FinnGen provides genetic insights from a well-phenotyped isolated population.

Population isolates such as those in Finland benefit genetic research because deleterious alleles are often concentrated on a small number of low-frequency variants (0.1% ≤ minor allele frequency < 5%). These variants survived the founding bottleneck rather than being distributed over a large number of ultrarare variants. Although this effect is well established in Mendelian genetics, its value in common disease genetics is less explored1,2. FinnGen aims to study the genome and national health register data of 500,000 Finnish individuals. Given the relatively high median age of participants (63 years) and the substantial fraction of hospital-based recruitment, FinnGen is enriched for disease end points. Here we analyse data from 224,737 participants from FinnGen and study 15 diseases that have previously been investigated in large genome-wide association studies (GWASs). We also include meta-analyses of biobank data from Estonia and the United Kingdom. We identified 30 new associations, primarily low-frequency variants, enriched in the Finnish population. A GWAS of 1,932 diseases also identified 2,733 genome-wide significant associations (893 phenome-wide significant (PWS), P < 2.6 × 10-11) at 2,496 (771 PWS) independent loci with 807 (247 PWS) end points. Among these, fine-mapping implicated 148 (73 PWS) coding variants associated with 83 (42 PWS) end points. Moreover, 91 (47 PWS) had an allele frequency of <5% in non-Finnish European individuals, of which 62 (32 PWS) were enriched by more than twofold in Finland. These findings demonstrate the power of bottlenecked populations to find entry points into the biology of common diseases through low-frequency, high impact variants.

NCOR2 is a novel candidate gene for migraine-epilepsy phenotype.

HYPOTHESIS: To identify genetic factors predisposing to migraine-epilepsy phenotype utilizing a multi-generational family with known linkage to chr12q24.2-q24.3. METHODS: We used single nucleotide polymorphism (SNP) genotyping and next-generation sequencing technologies to perform linkage, haplotype, and variant analyses in an extended Finnish migraine-epilepsy family (n = 120). In addition, we used a large genome-wide association study (GWAS) dataset of migraine and two biobank studies, UK Biobank and FinnGen, to test whether variants within the susceptibility region associate with migraine or epilepsy related phenotypes in a population setting. RESULTS: The family showed the highest evidence of linkage (LOD 3.42) between rs7966411 and epilepsy. The haplotype shared among 12 out of 13 epilepsy patients in the family covers almost the entire NCOR2 and co-localizes with one of the risk loci of the recent GWAS on migraine. The haplotype harbors nine low-frequency variants with potential regulatory functions. Three of them, in addition to two common variants, show nominal associations with neurological disorders in either UK Biobank or FinnGen. CONCLUSION: We provide several independent lines of evidence supporting association between migraine-epilepsy phenotype and NCOR2. Our study suggests that NCOR2 may have a role in both migraine and epilepsy and thus would provide evidence for shared pathophysiology underlying these two diseases.

PSEUDOMARKER 2.0: efficient computation of likelihoods using NOMAD.

BACKGROUND: PSEUDOMARKER is a software package that performs joint linkage and linkage disequilibrium analysis between a marker and a putative disease locus. A key feature of PSEUDOMARKER is that it can combine case-controls and pedigrees of varying structure into a single unified analysis. Thus it maximizes the full likelihood of the data over marker allele frequencies or conditional allele frequencies on disease and recombination fraction. RESULTS: The new version 2.0 uses the software package NOMAD to maximize likelihoods, resulting in generally comparable or better optima with many fewer evaluations of the likelihood functions. CONCLUSIONS: After being modified substantially to use modern optimization methods, PSEUDOMARKER version 2.0 is more robust and substantially faster than version 1.0. NOMAD may be useful in other bioinformatics problems where complex likelihood functions are optimized.

The prevalence of metabolic syndrome and metabolically healthy obesity in Europe: a collaborative analysis of ten large cohort studies.

