Publications by authors named "Zoltán Kutalik"

212 Publications

Simultaneous estimation of bi-directional causal effects and heritable confounding from GWAS summary statistics.

Nat Commun 2021 12 14;12(1):7274. Epub 2021 Dec 14.

University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland.

Mendelian Randomisation (MR) is an increasingly popular approach that estimates the causal effect of risk factors on complex human traits. While it has seen several extensions that relax its basic assumptions, most suffer from two major limitations; their under-exploitation of genome-wide markers, and sensitivity to the presence of a heritable confounder of the exposure-outcome relationship. To overcome these limitations, we propose a Latent Heritable Confounder MR (LHC-MR) method applicable to association summary statistics, which estimates bi-directional causal effects, direct heritabilities, and confounder effects while accounting for sample overlap. We demonstrate that LHC-MR outperforms several existing MR methods in a wide range of simulation settings and apply it to summary statistics of 13 complex traits. Besides several concordant results with other MR methods, LHC-MR unravels new mechanisms (how disease diagnosis might lead to improved lifestyle) and reveals new causal effects (e.g. HDL cholesterol being protective against high systolic blood pressure), hidden from standard MR methods due to a heritable confounder of opposite effect direction.
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http://dx.doi.org/10.1038/s41467-021-26970-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8671515PMC
December 2021

The power of genetic diversity in genome-wide association studies of lipids.

Nature 2021 Dec 9;600(7890):675-679. Epub 2021 Dec 9.

Department of Clinical Biochemistry, Landspitali-National University Hospital of Iceland, Reykjavik, Iceland.

Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels, heart disease remains the leading cause of death worldwide. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine, we anticipate that increased diversity of participants will lead to more accurate and equitable application of polygenic scores in clinical practice.
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http://dx.doi.org/10.1038/s41586-021-04064-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8730582PMC
December 2021

Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits.

Nat Commun 2021 11 30;12(1):6972. Epub 2021 Nov 30.

Institute of Science and Technology Austria, Klosterneuburg, Austria.

We develop a Bayesian model (BayesRR-RC) that provides robust SNP-heritability estimation, an alternative to marker discovery, and accurate genomic prediction, taking 22 seconds per iteration to estimate 8.4 million SNP-effects and 78 SNP-heritability parameters in the UK Biobank. We find that only ≤10% of the genetic variation captured for height, body mass index, cardiovascular disease, and type 2 diabetes is attributable to proximal regulatory regions within 10kb upstream of genes, while 12-25% is attributed to coding regions, 32-44% to introns, and 22-28% to distal 10-500kb upstream regions. Up to 24% of all cis and coding regions of each chromosome are associated with each trait, with over 3,100 independent exonic and intronic regions and over 5,400 independent regulatory regions having ≥95% probability of contributing ≥0.001% to the genetic variance of these four traits. Our open-source software (GMRM) provides a scalable alternative to current approaches for biobank data.
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http://dx.doi.org/10.1038/s41467-021-27258-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8633298PMC
November 2021

Untargeted Metabolome- and Transcriptome-Wide Association Study Suggests Causal Genes Modulating Metabolite Concentrations in Urine.

J Proteome Res 2021 Nov 26;20(11):5103-5114. Epub 2021 Oct 26.

Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland.

Gene products can affect the concentrations of small molecules (aka "metabolites"), and conversely, some metabolites can modulate the concentrations of gene transcripts. While many specific instances of this interplay have been revealed, a global approach to systematically uncover human gene-metabolite interactions is still lacking. We performed a metabolome- and transcriptome-wide association study to identify genes influencing the human metabolome using untargeted metabolome features, extracted from H nuclear magnetic resonance spectroscopy (NMR) of urine samples, and gene expression levels, quantified from RNA-Seq of lymphoblastoid cell lines (LCL) from 555 healthy individuals. We identified 20 study-wide significant associations corresponding to 15 genes, of which 5 associations (with 2 genes) were confirmed with follow-up NMR data. Using metabomatching, we identified the metabolites corresponding to metabolome features associated with the genes, namely, N-acetylated compounds with and trimethylamine (TMA) with . Finally, Mendelian randomization analysis supported a potential causal link between the expression of genes in both the - and -loci and their associated metabolite concentrations. In the case of , we additionally observed that TMA concentration likely exhibits a reverse causal effect on expression levels, indicating a negative feedback loop. Our study highlights how the integration of metabolomics, gene expression, and genetic data can pinpoint causal genes modulating metabolite concentrations.
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http://dx.doi.org/10.1021/acs.jproteome.1c00585DOI Listing
November 2021

Mendelian randomization to assess causality between uromodulin, blood pressure and chronic kidney disease.

