Circulating metabolites modulated by diet are associated with depression.

Metabolome reflects the interplay of genome and exposome at molecular level and thus can provide deep insights into the pathogenesis of a complex disease like major depression. To identify metabolites associated with depression we performed a metabolome-wide association analysis in 13,596 participants from five European population-based cohorts characterized for depression, and circulating metabolites using ultra high-performance liquid chromatography/tandem accurate mass spectrometry (UHPLC/MS/MS) based Metabolon platform. We tested 806 metabolites covering a wide range of biochemical processes including those involved in lipid, amino-acid, energy, carbohydrate, xenobiotic and vitamin metabolism for their association with depression. In a conservative model adjusting for life style factors and cardiovascular and antidepressant medication use we identified 8 metabolites, including 6 novel, significantly associated with depression. In individuals with depression, increased levels of retinol (vitamin A), 1-palmitoyl-2-palmitoleoyl-GPC (16:0/16:1) (lecithin) and mannitol/sorbitol and lower levels of hippurate, 4-hydroxycoumarin, 2-aminooctanoate (alpha-aminocaprylic acid), 10-undecenoate (11:1n1) (undecylenic acid), 1-linoleoyl-GPA (18:2) (lysophosphatidic acid; LPA 18:2) are observed. These metabolites are either directly food derived or are products of host and gut microbial metabolism of food-derived products. Our Mendelian randomization analysis suggests that low hippurate levels may be in the causal pathway leading towards depression. Our findings highlight putative actionable targets for depression prevention that are easily modifiable through diet interventions.

First mitochondrial genome-wide association study with metabolomics.

In the era of personalized medicine with more and more patient-specific targeted therapies being used, we need reliable, dynamic, faster and sensitive biomarkers both to track the causes of disease and to develop and evolve therapies during the course of treatment. Metabolomics recently has shown substantial evidence to support its emerging role in disease diagnosis and prognosis. Aside from biomarkers and development of therapies, it is also an important goal to understand the involvement of mitochondrial DNA (mtDNA) in metabolic regulation, aging and disease development. Somatic mutations of the mitochondrial genome are also heavily implicated in age-related disease and aging. The general hypothesis is that an alteration in the concentration of metabolite profiles (possibly conveyed by lifestyle and environmental factors) influences the increase of mutation rate in the mtDNA and thereby contributes to a range of pathophysiological alterations observed in complex diseases. We performed an inverted mitochondrial genome-wide association analysis between mitochondrial nucleotide variants (mtSNVs) and concentration of metabolites. We used 151 metabolites and the whole sequenced mitochondrial genome from 2718 individuals to identify the genetic variants associated with metabolite profiles. Because of the high coverage, next-generation sequencing-based analysis of the mitochondrial genome allows for an accurate detection of mitochondrial heteroplasmy and for the identification of variants associated with the metabolome. The strongest association was found for mt715G > A located in the MT-12SrRNA with the metabolite ratio of C2/C10:1 (P-value = 6.82*10-09, ß = 0.909). The second most significant mtSNV was found for mt3714A > G located in the MT-ND1 with the metabolite ratio of phosphatidylcholine (PC) ae C42:5/PC ae C44:5 (P-value = 1.02*10-08, ß = 3.631). A large number of significant metabolite ratios were observed involving PC aa C36:6 and the variant mt10689G > A, located in the MT-ND4L gene. These results show an important interconnection between mitochondria and metabolite concentrations. Considering that some of the significant metabolites found in this study have been previously related to complex diseases, such as neurological disorders and metabolic conditions, these associations found here might play a crucial role for further investigations of such complex diseases. Understanding the mechanisms that control human health and disease, in particular, the role of genetic predispositions and their interaction with environmental factors is a prerequisite for the development of safe and efficient therapies for complex disorders.

Biomolecular insights into North African-related ancestry, mobility and diet in eleventh-century Al-Andalus.