BACKGROUND: Not all obese subjects have an adverse metabolic profile predisposing them to developing type 2 diabetes or cardiovascular disease. The BioSHaRE-EU Healthy Obese Project aims to gain insights into the consequences of (healthy) obesity using data on risk factors and phenotypes across several large-scale cohort studies. Aim of this study was to describe the prevalence of obesity, metabolic syndrome (MetS) and metabolically healthy obesity (MHO) in ten participating studies. METHODS: Ten different cohorts in seven countries were combined, using data transformed into a harmonized format. All participants were of European origin, with age 18-80 years. They had participated in a clinical examination for anthropometric and blood pressure measurements. Blood samples had been drawn for analysis of lipids and glucose. Presence of MetS was assessed in those with obesity (BMI ≥ 30 kg/m2) based on the 2001 NCEP ATP III criteria, as well as an adapted set of less strict criteria. MHO was defined as obesity, having none of the MetS components, and no previous diagnosis of cardiovascular disease. RESULTS: Data for 163,517 individuals were available; 17% were obese (11,465 men and 16,612 women). The prevalence of obesity varied from 11.6% in the Italian CHRIS cohort to 26.3% in the German KORA cohort. The age-standardized percentage of obese subjects with MetS ranged in women from 24% in CHRIS to 65% in the Finnish Health2000 cohort, and in men from 43% in CHRIS to 78% in the Finnish DILGOM cohort, with elevated blood pressure the most frequently occurring factor contributing to the prevalence of the metabolic syndrome. The age-standardized prevalence of MHO varied in women from 7% in Health2000 to 28% in NCDS, and in men from 2% in DILGOM to 19% in CHRIS. MHO was more prevalent in women than in men, and decreased with age in both sexes. CONCLUSIONS: Through a rigorous harmonization process, the BioSHaRE-EU consortium was able to compare key characteristics defining the metabolically healthy obese phenotype across ten cohort studies. There is considerable variability in the prevalence of healthy obesity across the different European populations studied, even when unified criteria were used to classify this phenotype.

Identifying flavor preference subgroups. Genetic basis and related eating behavior traits.

Subgroups based on flavor preferences were identified and their genetic and behavior related characteristics investigated using extensive data from 331 Finnish twins (21-25years, 146 men) including 47 monozygotic (MZ) and 93 dizygotic (DZ) pairs, and 51 twin individuals. The subgroup identification (hierarchical and K-means clustering) was based on liking responses to food names representing sour, umami, and spicy flavor qualities. Furthermore, sensory tests were conducted, a questionnaire on food likes completed, and various eating behavior related traits measured with validated scales. Sensory data included intensity ratings of PROP (6-n-propylthiouracil-impregnated filter paper), hedonic and intensity responses to sourness (orange juice with and without added citric acid, 0.42%), pungency (strawberry jelly with and without added capsaicin 0.00013%) and umami ('mouthfeel flavor' taste solution). Ratings of liking of 41 general food names were categorized into salty-and-fatty, sweet-and-fatty, fruits and vegetables and fish foods. Subgroup differences (complex samples procedure) and the genetics underlying the subgroups (structural equation modeling) were investigated. Of the resulting two groups (basic, n=140, adventurous n=152; non-grouped n=39), the adventurous expressed higher liking for sour and spicy foods, and had more tolerance for capsaicin burn in the sensory-hedonic test. The adventurous were also less food neophobic (25.9±9.1 vs. 32.5±10.6, respectively) and expressed higher liking for fruits and vegetables compared to the basic group. Genetic effects were shown to underlie the subgroups (heritability 72%, CI: 36-92%). Linkage analysis for 27 candidate gene regions revealed suggestively that being adventurous is linked to TAS1R1 and PKD1L3 genes. These results indicate that food neophobia and genetic differences may form a barrier through which individual flavor preferences are generated.

On the validity of the likelihood ratio test and consistency of resulting parameter estimates in joint linkage and linkage disequilibrium analysis under improperly specified parametric models.

It has been shown that parametric analysis of linkage disequilibrium conditional on linkage using an overly deterministic model can be optimal for family-based association analysis. However, if one applies this strategy carelessly, there is a risk of false inference. We analyse properties of such likelihood ratio tests when the assumed disease mode of inheritance is inaccurate. Under some conditions, problems result if one is not careful to consider what null hypothesis is being tested. We show that: (a) tests for which the null hypothesis assumes the absence of both linkage and association are independent of the true mode of inheritance; (b) likelihood ratio tests assuming either linkage or association under the null hypothesis may depend on the true mode of inheritance, leading to inconsistent parameter estimates, in particular under extremely deterministic models; (c) this problem cannot be eliminated by increasing sample size or adding population controls--as sample size increases, the chance of false positive inference goes to 100%; (d) this issue can lead to systematic false positive inference of association in regions of linkage. This is important because highly deterministic models are often used intentionally in model-based analyses because they can have more power than the true model, and are implicit in many model-free analysis methods.

PSEUDOMARKER: a powerful program for joint linkage and/or linkage disequilibrium analysis on mixtures of singletons and related individuals.