Kidney Int 2021 12 9;100(6):1282-1291. Epub 2021 Oct 9.

Mechanisms of Inherited Kidney Disorders Group, Institute of Physiology, University of Zurich, Zürich, Switzerland. Electronic address:

UMOD variants associated with higher levels of urinary uromodulin (uUMOD) increase the risk of chronic kidney disease (CKD) and hypertension. However, uUMOD levels also reflect functional kidney tubular mass in observational studies, questioning the causal link between uromodulin production and kidney damage. We used Mendelian randomization to clarify causality between uUMOD levels, kidney function and blood pressure in individuals of European descent. The link between uUMOD and estimated glomerular filtration rate (eGFR) was first investigated in a population-based cohort of 3851 individuals. In observational data, higher uUMOD associated with higher eGFR. Conversely, when using rs12917707 (an UMOD polymorphism) as an instrumental variable in one-sample Mendelian randomization, higher uUMOD strongly associated with eGFR decline. We next applied two-sample Mendelian randomization on four genome wide association study consortia to explore causal links between uUMOD and eGFR, CKD risk (567,460 individuals) and blood pressure (757,461 individuals). Higher uUMOD levels significantly associated with lower eGFR, higher odds for eGFR decline or CKD, and higher systolic or diastolic blood pressure. Each one standard deviation (SD) increase of uUMOD decreased log-transformed eGFR by -0.15 SD (95% confidence interval -0.17 to -0.13) and increased log-odds CKD by 0.13 SD (0.12 to 0.15). One SD increase of uUMOD increased systolic blood pressure by 0.06 SD (0.03 to 0.09) and diastolic blood pressure by 0.08 SD (0.05 to 0.12). The effect of uUMOD on blood pressure was mediated by eGFR, whereas the effect on eGFR was not mediated by blood pressure. Thus, our data support that genetically driven levels of uromodulin have a direct, causal and adverse effect on kidney function outcome in the general population, not mediated by blood pressure.
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http://dx.doi.org/10.1016/j.kint.2021.08.032DOI Listing
December 2021

Differentially expressed genes reflect disease-induced rather than disease-causing changes in the transcriptome.

Nat Commun 2021 09 24;12(1):5647. Epub 2021 Sep 24.

Swiss Institute of Bioinformatics, Lausanne, Switzerland.

Comparing transcript levels between healthy and diseased individuals allows the identification of differentially expressed genes, which may be causes, consequences or mere correlates of the disease under scrutiny. We propose a method to decompose the observational correlation between gene expression and phenotypes driven by confounders, forward- and reverse causal effects. The bi-directional causal effects between gene expression and complex traits are obtained by Mendelian Randomization integrating summary-level data from GWAS and whole-blood eQTLs. Applying this approach to complex traits reveals that forward effects have negligible contribution. For example, BMI- and triglycerides-gene expression correlation coefficients robustly correlate with trait-to-expression causal effects (r= 0.11, P= 2.0 × 10 and r= 0.13, P= 1.1 × 10), but not detectably with expression-to-trait effects. Our results demonstrate that studies comparing the transcriptome of diseased and healthy subjects are more prone to reveal disease-induced gene expression changes rather than disease causing ones.
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http://dx.doi.org/10.1038/s41467-021-25805-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8463674PMC
September 2021

Composite trait Mendelian randomization reveals distinct metabolic and lifestyle consequences of differences in body shape.

Commun Biol 2021 09 13;4(1):1064. Epub 2021 Sep 13.

University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland.