Historical records document medieval immigration from North Africa to Iberia to create Islamic al-Andalus. Here, we present a low-coverage genome of an eleventh century CE man buried in an Islamic necropolis in Segorbe, near Valencia, Spain. Uniparental lineages indicate North African ancestry, but at the autosomal level he displays a mosaic of North African and European-like ancestries, distinct from any present-day population. Altogether, the genome-wide evidence, stable isotope results and the age of the burial indicate that his ancestry was ultimately a result of admixture between recently arrived Amazigh people (Berbers) and the population inhabiting the Peninsula prior to the Islamic conquest. We detect differences between our sample and a previously published group of contemporary individuals from Valencia, exemplifying how detailed, small-scale aDNA studies can illuminate fine-grained regional and temporal differences. His genome demonstrates how ancient DNA studies can capture portraits of past genetic variation that have been erased by later demographic shifts-in this case, most likely the seventeenth century CE expulsion of formerly Islamic communities as tolerance dissipated following the Reconquista by the Catholic kingdoms of the north.

Prediction of type 2 diabetes mellitus based on nutrition data.

Numerous predictive models for the risk of type 2 diabetes mellitus (T2DM) exist, but a minority of them has implemented nutrition data so far, even though the significant effect of nutrition on the pathogenesis, prevention and management of T2DM has been established. Thus, in the present study, we aimed to build a predictive model for the risk of T2DM that incorporates nutrition data and calculates its predictive performance. We analysed cross-sectional data from 1591 individuals from the population-based Cooperative Health Research in the Region of Augsburg (KORA) FF4 study (2013-14) and used a bootstrap enhanced elastic net penalised multivariate regression method in order to build our predictive model and select among 193 food intake variables. After selecting the significant predictor variables, we built a logistic regression model with these variables as predictors and T2DM status as the outcome. The values of area under the receiver operating characteristic (ROC) curve, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of our predictive model were calculated. Eleven out of the 193 food intake variables were selected for inclusion in our model, which yielded a value of area under the ROC curve of 0⋅79 and a maximum PPV, NPV and accuracy of 0⋅37, 0⋅98 and 0⋅91, respectively. The present results suggest that nutrition data should be implemented in predictive models to predict the risk of T2DM, since they improve their performance and they are easy to assess.

The conserved ASTN2/BRINP1 locus at 9q33.1-33.2 is associated with major psychiatric disorders in a large pedigree from Southern Spain.

We investigated the genetic causes of major mental disorders (MMDs) including schizophrenia, bipolar disorder I, major depressive disorder and attention deficit hyperactive disorder, in a large family pedigree from Alpujarras, South of Spain, a region with high prevalence of psychotic disorders. We applied a systematic genomic approach based on karyotyping (n = 4), genotyping by genome-wide SNP array (n = 34) and whole-genome sequencing (n = 12). We performed genome-wide linkage analysis, family-based association analysis and polygenic risk score estimates. Significant linkage was obtained at chromosome 9 (9q33.1-33.2, LOD score = 4.11), a suggestive region that contains five candidate genes ASTN2, BRINP1, C5, TLR4 and TRIM32, previously associated with MMDs. Comprehensive analysis associated the MMD phenotype with genes of the immune system with dual brain functions. Moreover, the psychotic phenotype was enriched for genes involved in synapsis. These results should be considered once studying the genetics of psychiatric disorders in other families, especially the ones from the same region, since founder effects may be related to the high prevalence.

Familial Psychosis Associated With a Missense Mutation at MACF1 Gene Combined With the Rare Duplications DUP3p26.3 and DUP16q23.3, Affecting the CNTN6 and CDH13 Genes.

Psychosis is a highly heritable and heterogeneous psychiatric condition. Its genetic architecture is thought to be the result of the joint effect of common and rare variants. Families with high prevalence are an interesting approach to shed light on the rare variant's contribution without the need of collecting large cohorts. To unravel the genomic architecture of a family enriched for psychosis, with four affected individuals, we applied a system genomic approach based on karyotyping, genotyping by whole-exome sequencing to search for rare single nucleotide variants (SNVs) and SNP array to search for copy-number variants (CNVs). We identified a rare non-synonymous variant, g.39914279 C > G, in the MACF1 gene, segregating with psychosis. Rare variants in the MACF1 gene have been previously detected in SCZ patients. Besides, two rare CNVs, DUP3p26.3 and DUP16q23.3, were also identified in the family affecting relevant genes (CNTN6 and CDH13, respectively). We hypothesize that the co-segregation of these duplications with the rare variant g.39914279 C > G of MACF1 gene precipitated with schizophrenia and schizoaffective disorder.