A decade ago, there was widespread enthusiasm for the prospects of genome-wide association studies to identify common variants related to common chronic diseases using samples of unrelated individuals from populations. Although technological advancements allow us to query more than a million SNPs across the genome at low cost, a disappointingly small fraction of the genetic portion of common disease etiology has been uncovered. This has led to the hypothesis that less frequent variants might be involved, stimulating a renaissance of the traditional approach of seeking genes using multiplex families from less diverse populations. However, by using the modern genotyping and sequencing technology, we can now look not just at linkage, but jointly at linkage and linkage disequilibrium (LD) in such samples. Software methods that can look simultaneously at linkage and LD in a powerful and robust manner have been lacking. Most algorithms cannot jointly analyze datasets involving families of varying structures in a statistically or computationally efficient manner. We have implemented previously proposed statistical algorithms in a user-friendly software package, PSEUDOMARKER. This paper is an announcement of this software package. We describe the motivation behind the approach, the statistical methods, and software, and we briefly demonstrate PSEUDOMARKER's advantages over other packages by example.

Recontacting biobank participants to collect lifestyle, behavioural and cognitive information via online questionnaires: lessons from a pilot study within FinnGen.

OBJECTIVES: To recontact biobank participants and collect cognitive, behavioural and lifestyle information via a secure online platform. DESIGN: Biobank-based recontacting pilot study. SETTING: Three Finnish biobanks (Helsinki, Auria, Tampere) recruiting participants from February 2021 to July 2021. PARTICIPANTS: All eligible invitees were enrolled in FinnGen by their biobanks (Helsinki, Auria, Tampere), had available genetic data and were >18 years old. Individuals with severe neuropsychiatric disease or cognitive or physical disabilities were excluded. Lastly, 5995 participants were selected based on their polygenic score for cognitive abilities and invited to the study. Among invitees, 1115 had successfully participated and completed the study questionnaire(s). OUTCOME MEASURES: The primary outcome was the participation rate among study invitees. Secondary outcomes included questionnaire completion rate, quality of data collected and comparison of participation rate boosting strategies. RESULTS: The overall participation rate was 18.6% among all invitees and 23.1% among individuals aged 18-69. A second reminder letter yielded an additional 9.7% participation rate in those who did not respond to the first invitation. Recontacting participants via an online healthcare portal yielded lower participation than recontacting via physical letter. The completion rate of the questionnaire and cognitive tests was high (92% and 85%, respectively), and measurements were overall reliable among participants. For example, the correlation (r) between self-reported body mass index and that collected by the biobanks was 0.92. CONCLUSION: In summary, this pilot suggests that recontacting FinnGen participants with the goal to collect a wide range of cognitive, behavioural and lifestyle information without additional engagement results in a low participation rate, but with reliable data. We suggest that such information be collected at enrolment, if possible, rather than via post hoc recontacting.

Combined genome scans for body stature in 6,602 European twins: evidence for common Caucasian loci.

Twin cohorts provide a unique advantage for investigations of the role of genetics and environment in the etiology of variation in common complex traits by reducing the variance due to environment, age, and cohort differences. The GenomEUtwin (http://www.genomeutwin.org) consortium consists of eight twin cohorts (Australian, Danish, Dutch, Finnish, Italian, Norwegian, Swedish, and United Kingdom) with the total resource of hundreds of thousands of twin pairs. We performed quantitative trait locus (QTL) analysis of one of the most heritable human complex traits, adult stature (body height) using genome-wide scans performed for 3,817 families (8,450 individuals) derived from twin cohorts from Australia, Denmark, Finland, Netherlands, Sweden, and United Kingdom with an approximate ten-centimorgan microsatellite marker map. The marker maps for different studies differed and they were combined and related to the sequence positions using software developed by us, which is publicly available (https://apps.bioinfo.helsinki.fi/software/cartographer.aspx). Variance component linkage analysis was performed with age, sex, and country of origin as covariates. The covariate adjusted heritability was 81% for stature in the pooled dataset. We found evidence for a major QTL for human stature on 8q21.3 (multipoint logarithm of the odds 3.28), and suggestive evidence for loci on Chromosomes X, 7, and 20. Some evidence of sex heterogeneity was found, however, no obvious female-specific QTLs emerged. Several cohorts contributed to the identified loci, suggesting an evolutionarily old genetic variant having effects on stature in European-based populations. To facilitate the genetic studies of stature we have also set up a website that lists all stature genome scans published and their most significant loci (http://www.genomeutwin.org/stature_gene_map.htm).

An epigenome-wide association study of metabolic syndrome and its components.