Obesity is a major risk factor for a wide range of cardiometabolic diseases, however the impact of specific aspects of body morphology remains poorly understood. We combined the GWAS summary statistics of fourteen anthropometric traits from UK Biobank through principal component analysis to reveal four major independent axes: body size, adiposity, predisposition to abdominal fat deposition, and lean mass. Mendelian randomization analysis showed that although body size and adiposity both contribute to the consequences of BMI, many of their effects are distinct, such as body size increasing the risk of cardiac arrhythmia (b = 0.06, p = 4.2 ∗ 10) while adiposity instead increased that of ischemic heart disease (b = 0.079, p = 8.2 ∗ 10). The body mass-neutral component predisposing to abdominal fat deposition, likely reflecting a shift from subcutaneous to visceral fat, exhibited health effects that were weaker but specifically linked to lipotoxicity, such as ischemic heart disease (b = 0.067, p = 9.4 ∗ 10) and diabetes (b = 0.082, p = 5.9 ∗ 10). Combining their independent predicted effects significantly improved the prediction of obesity-related diseases (p < 10). The presented decomposition approach sheds light on the biological mechanisms underlying the heterogeneity of body morphology and its consequences on health and lifestyle.
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http://dx.doi.org/10.1038/s42003-021-02550-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8438050PMC
September 2021

Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression.

Nat Genet 2021 09 2;53(9):1300-1310. Epub 2021 Sep 2.

Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland.

Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.
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http://dx.doi.org/10.1038/s41588-021-00913-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8432599PMC
September 2021

Genetic insights into biological mechanisms governing human ovarian ageing.

Nature 2021 08 4;596(7872):393-397. Epub 2021 Aug 4.

Genome Integrity and Instability Group, Institut de Biotecnologia i Biomedicina, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain.

Reproductive longevity is essential for fertility and influences healthy ageing in women, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.
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http://dx.doi.org/10.1038/s41586-021-03779-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7611832PMC
August 2021

Socio-economic position as a moderator of cardiometabolic outcomes in patients receiving psychotropic treatment associated with weight gain: results from a prospective 12-month inception cohort study and a large population-based cohort.

Transl Psychiatry 2021 06 26;11(1):360. Epub 2021 Jun 26.

Unit of Pharmacogenetics and Clinical Psychopharmacology, Center for Psychiatric Neuroscience, Department of Psychiatry, Lausanne University Hospital, University of Lausanne, Prilly, Switzerland.

Weight gain and metabolic complications are major adverse effects of many psychotropic drugs. We aimed to understand how socio-economic status (SES), defined as the Swiss socio-economic position (SSEP), is associated with cardiometabolic parameters after initiation of psychotropic medications known to induce weight gain. Cardiometabolic parameters were collected in two Swiss cohorts following the prescription of psychotropic medications. The SSEP integrated neighborhood-based income, education, occupation, and housing condition. The results were then validated in an independent replication sample (UKBiobank), using educational attainment (EA) as a proxy for SES. Adult patients with a low SSEP had a higher risk of developing metabolic syndrome over one year versus patients with a high SSEP (Hazard ratio (95% CI) = 3.1 (1.5-6.5), n = 366). During the first 6 months of follow-up, a significant negative association between SSEP and body mass index (BMI), weight change, and waist circumference change was observed (25 ≤ age < 65, n = 526), which was particularly important in adults receiving medications with the highest risk of weight gain, with a BMI difference of 0.86 kg/m between patients with low versus high SSEP (95% CI: 0.03-1.70, n = 99). Eventually, a causal effect of EA on BMI was revealed using Mendelian randomization in the UKBiobank, which was notably strong in high-risk medication users (beta: -0.47 SD EA per 1 SD BMI; 95% CI: -0.46 to -0.27, n = 11,314). An additional aspect of personalized medicine was highlighted, suggesting the patients' SES represents a significant risk factor. Particular attention should be paid to patients with low SES when initiating high cardiometabolic risk psychotropic medications.
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http://dx.doi.org/10.1038/s41398-021-01482-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8257637PMC
June 2021

HSD17B7 gene in self-renewal and oncogenicity of keratinocytes from Black versus White populations.

EMBO Mol Med 2021 07 29;13(7):e14133. Epub 2021 Jun 29.

Department of Biochemistry, University of Lausanne, Epalinges, Switzerland.

Human populations of Black African ancestry have a relatively high risk of aggressive cancer types, including keratinocyte-derived squamous cell carcinomas (SCCs). We show that primary keratinocytes (HKCs) from Black African (Black) versus White Caucasian (White) individuals have on average higher oncogenic and self-renewal potential, which are inversely related to mitochondrial electron transfer chain activity and ATP and ROS production. HSD17B7 is the top-ranked differentially expressed gene in HKCs and Head/Neck SCCs from individuals of Black African versus Caucasian ancestries, with several ancestry-specific eQTLs linked to its expression. Mirroring the differences between Black and White HKCs, modulation of the gene, coding for an enzyme involved in sex steroid and cholesterol biosynthesis, determines HKC and SCC cell proliferation and oncogenicity as well as mitochondrial OXPHOS activity. Overall, the findings point to a targetable determinant of cancer susceptibility among different human populations, amenable to prevention and management of the disease.
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http://dx.doi.org/10.15252/emmm.202114133DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8261506PMC
July 2021

The trans-ancestral genomic architecture of glycemic traits.