Mitochondrial GWA Analysis of Lipid Profile Identifies Genetic Variants to Be Associated with HDL Cholesterol and Triglyceride Levels.

It has been suggested that mitochondrial dysfunction has an influence on lipid metabolism. The fact that mitochondrial defects can be accumulated over time as a normal part of aging may explain why cholesterol levels often are altered with age. To test the hypothesis whether mitochondrial variants are associated with lipid profile (total cholesterol, LDL, HDL, and triglycerides) we analyzed a total number of 978 mitochondrial single nucleotide polymorphisms (mtSNPs) in a sample of 2,815 individuals participating in the population-based KORA F4 study. To assess mtSNP association while taking the presence of heteroplasmy into account we used the raw signal intensity values measured on the microarray and applied linear regression. Ten mtSNPs (mt3285, mt3336, mt5285, mt6591, mt6671, mt9163, mt13855, mt13958, mt14000, and mt14580) were significantly associated with HDL cholesterol and one mtSNP (mt15074) with triglycerides levels. These results highlight the importance of the mitochondrial genome among the factors that contribute to the regulation of lipid levels. Focusing on mitochondrial variants may lead to further insights regarding the underlying physiological mechanisms, or even to the development of innovative treatments. Since this is the first mitochondrial genome-wide association analysis (mtGWAS) for lipid profile, further analyses are needed to follow up on the present findings.

Mitochondrial genetic variants identified to be associated with BMI in adults.

It has been suggested that mitochondrial dysfunction plays a role in metabolic disorders including obesity, diabetes, and hypertension. The fact that mitochondrial defects can be accumulated over time as a normal part of aging may explain why some individuals can eat all sorts of foods and remain at normal weight while they are young. However, around the fourth decade of life there is a trend towards "middle-age spread" with weight gain and the body's decreasing ability to metabolize calories efficiently. To test the hypothesis that mitochondrial variants are associated with BMI in adults, we analyzed a total number of 984 mitochondrial single nucleotide polymorphisms (mtSNPs) in a sample of 6,528 individuals participating in the KORA studies. To assess mtSNP association while taking heteroplasmy into account we used the raw signal intensity values measured on the microarray and applied linear regression. Significant results were obtained for 2 mtSNPs located in the Cytochrome c oxidase subunit genes (MT-CO1: Padjusted = 0.0140 and MT-CO3: Padjusted = 0.0286) and 3 mtSNPs located in the NADH dehydrogenase subunit genes (MT-ND1, MT-ND2 and MT-ND4L: Padjusted = 0.0286). Polymorphisms located in the MT-CO3 and MT-ND4L genes have not been associated with BMI or related phenotypes in the past. Our results highlight the importance of the mitochondrial genome among the factors that contribute to the risk of high BMI. Focusing on mitochondrial variants may lead to further insights regarding effects of existing medications, or even to the development of innovative treatments.

Association study of mitochondrial genetic polymorphisms in asthmatic children.

It has been suggested that mitochondrial dysfunction plays a role in the pathogenesis of asthma. To test whether mitochondrial variants influence the risk of asthma, we analyzed 16,158 mtSNPs in a sample of 372 asthmatic children and 395 healthy children using the DNA pooling technique and genome wide association analysis. Stratified analysis by sex was performed to explain the differences observed between sexes in the etiology of asthma. Different variants were detected to be significant in the sample of girls and boys with the smallest adjusted p values being 1.4 × 10(-09) (mt5295) and 3.6 × 10(-12) (mt16158), respectively. Most of the significant locations found in boys are within the CYB gene and the non-coding region. For girls, most of the significant mtSNPs lie within NADH-dehydrogenase-subunits. The variants reported here have not previously been described in connection with asthma. Although further studies in other cohorts are needed to confirm these findings our study highlights the importance of the mitochondria among the factors that contribute to the risk of asthma.

Genome-wide linkage analysis of congenital heart defects using MOD score analysis identifies two novel loci.

