and Docker image. Results: We described various implementations of IDeRare phenotype and genotype parts with real-world clinical and exome data using IDeRare, accelerating the terminology conversion process and giving insight on the diagnostic pathway based on disease linkage analysis until exome analysis and HTML-based reporting for clinicians. Conclusion: IDeRare is freely available under the BSD-3 license, obtainable via GitHub. The portability of IDeRare pipeline could be easily implemented for semi-technical users and extensible for advanced users.

Development and validation of an intrinsic capacity score in the UK Biobank study.

BACKGROUND: In 2015, the World Health Organization introduced the concept of intrinsic capacity (IC) to define the individual-level characteristics that enable an older person to be and do the things they value. This study developed an intrinsic capacity score for UK Biobank study participants and validated its use as a tool for health outcome prediction, understanding healthy aging trajectories, and genetic research. METHODS: Our analysis included data from 45,208 UK biobank participants who had a complete record of the ten variables included in the analysis. Factor adequacy was tested using Kaiser-Meyer-Olkin, Barthelt's, and the determinant of matrix tests, and the number of factors was determined by the parallel analysis method. Exploratory and confirmatory factor analyses were employed to determine the structure and dimensionality of indicators. Finally, the intrinsic capacity score was generated, and its construct and predictive validities as well as reliability were assessed. RESULTS: The factor analysis identified a multidimensional construct comprising one general factor (intrinsic capacity) and five specific factors (locomotor, vitality, cognitive, psychological, and sensory). The bifactor structure showed a better fit (comparative fit index = 0.995, Tucker Lewis index = 0.976, root mean square error of approximation = 0.025, root mean square residual = 0.009) than the conventional five-factor structure. The intrinsic capacity score generated using the bifactor confirmatory factor analysis has good construct validity, as demonstrated by an inverse association with age (lower intrinsic capacity in older age; (ß) =-0.035 (95%CI: -0.036, -0.034)), frailty (lower intrinsic capacity score in prefrail participants, ß = -0.104 (95%CI: (-0.114, -0.094)) and frail participants, ß = -0.227 (95%CI: -0.267, -0.186) than robust participants), and comorbidity (a lower intrinsic capacity score associated with increased Charlson's comorbidity index, ß =-0.019 (95%CI: -0.022, -0.015)). The intrinsic capacity score also predicted comorbidity (a one-unit increase in baseline intrinsic capacity score led to a lower Charlson's comorbidity index, ß = 0.147 (95%CI: -0.173, -0.121)) and mortality (a one-unit increase in baseline intrinsic capacity score led to 25 % lower risk of death, odds ratio = 0.75(95%CI: 0.663, 0.848)). CONCLUSION: The bifactor structure showed a better fit in all goodness of fit tests. The intrinsic capacity construct has strong structural, construct, and predictive validities and is a promising tool for monitoring aging trajectories.

Serum iron levels and the risk of Parkinson disease: a Mendelian randomization study.

BACKGROUND: Although levels of iron are known to be increased in the brains of patients with Parkinson disease (PD), epidemiological evidence on a possible effect of iron blood levels on PD risk is inconclusive, with effects reported in opposite directions. Epidemiological studies suffer from problems of confounding and reverse causation, and mendelian randomization (MR) represents an alternative approach to provide unconfounded estimates of the effects of biomarkers on disease. We performed a MR study where genes known to modify iron levels were used as instruments to estimate the effect of iron on PD risk, based on estimates of the genetic effects on both iron and PD obtained from the largest sample meta-analyzed to date. METHODS AND FINDINGS: We used as instrumental variables three genetic variants influencing iron levels, HFE rs1800562, HFE rs1799945, and TMPRSS6 rs855791. Estimates of their effect on serum iron were based on a recent genome-wide meta-analysis of 21,567 individuals, while estimates of their effect on PD risk were obtained through meta-analysis of genome-wide and candidate gene studies with 20,809 PD cases and 88,892 controls. Separate MR estimates of the effect of iron on PD were obtained for each variant and pooled by meta-analysis. We investigated heterogeneity across the three estimates as an indication of possible pleiotropy and found no evidence of it. The combined MR estimate showed a statistically significant protective effect of iron, with a relative risk reduction for PD of 3% (95% CI 1%-6%; p = 0.001) per 10 µg/dl increase in serum iron. CONCLUSIONS: Our study suggests that increased iron levels are causally associated with a decreased risk of developing PD. Further studies are needed to understand the pathophysiological mechanism of action of serum iron on PD risk before recommendations can be made.

The role of adiposity in cardiometabolic traits: a Mendelian randomization analysis.

BACKGROUND: The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach. METHODS AND FINDINGS: We used the adiposity-associated variant rs9939609 at the FTO locus as an instrumental variable (IV) for body mass index (BMI) in a Mendelian randomization design. Thirty-six population-based studies of individuals of European descent contributed to the analyses. Age- and sex-adjusted regression models were fitted to test for association between (i) rs9939609 and BMI (n  =  198,502), (ii) rs9939609 and 24 traits, and (iii) BMI and 24 traits. The causal effect of BMI on the outcome measures was quantified by IV estimators. The estimators were compared to the BMI-trait associations derived from the same individuals. In the IV analysis, we demonstrated novel evidence for a causal relationship between adiposity and incident heart failure (hazard ratio, 1.19 per BMI-unit increase; 95% CI, 1.03-1.39) and replicated earlier reports of a causal association with type 2 diabetes, metabolic syndrome, dyslipidemia, and hypertension (odds ratio for IV estimator, 1.1-1.4; all p < 0.05). For quantitative traits, our results provide novel evidence for a causal effect of adiposity on the liver enzymes alanine aminotransferase and gamma-glutamyl transferase and confirm previous reports of a causal effect of adiposity on systolic and diastolic blood pressure, fasting insulin, 2-h post-load glucose from the oral glucose tolerance test, C-reactive protein, triglycerides, and high-density lipoprotein cholesterol levels (all p < 0.05). The estimated causal effects were in agreement with traditional observational measures in all instances except for type 2 diabetes, where the causal estimate was larger than the observational estimate (p  =  0.001). CONCLUSIONS: We provide novel evidence for a causal relationship between adiposity and heart failure as well as between adiposity and increased liver enzymes.

Genome-wide association study identifies two loci strongly affecting transferrin glycosylation.

Polysaccharide sidechains attached to proteins play important roles in cell-cell and receptor-ligand interactions. Variation in the carbohydrate component has been extensively studied for the iron transport protein transferrin, because serum levels of the transferrin isoforms asialotransferrin + disialotransferrin (carbohydrate-deficient transferrin, CDT) are used as biomarkers of excessive alcohol intake. We conducted a genome-wide association study to assess whether genetic factors affect CDT concentration in serum. CDT was measured in three population-based studies: one in Switzerland (CoLaus study, n = 5181) and two in Australia (n = 1509, n = 775). The first cohort was used as the discovery panel and the latter ones served as replication. Genome-wide single-nucleotide polymorphism (SNP) typing data were used to identify loci with significant associations with CDT as a percentage of total transferrin (CDT%). The top three SNPs in the discovery panel (rs2749097 near PGM1 on chromosome 1, and missense polymorphisms rs1049296, rs1799899 in TF on chromosome 3) were successfully replicated , yielding genome-wide significant combined association with CDT% (P = 1.9 × 10(-9), 4 × 10(-39), 5.5 × 10(-43), respectively) and explain 5.8% of the variation in CDT%. These allelic effects are postulated to be caused by variation in availability of glucose-1-phosphate as a precursor of the glycan (PGM1), and variation in transferrin (TF) structure.