Nat Genet 2021 06 31;53(6):840-860. Epub 2021 May 31.

Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.
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http://dx.doi.org/10.1038/s41588-021-00852-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610958PMC
June 2021

Genomic architecture and prediction of censored time-to-event phenotypes with a Bayesian genome-wide analysis.

Nat Commun 2021 04 20;12(1):2337. Epub 2021 Apr 20.

Institute of Science and Technology Austria, Klosterneuburg, Austria.

While recent advancements in computation and modelling have improved the analysis of complex traits, our understanding of the genetic basis of the time at symptom onset remains limited. Here, we develop a Bayesian approach (BayesW) that provides probabilistic inference of the genetic architecture of age-at-onset phenotypes in a sampling scheme that facilitates biobank-scale time-to-event analyses. We show in extensive simulation work the benefits BayesW provides in terms of number of discoveries, model performance and genomic prediction. In the UK Biobank, we find many thousands of common genomic regions underlying the age-at-onset of high blood pressure (HBP), cardiac disease (CAD), and type-2 diabetes (T2D), and for the genetic basis of onset reflecting the underlying genetic liability to disease. Age-at-menopause and age-at-menarche are also highly polygenic, but with higher variance contributed by low frequency variants. Genomic prediction into the Estonian Biobank data shows that BayesW gives higher prediction accuracy than other approaches.
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http://dx.doi.org/10.1038/s41467-021-22538-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8058085PMC
April 2021

Triangulating evidence from longitudinal and Mendelian randomization studies of metabolomic biomarkers for type 2 diabetes.

Sci Rep 2021 03 18;11(1):6197. Epub 2021 Mar 18.

Swiss Institute of Bioinformatics, Lausanne, Switzerland.

The number of people affected by Type 2 diabetes mellitus (T2DM) is close to half a billion and is on a sharp rise, representing a major and growing public health burden. Given its mild initial symptoms, T2DM is often diagnosed several years after its onset, leaving half of diabetic individuals undiagnosed. While several classical clinical and genetic biomarkers have been identified, improving early diagnosis by exploring other kinds of omics data remains crucial. In this study, we have combined longitudinal data from two population-based cohorts CoLaus and DESIR (comprising in total 493 incident cases vs. 1360 controls) to identify new or confirm previously implicated metabolomic biomarkers predicting T2DM incidence more than 5 years ahead of clinical diagnosis. Our longitudinal data have shown robust evidence for valine, leucine, carnitine and glutamic acid being predictive of future conversion to T2DM. We confirmed the causality of such association for leucine by 2-sample Mendelian randomisation (MR) based on independent data. Our MR approach further identified new metabolites potentially playing a causal role on T2D, including betaine, lysine and mannose. Interestingly, for valine and leucine a strong reverse causal effect was detected, indicating that the genetic predisposition to T2DM may trigger early changes of these metabolites, which appear well-before any clinical symptoms. In addition, our study revealed a reverse causal effect of metabolites such as glutamic acid and alanine. Collectively, these findings indicate that molecular traits linked to the genetic basis of T2DM may be particularly promising early biomarkers.
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http://dx.doi.org/10.1038/s41598-021-85684-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7973501PMC
March 2021

Gene regulation contributes to explain the impact of early life socioeconomic disadvantage on adult inflammatory levels in two cohort studies.

Sci Rep 2021 02 4;11(1):3100. Epub 2021 Feb 4.

Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland.

Individuals experiencing socioeconomic disadvantage in childhood have a higher rate of inflammation-related diseases decades later. Little is known about the mechanisms linking early life experiences to the functioning of the immune system in adulthood. To address this, we explore the relationship across social-to-biological layers of early life social exposures on levels of adulthood inflammation and the mediating role of gene regulatory mechanisms, epigenetic and transcriptomic profiling from blood, in 2,329 individuals from two European cohort studies. Consistently across both studies, we find transcriptional activity explains a substantive proportion (78% and 26%) of the estimated effect of early life disadvantaged social exposures on levels of adulthood inflammation. Furthermore, we show that mechanisms other than cis DNA methylation may regulate those transcriptional fingerprints. These results further our understanding of social-to-biological transitions by pinpointing the role of gene regulation that cannot fully be explained by differential cis DNA methylation.
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http://dx.doi.org/10.1038/s41598-021-82714-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7862626PMC
February 2021

Obesity and atypical depression symptoms: findings from Mendelian randomization in two European cohorts.