BACKGROUND: Congenital heart defects (CHD) is the most common cause of death from a congenital structure abnormality in newborns and is often associated with fetal loss. There are many types of CHD. Human genetic studies have identified genes that are responsible for the inheritance of a particular type of CHD and for some types of CHD previously thought to be sporadic. However, occasionally different members of the same family might have anatomically distinct defects - for instance, one member with atrial septal defect, one with tetralogy of Fallot, and one with ventricular septal defect. Our objective is to identify susceptibility loci for CHD in families affected by distinct defects. The occurrence of these apparently discordant clinical phenotypes within one family might hint at a genetic framework common to most types of CHD. RESULTS: We performed a genome-wide linkage analysis using MOD score analysis in families with diverse CHD. Significant linkage was obtained in two regions, at chromosome 15 (15q26.3, P(empirical) = 0.0004) and at chromosome 18 (18q21.2, P(empirical) = 0.0005). CONCLUSIONS: In these two novel regions four candidate genes are located: SELS, SNRPA1, and PCSK6 on 15q26.3, and TCF4 on 18q21.2. The new loci reported here have not previously been described in connection with CHD. Although further studies in other cohorts are needed to confirm these findings, the results presented here together with recent insight into how the heart normally develops will improve the understanding of CHD.

A comparison of different linkage statistics in small to moderate sized pedigrees with complex diseases.

BACKGROUND: In the last years GWA studies have successfully identified common SNPs associated with complex diseases. However, most of the variants found this way account for only a small portion of the trait variance. This fact leads researchers to focus on rare-variant mapping with large scale sequencing, which can be facilitated by using linkage information. The question arises why linkage analysis often fails to identify genes when analyzing complex diseases. Using simulations we have investigated the power of parametric and nonparametric linkage statistics (KC-LOD, NPL, LOD and MOD scores), to detect the effect of genes responsible for complex diseases using different pedigree structures. RESULTS: As expected, a small number of pedigrees with less than three affected individuals has low power to map disease genes with modest effect. Interestingly, the power decreases when unaffected individuals are included in the analysis, irrespective of the true mode of inheritance. Furthermore, we found that the best performing statistic depends not only on the type of pedigrees but also on the true mode of inheritance. CONCLUSIONS: When applied in a sensible way linkage is an appropriate and robust technique to map genes for complex disease. Unlike association analysis, linkage analysis is not hampered by allelic heterogeneity. So, why does linkage analysis often fail with complex diseases? Evidently, when using an insufficient number of small pedigrees, one might miss a true genetic linkage when actually a real effect exists. Furthermore, we show that the test statistic has an important effect on the power to detect linkage as well. Therefore, a linkage analysis might fail if an inadequate test statistic is employed. We provide recommendations regarding the most favorable test statistics, in terms of power, for a given mode of inheritance and type of pedigrees under study, in order to reduce the probability to miss a true linkage.

A new susceptibility locus for bipolar affective disorder in PAR1 on Xp22.3/Yp11.3.

We present the findings of a linkage study of bipolar affective disorder (BPAD) that involve the pseudoautosomal region 1 of the human sex chromosomes. We analyzed a substantial subset of pedigrees (89 families of German and Spanish origin; 661 participants; 298 affected individuals) from the large collection of BPAD-affected families with which a genomewide linkage analysis was previously performed and where the pseudoautosomal regions were poorly covered. Nonparametric linkage (Z(lr)) scores were calculated. The highest Z(lr) scores were obtained on Xp22.3/Yp11.3 in the Spanish subsample (DXS1071; Z(lr) = 3.54, P(empirical) = 0.0009 for the broad definition of affection sttuts; Z(lr) = 2.63, P(empirical) = 0.0129 for the medium definition of affection status; Z(lr) = 2.12, P(empirical) = 0.0429 for the narrow definition of affection status). Empirical P-values are adjusted using the Bonferroni correction to account for the testing of three affection status definitions. This region has not drawn much attention in previous linkage studies of BPAD. On the basis of these results, Xp22.3/Yp11.3 should now be considered a candidate region for BPAD.

A new sex-specific genetic map of the human pseudoautosomal regions (PAR1 and PAR2).