The role of metabolic syndrome (MetS) as a preceding metabolic state for type 2 diabetes and cardiovascular disease is widely recognised. To accumulate knowledge of the pathological mechanisms behind the condition at the methylation level, we conducted an epigenome-wide association study (EWAS) of MetS and its components, testing 1187 individuals of European ancestry for approximately 470 000 methylation sites throughout the genome. Methylation site cg19693031 in gene TXNIP -previously associated with type 2 diabetes, glucose and lipid metabolism, associated with fasting glucose level (P = 1.80 × 10-8). Cg06500161 in gene ABCG1 associated both with serum triglycerides (P = 5.36 × 10-9) and waist circumference (P = 5.21 × 10-9). The previously identified type 2 diabetes-associated locus cg08309687 in chromosome 21 associated with waist circumference for the first time (P = 2.24 × 10-7). Furthermore, a novel HDL association with cg17901584 in chromosome 1 was identified (P = 7.81 × 10-8). Our study supports previous genetic studies of MetS, finding that lipid metabolism plays a key role in pathology of the syndrome. We provide evidence regarding a close interplay with glucose metabolism. Finally, we suggest that in attempts to identify methylation loci linking separate MetS components, cg19693031 appears to represent a strong candidate.

Linkage analysis of schizophrenia controlling for population substructure.

Etiological heterogeneity and complexity has hampered attempts to identify predisposing genes for schizophrenia. We sought to minimize the number of segregating genes involved by focusing on a population isolate with elevated disease prevalence. We exploited the well-established population history, and searched for disease susceptibility loci in families from two alternative founder lineages. We studied 28 schizophrenia pedigrees (123 nuclear families) from an outlying municipality on the eastern border of Finland. We divided the families based on their genealogy and defined two routes of immigration: southern and northern. We examined the kinship coefficients and allele frequency distributions within each group, and performed a linkage analysis based on 497 microsatellite markers across the genome. A high degree of historical relatedness was demonstrated by higher sharing of alleles than predicted by the relationships we identified within the previous four generations alone, as would be expected. Between the two subpopulations, allele frequencies were significantly different, consistent with their isolated genealogies. The southern families showed some evidence of linkage in a schizophrenia locus at 4q23 (Z = 3.3) near our previous finding with quantitative variation in verbal learning and memory [Paunio et al. (2004); Hum Mol Genet 13: 1693-1702], while the northern pedigrees gave most significant evidence on 10q21 (Z = 2.53). Joint analysis of families from both lineages suggested evidence of linkage only at 3p14 (Z = 3.18). Thus the detailed genealogical information led us to identification of distinct linkage signals for schizophrenia susceptibility loci between the three analyses we performed.

A bias-ed assessment of the use of SNPs in human complex traits.

Although many biotechnological advancements have been made in the past decade, there has been very limited success in unraveling the genetic component of complex traits. Heavily invested research has been initiated based on etiological models of unrealistic simplicity and conducted under poor experimental designs, on data sets of insufficient size, leading to an overestimation of the effect sizes of genetic variants and the quantity and quality of linkage disequilibrium (LD). Arguments about whether families or unrelated individuals provide more power for gene mapping have been erroneously debated as issues of whether linkage or LD are more detectable sorts of correlation. Although the latter issue may be subject to debate, there is no doubt that family-based analysis is more powerful for detecting linkage and/or LD. If the recent advances in biotechnology are to be exploited effectively, vastly improved study designs will be imperative, as the reasons for the lack of success to date have much more to do with biology than technology, an issue that has become increasingly clear with the findings of the past years.

Genetic component of identification, intensity and pleasantness of odours: a Finnish family study.

Although potential odorant receptor genes have been identified, the precise genetic component of perception of odours is still obscure. Although there is some evidence for heritability of a few olfactory-related traits, no genome-wide search for loci harboring underlying genes has been published to date. We performed a genome-wide scan to identify loci affecting the identification, intensity and pleasantness of 12 odours (cinnamon, turpentine, lemon, smoke, chocolate, rose, paint thinner, banana, pineapple, gasoline, soap, onion) using 146 Finnish adults from 26 families. Several of these traits showed heritable variation in the families. Suggestive evidence of linkage was found for the pleasantness of cinnamon odour (h(2)=61%) on chromosome 4q32.3 (multipoint logarithm of the odds (LOD) score 3.01), as well as for the perceived intensity of paint thinner odour (h(2)=31%) on chromosome 2p14 (multipoint LOD score 2.55). As these loci do not contain any known human odorant receptor genes, they may rather harbor genes that affect the central processing than the peripheral detection of the odour signal. Thus, perception of odours is potentially modified by genes other than those encoding odorant receptors.