Transl Psychiatry 2021 02 4;11(1):96. Epub 2021 Feb 4.

Institute of Primary Care and Public Health (Unisante), University of Lausanne, Lausanne, Switzerland.

Studies considering the causal role of body mass index (BMI) for the predisposition of major depressive disorder (MDD) based on a Mendelian Randomization (MR) approach have shown contradictory results. These inconsistent findings may be attributable to the heterogeneity of MDD; in fact, several studies have documented associations between BMI and mainly the atypical subtype of MDD. Using a MR approach, we investigated the potential causal role of obesity in both the atypical subtype and its five specific symptoms assessed according to the Statistical Manual of Mental Disorders (DSM), in two large European cohorts, CoLaus|PsyCoLaus (n = 3350, 1461 cases and 1889 controls) and NESDA|NTR (n = 4139, 1182 cases and 2957 controls). We first tested general obesity measured by BMI and then the body fat distribution measured by waist-to-hip ratio (WHR). Results suggested that BMI is potentially causally related to the symptom increase in appetite, for which inverse variance weighted, simple median and weighted median MR regression estimated slopes were 0.68 (SE = 0.23, p = 0.004), 0.77 (SE = 0.37, p = 0.036), and 1.11 (SE = 0.39, p = 0.004). No causal effect of BMI or WHR was found on the risk of the atypical subtype or for any of the other atypical symptoms. Our findings show that higher obesity is likely causal for the specific symptom of increase in appetite in depressed participants and reiterate the need to study depression at the granular level of its symptoms to further elucidate potential causal relationships and gain additional insight into its biological underpinnings.
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http://dx.doi.org/10.1038/s41398-021-01236-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7862438PMC
February 2021

Genome-wide association study of circulating interleukin 6 levels identifies novel loci.

Hum Mol Genet 2021 04;30(5):393-409

Institute of Cardiovascular Science, University College London, London WC1E 6BT, UK.

Interleukin 6 (IL-6) is a multifunctional cytokine with both pro- and anti-inflammatory properties with a heritability estimate of up to 61%. The circulating levels of IL-6 in blood have been associated with an increased risk of complex disease pathogenesis. We conducted a two-staged, discovery and replication meta genome-wide association study (GWAS) of circulating serum IL-6 levels comprising up to 67 428 (ndiscovery = 52 654 and nreplication = 14 774) individuals of European ancestry. The inverse variance fixed effects based discovery meta-analysis, followed by replication led to the identification of two independent loci, IL1F10/IL1RN rs6734238 on chromosome (Chr) 2q14, (Pcombined = 1.8 × 10-11), HLA-DRB1/DRB5 rs660895 on Chr6p21 (Pcombined = 1.5 × 10-10) in the combined meta-analyses of all samples. We also replicated the IL6R rs4537545 locus on Chr1q21 (Pcombined = 1.2 × 10-122). Our study identifies novel loci for circulating IL-6 levels uncovering new immunological and inflammatory pathways that may influence IL-6 pathobiology.
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http://dx.doi.org/10.1093/hmg/ddab023DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8098112PMC
April 2021

Genome-wide association study identifies 48 common genetic variants associated with handedness.

Nat Hum Behav 2021 01 28;5(1):59-70. Epub 2020 Sep 28.

Institute of Biological Psychiatry, Mental Health Services of Copenhagen, Copenhagen, Denmark.

Handedness has been extensively studied because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and the International Handedness Consortium, we conducted a genome-wide association meta-analysis of handedness (N = 1,766,671). We found 41 loci associated (P < 5 × 10) with left-handedness and 7 associated with ambidexterity. Tissue-enrichment analysis implicated the CNS in the aetiology of handedness. Pathways including regulation of microtubules and brain morphology were also highlighted. We found suggestive positive genetic correlations between left-handedness and neuropsychiatric traits, including schizophrenia and bipolar disorder. Furthermore, the genetic correlation between left-handedness and ambidexterity is low (r = 0.26), which implies that these traits are largely influenced by different genetic mechanisms. Our findings suggest that handedness is highly polygenic and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders.
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http://dx.doi.org/10.1038/s41562-020-00956-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7116623PMC
January 2021

Genetic Studies of Leptin Concentrations Implicate Leptin in the Regulation of Early Adiposity.