OBJECTIVES: Accurate sex-specific genetic maps are essential for gene mapping projects when using multipoint methods, especially for the pseudoautosomal regions (PARs). This paper describes a new sex-specific genetic map for the human PARs. METHODS: We used multipoint linkage analysis, three-generation pedigrees and to date, the largest set of genetic markers to estimate recombination events in the PARs. The new map combines genotype data from 28 CEPH pedigrees and 29 genetic markers. All genetic markers have been physically mapped, thus providing the opportunity to compare genetic to physical distance through all the intervals. RESULTS: Recombination activity in PAR1 is on average 7-fold higher in male than in female meiosis, resulting in a much larger genetic map for males. This new map shows how genetically different in size is the X chromosome between males and females. CONCLUSIONS: Genetic distances vary extremely between males and females in the PARs. These differences should be considered in genetic studies using accurate sex-specific maps instead of sex-averaged maps. The new map provides a significantly different length compared to some previously published maps, since a much higher number of genetic markers is used. Therefore, we conclude that our map is the most accurate resource for obtaining genetic map information for the PARs.

Evaluation of potential power gain with imputed genotypes in genome-wide association studies.

BACKGROUND: With the beginning of the era of genome-wide association studies methods to obtain 'in silico' genotypes have gained importance. In this context, an evaluation of genome-wide power levels of current marker panels and the power gain achievable with imputed genotypes are of high interest. METHODS: Power for single-marker analysis of imputed genotypes is evaluated via a simulation study based on HapMap data. Power values for genome-wide significance of marker panels of 1,000,000 SNPs are considered for small effect sizes typical of common diseases and large case-control samples. In order to evaluate the performance of imputing, we consider a method that is conceptually related to previous approaches. We introduce various modifications which together lead to an alternative implementation of the imputation idea. In particular, a Monte-Carlo (MC) simulation method for association testing of imputed markers is introduced. RESULTS: We show that the incorporation of imputed genotypes can lead to a substantial power gain for common disease variants if the training sample is large enough. In addition, we show that the MC approach is valuable to for validating association results obtained with imputed genotypes. DISCUSSION: Our simulation study also shows that even denser marker panels than those currently available are needed when sample size is limited. We thus expect that full genome SNP panels will lead to the identification of additional disease variants in the future. Until then, it is desirable that large and ethnically matched training samples genotyped on dense marker panels are available in each country.

Genetic association study of the P-type ATPase ATP13A2 in late-onset Parkinson's disease.

A role of ATP13A2 in early-onset Parkinsonism (EOP) has been proposed. Conversely, the contribution of this ATPase to late-onset Parkinson's disease (PD) remains unexplored. We therefore conducted a case-control association study in this age-of-onset group with PD. The initial sample was of German origin and consisted of 220 patients with late-onset PD (mean age of onset 60.1 years) and 232 age-matched unrelated controls. Five single nucleotide polymorphisms (SNPs) covering ATP13A2 and its common haplotypes were genotyped. The overall association results in this sample were negative. Interestingly, gender stratification gave a positive result for SNP rs11203280 (P(UNC) = 0.016) in men. This result could not be reproduced in a replication sample of German and Serbian origin composed of 161 patients with late-onset PD (mean age of onset 51.7 years) and 150 age- and ethnic-matched controls. In conclusion, we found no consistent evidence for an association between ATP13A2 and late-onset PD.

Susceptibility variants for male-pattern baldness on chromosome 20p11.

We carried out a genome-wide association study in 296 individuals with male-pattern baldness (androgenetic alopecia) and 347 controls. We then investigated the 30 best SNPs in an independent replication sample and found highly significant association for five SNPs on chromosome 20p11 (rs2180439 combined P = 2.7 x 10(-15)). No interaction was detected with the X-chromosomal androgen receptor locus, suggesting that the 20p11 locus has a role in a yet-to-be-identified androgen-independent pathway.

Genome-wide SNP-based linkage scan identifies a locus on 8q24 for an age-related hearing impairment trait.