An utter refutation of the "fundamental theorem of the HapMap".

The International HapMap Project was proposed in order to quantify linkage disequilibrium (LD) relationships among human DNA polymorphisms in an assortment of populations, in order to facilitate the process of selecting a minimal set of markers that could capture most of the signal from the untyped markers in a genome-wide association study. The central dogma can be summarized by the argument that if a marker is in tight LD with a polymorphism that directly impacts disease risk, as measured by the metric r(2), then one would be able to detect an association between the marker and disease with sample size that was increased by a factor of 1/r(2) over that needed to detect the effect of the functional variant directly. This "fundamental theorem" holds, however, only if one assumes that the LD between loci and the etiological effect of the functional variant are independent of each other, that they are statistically independent of all other etiological factors (in exposure and action), that sampling is prospective, and that the estimates of r(2) are accurate. None of these are standard operating assumptions, however. We describe the ramifications of these implicit assumptions, and provide simple examples in which the effects of a functional variant could be unequivocally detected if it were directly genotyped, even as markers in high LD with the functional variant would never show association with disease, even in infinite sample sizes. Both theoretical and empirical refutation of the central dogma of genome-wide association studies is thus presented.

A genome-wide screen for acrophobia susceptibility loci in a Finnish isolate.

Acrophobia, an abnormal fear of heights, is a specific phobia characterized as apprehension cued by the occurrence or anticipation of elevated spaces. It is considered a complex trait with onset influenced by both genetic and environmental factors. Identification of genetic risk variants would provide novel insight into the genetic basis of the fear of heights phenotype and contribute to the molecular-level understanding of its aetiology. Genetic isolates may facilitate identification of susceptibility alleles due to reduced genetic heterogeneity. We took advantage of an internal genetic isolate in Finland in which a distinct acrophobia phenotype appears to be segregating in pedigrees originally ascertained for schizophrenia. We conducted parametric, nonparametric, joint linkage and linkage disequilibrium analyses using a microsatellite marker panel, genotyped in families to search for chromosomal regions correlated with acrophobia. Our results implicated a few regions with suggestive evidence for linkage on chromosomes 4q28 (LOD = 2.17), 8q24 (LOD = 2.09) and 13q21-q22 (LOD = 2.22). We observed no risk haplotypes shared between different families. These results suggest that genetic predisposition to acrophobia in this genetic isolate is unlikely to be mediated by a small number of shared high-risk alleles, but rather has a complex genetic architecture.

AMIGO-Kv2.1 Potassium Channel Complex Is Associated With Schizophrenia-Related Phenotypes.

The enormous variability in electrical properties of neurons is largely affected by a multitude of potassium channel subunits. Kv2.1 is a widely expressed voltage-dependent potassium channel and an important regulator of neuronal excitability. The Kv2.1 auxiliary subunit AMIGO constitutes an integral part of the Kv2.1 channel complex in brain and regulates the activity of the channel. AMIGO and Kv2.1 localize to the distinct somatodendritic clusters at the neuronal plasma membrane. Here we have created and characterized a mouse line lacking the AMIGO gene. Absence of AMIGO clearly reduced the amount of the Kv2.1 channel protein in mouse brain and altered the electrophysiological properties of neurons. These changes were accompanied by behavioral and pharmacological abnormalities reminiscent of those identified in schizophrenia. Concomitantly, we have detected an association of a rare, population-specific polymorphism of KV2.1 (KCNB1) with human schizophrenia in a genetic isolate enriched with schizophrenia. Our study demonstrates the involvement of AMIGO-Kv2.1 channel complex in schizophrenia-related behavioral domains in mice and identifies KV2.1 (KCNB1) as a strong susceptibility gene for schizophrenia spectrum disorders in humans.

AUTOGSCAN: powerful tools for automated genome-wide linkage and linkage disequilibrium analysis.

Genome-wide linkage analysis using multiple traits and statistical software packages is a tedious process which requires a significant amount of manual file manipulation. Different linkage analysis programs require different input file formats, making the task of analyzing data with multiple methods even more time-consuming. We have developed a software tool, AUTOGSCAN, that automates file formatting, the running of statistical analyses, and the summarizing of resulting statistics for whole genome scans with a push of a button, using several independent, and often idiosyncratic, statistical software packages such as MERLIN, SOLAR and GENEHUNTER. We also describe a program, ANALYZE, designed to run qualitative linkage analysis with several different statistical strategies and programs to efficiently screen for linkage and linkage disequilibrium for a given discrete trait. The ANALYZE program can also be used by AUTOGSCAN in a genome-wide sense.