Diabetes 2020 12 11;69(12):2806-2818. Epub 2020 Sep 11.

Department of Biostatistics, Boston University School of Public Health, Boston, MA.

Leptin influences food intake by informing the brain about the status of body fat stores. Rare mutations associated with congenital leptin deficiency cause severe early-onset obesity that can be mitigated by administering leptin. However, the role of genetic regulation of leptin in polygenic obesity remains poorly understood. We performed an exome-based analysis in up to 57,232 individuals of diverse ancestries to identify genetic variants that influence adiposity-adjusted leptin concentrations. We identify five novel variants, including four missense variants, in , , , and , and one intergenic variant near The missense variant Val94Met (rs17151919) in was common in individuals of African ancestry only, and its association with lower leptin concentrations was specific to this ancestry ( = 2 × 10, = 3,901). Using in vitro analyses, we show that the Met94 allele decreases leptin secretion. We also show that the Met94 allele is associated with higher BMI in young African-ancestry children but not in adults, suggesting that leptin regulates early adiposity.
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http://dx.doi.org/10.2337/db20-0070DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7679778PMC
December 2020

Causal Inference Methods to Integrate Omics and Complex Traits.

Cold Spring Harb Perspect Med 2021 05 3;11(5). Epub 2021 May 3.

Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland.

Major biotechnological advances have facilitated a tremendous boost to the collection of (gen-/transcript-/prote-/methyl-/metabol-)omics data in very large sample sizes worldwide. Coordinated efforts have yielded a deluge of studies associating diseases with genetic markers (genome-wide association studies) or with molecular phenotypes. Whereas omics-disease associations have led to biologically meaningful and coherent mechanisms, the identified (non-germline) disease biomarkers may simply be correlates or consequences of the explored diseases. To move beyond this realm, Mendelian randomization provides a principled framework to integrate information on omics- and disease-associated genetic variants to pinpoint molecular traits causally driving disease development. In this review, we show the latest advances in this field, flag up key challenges for the future, and propose potential solutions.
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http://dx.doi.org/10.1101/cshperspect.a040493DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8091955PMC
May 2021

Genetic comorbidity between major depression and cardio-metabolic traits, stratified by age at onset of major depression.

Am J Med Genet B Neuropsychiatr Genet 2020 09 18;183(6):309-330. Epub 2020 Jul 18.

Max Planck Institute of Psychiatry, Munich, Germany.

It is imperative to understand the specific and shared etiologies of major depression and cardio-metabolic disease, as both traits are frequently comorbid and each represents a major burden to society. This study examined whether there is a genetic association between major depression and cardio-metabolic traits and if this association is stratified by age at onset for major depression. Polygenic risk scores analysis and linkage disequilibrium score regression was performed to examine whether differences in shared genetic etiology exist between depression case control status (N cases = 40,940, N controls = 67,532), earlier (N = 15,844), and later onset depression (N = 15,800) with body mass index, coronary artery disease, stroke, and type 2 diabetes in 11 data sets from the Psychiatric Genomics Consortium, Generation Scotland, and UK Biobank. All cardio-metabolic polygenic risk scores were associated with depression status. Significant genetic correlations were found between depression and body mass index, coronary artery disease, and type 2 diabetes. Higher polygenic risk for body mass index, coronary artery disease, and type 2 diabetes was associated with both early and later onset depression, while higher polygenic risk for stroke was associated with later onset depression only. Significant genetic correlations were found between body mass index and later onset depression, and between coronary artery disease and both early and late onset depression. The phenotypic associations between major depression and cardio-metabolic traits may partly reflect their overlapping genetic etiology irrespective of the age depression first presents.
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http://dx.doi.org/10.1002/ajmg.b.32807DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7991693PMC
September 2020

bGWAS: an R package to perform Bayesian genome wide association studies.

Bioinformatics 2020 08;36(15):4374-4376

Department of Training, Research and Innovation, University Center for Primary Care and Public Health, Lausanne 1010, Switzerland.