Age-related hearing impairment (ARHI), or presbycusis, is a very common multifactorial disorder. Despite the knowledge that genetics play an important role in the etiology of human ARHI as revealed by heritability studies, to date, its precise genetic determinants remain elusive. Here we report the results of a cross-sectional family-based genetic study employing audiometric data. By using principal component analysis, we were able to reduce the dimensionality of this multivariate phenotype while capturing most of the variation and retaining biologically important features of the audiograms. We conducted a genome-wide association as well as a linkage scan with high-density SNP microarrays. Because of the presence of genetic population substructure, association testing was stratified after which evidence was combined by meta-analysis. No association signals reaching genome-wide significance were detected. Linkage analysis identified a linkage peak on 8q24.13-q24.22 for a trait correlated to audiogram shape. The signal reached genome-wide significance, as assessed by simulations. This finding represents the first locus for an ARHI trait.

The human pseudoautosomal regions: a review for genetic epidemiologists.

Two intervals of sequence identity at the tips of X and Y chromosomes, the human pseudoautosomal regions PAR1 and PAR2, have drawn interest from researchers in human genetics, cytogenetics, and evolutionary biology. However, they have been widely ignored in linkage and association studies. The pseudoautosomal regions (PARs) pair and recombine during meiosis like autosomes, but the recombination activity in PAR1 is extremely different between sexes. In men, it exhibits the highest recombination frequencies of the genome. Conflicting genetic maps of this region have been estimated by using three-generation pedigrees, sperm typing, and by using haplotypes from single nucleotide polymorphisms. Male genetic map lengths in the literature vary, and linkage disequilibrium has not been analyzed in detail. We review existing tools like genetic and physical maps, linkage disequilibrium methods, linkage and association analysis, implemented statistical methods, and their suitability for PARs. For multipoint linkage analysis, sex specificity must be indicated twice, first using sex-specific maps, and second by considering the sex-specific pseudoautosomal inheritance pattern. Currently, microsatellite panels and single nucleotide polymorphism chips do not contain sufficient numbers of markers in PAR1 and PAR2. The number of markers in PAR1, needed in indirect association studies, should be much larger than for autosomal regions alike in size, since linkage disequilibrium is very low. For genome-wide studies, it is essential to include pseudoautosomal markers since such expensive studies cannot afford to oversee pseudoautosomal linkage or association. This drawback could be solved with a sufficient number of markers, statistical methods that are adopted for the PARs, and their integration into softwares.

Genome-wide scan and fine-mapping linkage study of androgenetic alopecia reveals a locus on chromosome 3q26.

Androgenetic alopecia (AGA, male pattern baldness) is the most common form of hair loss. The origin of AGA is genetic, with the X chromosome located androgen receptor gene (AR) being the only risk gene identified to date. We present the results of a genome-wide linkage study of 95 families and linkage fine mapping of the 3q21-q29, 11q14-q25, 18p11-q23, and 19p13-q13 regions in an extended sample of 125 families of German descent. The locus with strongest evidence for linkage was mapped to 3q26 with a nonparametric linkage (NPL) score of 3.97 (empirical p value = 0.00055). This is the first step toward the identification of new susceptibility genes in AGA, a process which will provide important insights into the molecular and cellular basis of scalp hair loss.

Loss-of-function mutations in the filaggrin gene and alopecia areata: strong risk factor for a severe course of disease in patients comorbid for atopic disease.

Alopecia areata (AA) is a common dermatological disease, which affects nearly 2% of the general population. Association of AA with atopic disease has been repeatedly reported. Loss-of-function mutations in the filaggrin gene (FLG) may be considered as promising candidates in AA, as they have been observed to be a strong risk factor in atopic dermatitis. The FLG mutations R501X and 2282del4 were genotyped in a large sample of AA patients (n=449) and controls (n=473). Although no significant association was observed in the patient sample overall, FLG mutations were significantly associated with the presence of atopic dermatitis among AA patients. Furthermore, the presence of FLG mutations had a strong impact on the clinical course of AA in comorbid patients. For example, 19 of the 22 mutation carriers among AA patients with atopic dermatitis showed a severe form of the disease (P=0.003; odds ratio (OR)=5.47 (95% confidence interval (CI): 1.59-18.76)). In conclusion, our data suggest that when AA occurs in conjunction with FLG-associated atopic disorder, the clinical presentation of AA may be more severe.