Summary: Increasing sample size is not the only strategy to improve discovery in Genome Wide Association Studies (GWASs) and we propose here an approach that leverages published studies of related traits to improve inference. Our Bayesian GWAS method derives informative prior effects by leveraging GWASs of related risk factors and their causal effect estimates on the focal trait using multivariable Mendelian randomization. These prior effects are combined with the observed effects to yield Bayes Factors, posterior and direct effects. The approach not only increases power, but also has the potential to dissect direct and indirect biological mechanisms.

Availability And Implementation: bGWAS package is freely available under a GPL-2 License, and can be accessed, alongside with user guides and tutorials, from https://github.com/n-mounier/bGWAS.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btaa549DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7520046PMC
August 2020

Commentary on: "The contribution of tissue-specific BMI-associated gene sets to cardiometabolic disease risk: a Mendelian randomization study".

Authors:
Zoltán Kutalik

Int J Epidemiol 2020 08;49(4):1257-1258

Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland.

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http://dx.doi.org/10.1093/ije/dyaa062DOI Listing
August 2020

48th European Mathematical Genetics Meeting (EMGM) 2020.

Authors:
Zoltan Kutalik

Hum Hered 2019 8;84(4-5):203-232. Epub 2020 Apr 8.

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http://dx.doi.org/10.1159/000507248DOI Listing
April 2020

Quantification of the overall contribution of gene-environment interaction for obesity-related traits.

Nat Commun 2020 03 13;11(1):1385. Epub 2020 Mar 13.

University Center for Primary Care and Public Health, University of Lausanne, Lausanne, 1010, Switzerland.

The growing sample size of genome-wide association studies has facilitated the discovery of gene-environment interactions (GxE). Here we propose a maximum likelihood method to estimate the contribution of GxE to continuous traits taking into account all interacting environmental variables, without the need to measure any. Extensive simulations demonstrate that our method provides unbiased interaction estimates and excellent coverage. We also offer strategies to distinguish specific GxE from general scale effects. Applying our method to 32 traits in the UK Biobank reveals that while the genetic risk score (GRS) of 376 variants explains 5.2% of body mass index (BMI) variance, GRSxE explains an additional 1.9%. Nevertheless, this interaction holds for any variable with identical correlation to BMI as the GRS, hence may not be GRS-specific. Still, we observe that the global contribution of specific GRSxE to complex traits is substantial for nine obesity-related measures (including leg impedance and trunk fat-free mass).
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http://dx.doi.org/10.1038/s41467-020-15107-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070002PMC
March 2020

Influence of Genetic Ancestry on Human Serum Proteome.

Am J Hum Genet 2020 03 13;106(3):303-314. Epub 2020 Feb 13.

Population Health Research Institute, David Braley Cardiac, Vascular, and Stroke Research Institute, 237 Barton Street East, Hamilton, ON L8L 2X2, Canada; Thrombosis and Atherosclerosis Research Institute, David Braley Cardiac, Vascular, and Stroke Research Institute, 237 Barton Street East, Hamilton, ON L8L 2X2, Canada; Department of Pathology and Molecular Medicine, McMaster University, Michael G. DeGroote School of Medicine, 1280 Main Street West, Hamilton ON L8S 4K1, Canada; Department of Clinical Epidemiology and Biostatistics, McMaster University, 1280 Main Street West, Hamilton ON L8S 4K1, Canada; Department of Biochemistry, McMaster University, 1280 Main Street West, Hamilton ON L8S 4K1, Canada. Electronic address:

Disease risk varies significantly between ethnic groups, however, the clinical significance and implications of these observations are poorly understood. Investigating ethnic differences within the human proteome may shed light on the impact of ancestry on disease risk. We used admixture mapping to explore the impact of genetic ancestry on 237 cardiometabolic biomarkers in 2,216 Latin Americans within the Outcomes Reduction with an Initial Glargine Intervention (ORIGIN) study. We developed a variance component model in order to determine the proportion of variance explained by inter-ancestry differences, and we applied it to the biomarker panel. Multivariable linear regression was used to identify and localize genetic loci affecting biomarker variability between ethnicities. Variance component analysis revealed that 5% of biomarkers were significantly impacted by genetic admixture (p < 0.05/237), including C-peptide, apolipoprotein-E, and intercellular adhesion molecule 1. We also identified 46 regional associations across 40 different biomarkers (p < 1.13 × 10). An independent analysis revealed that 34 of these 46 regions were associated at genome-wide significance (p < 5 × 10) with their respective biomarker in either Europeans or Latin populations. Additional analyses revealed that an admixture mapping signal associated with increased C-peptide levels was also associated with an increase in diabetes risk (odds ratio [OR] = 6.07 per SD, 95% confidence interval [CI] 1.44 to 25.56, p = 0.01) and surrogate measures of insulin resistance. Our results demonstrate the impact of ancestry on biomarker levels, suggesting that some of the observed differences in disease prevalence have a biological basis, and that reference intervals for those biomarkers should be tailored to ancestry. Specifically, our results point to a strong role of ancestry in insulin resistance and diabetes risk.
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http://dx.doi.org/10.1016/j.ajhg.2020.01.016DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7058828PMC
March 2020

Heterogeneity in Obesity: Genetic Basis and Metabolic Consequences.

Curr Diab Rep 2020 01 22;20(1). Epub 2020 Jan 22.

Institute for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland.

Purpose Of Review: Our review provides a brief summary of the most recent advances towards the identification of the genetic basis of specific aspects of obesity and the quantification of their consequences on health. We also highlight the most promising avenues to be explored in the future.

Recent Findings: While obesity has been demonstrated to lead to adverse cardio-metabolic consequences, the determinants of inter-individual variability remain largely unknown. The elucidation of the molecular underpinnings of this relationship is hampered by the extremely heterogeneous nature of obesity as a human trait. Recent technological advances have facilitated a more in-depth characterization of body composition at large-scale. At the pace of current data acquisition and resolution, it is realistic to improve characterization of obesity and to advise individuals based on detailed body composition combined with tissue-specific molecular signatures. Individualized predictions of health implications would enable more personalized and effective public health interventions.
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http://dx.doi.org/10.1007/s11892-020-1285-4DOI Listing
January 2020

FADS3 is a Δ14Z sphingoid base desaturase that contributes to gender differences in the human plasma sphingolipidome.

J Biol Chem 2020 02 20;295(7):1889-1897. Epub 2019 Dec 20.

Institute for Clinical Chemistry, University Hospital and University Zurich, 8091 Zürich, Switzerland. Electronic address:

Sphingolipids (SLs) are structurally diverse lipids that are defined by the presence of a long-chain base (LCB) backbone. Typically, LCBs contain a single Δ4E double bond (DB) (mostly d18:1), whereas the dienic LCB sphingadienine (d18:2) contains a second DB at the Δ14Z position. The enzyme introducing the Δ14Z DB is unknown. We analyzed the LCB plasma profile in a gender-, age-, and BMI-matched subgroup of the CoLaus cohort ( = 658). Sphingadienine levels showed a significant association with gender, being on average ∼30% higher in females. A genome-wide association study (GWAS) revealed variants in the fatty acid desaturase 3 () gene to be significantly associated with the plasma d18:2/d18:1 ratio ( = -log 7.9). Metabolic labeling assays, FADS3 overexpression and knockdown approaches, and plasma LCB profiling in FADS3-deficient mice confirmed that FADS3 is a LCB desaturase and required for the introduction of the Δ14Z double bond. Moreover, we showed that FADS3 is required for the conversion of the atypical cytotoxic 1-deoxysphinganine (1-deoxySA, m18:0) to 1-deoxysphingosine (1-deoxySO, m18:1). HEK293 cells overexpressing FADS3 were more resistant to m18:0 toxicity than WT cells. In summary, using a combination of metabolic profiling and GWAS, we identified FADS3 to be essential for forming Δ14Z DB containing LCBs, such as d18:2 and m18:1. Our results unravel FADS3 as a Δ14Z LCB desaturase, thereby disclosing the last missing enzyme of the SL synthesis pathway.
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http://dx.doi.org/10.1074/jbc.AC119.011883DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7029104PMC
February 2020

Associations of autozygosity with a broad range of human phenotypes.

Nat Commun 2019 10 31;10(1):4957. Epub 2019 Oct 31.

Department of Neurology, Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht University, Utrecht, 3584 CX, The Netherlands.

In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (F) for >1.4 million individuals, we show that F is significantly associated (p < 0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: F equivalent to the offspring of first cousins is associated with a 55% decrease [95% CI 44-66%] in the odds of having children. Finally, the effects of F are confirmed within full-sibling pairs, where the variation in F is independent of all environmental confounding.
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http://dx.doi.org/10.1038/s41467-019-12283-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6823371PMC
October 2019
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