Christian Benner

FINEMAP: efficient variable selection using summary data from genome-wide association studies

Motivation: The goal of fine-mapping in genomic regions associated with complex diseases and traits is to identify causal variants that point to molecular mechanisms behind the associations. Recent fine-mapping methods using summary data from genome-wide association studies rely on exhaustive search through all possible causal configurations, which is computationally expensive. Results: We introduce FINEMAP, a software package to efficiently explore a set of the most important causal configurations of the region via a shotgun stochastic search algorithm. We show that FINEMAP produces accurate results in a fraction of processing time of existing approaches and is therefore a promising tool for analyzing growing amounts of data produced in genome-wide association studies and emerging sequencing projects. Availability and implementation: FINEMAP v1.0 is freely available for Mac OS X and Linux at http://www.christianbenner.com. Contact: christian.benner@helsinki.fi or matti.pirinen@helsinki.fi

Genome-Wide Analysis of Evolutionary Markers of Human Influenza A(H1N1)pdm09 and A(H3N2) Viruses May Guide Selection of Vaccine Strain Candidates.

Here we analyzed whole-genome sequences of 3,969 influenza A(H1N1)pdm09 and 4,774 A(H3N2) strains that circulated during 2009–2015 in the world. The analysis revealed changes at 481 and 533 amino acid sites in proteins of influenza A(H1N1)pdm09 and A(H3N2) strains, respectively. Many of these changes were introduced as a result of random drift. However, there were 61 and 68 changes that were present in relatively large number of A(H1N1)pdm09 and A(H3N2) strains, respectively, that circulated during relatively long time. We named these amino acid substitutions evolutionary markers, as they seemed to contain valuable information regarding the viral evolution. Interestingly, influenza A(H1N1)pdm09 and A(H3N2) viruses acquired non-overlapping sets of evolutionary markers. We next analyzed these characteristic markers in vaccine strains recommended by the World Health Organization for the past five years. Our analysis revealed that vaccine strains carried only few evolutionary markers at antigenic sites of viral hemagglutinin (HA) and neuraminidase (NA). The absence of these markers at antigenic sites could affect the recognition of HA and NA by human antibodies generated in response to vaccinations. This could, in part, explain moderate efficacy of influenza vaccines during 2009–2014. Finally, we identified influenza A(H1N1)pdm09 and A(H3N2) strains, which contain all the evolutionary markers of influenza A strains circulated in 2015, and which could be used as vaccine candidates for the 2015/2016 season. Thus, genome-wide analysis of evolutionary markers of influenza A(H1N1)pdm09 and A(H3N2) viruses may guide selection of vaccine strain candidates.

Prospects of Fine-Mapping Trait-Associated Genomic Regions by Using Summary Statistics from Genome-wide Association Studies

During the past few years, various novel statistical methods have been developed for fine-mapping with the use of summary statistics from genome-wide association studies (GWASs). Although these approaches require information about the linkage disequilibrium (LD) between variants, there has not been a comprehensive evaluation of how estimation of the LD structure from reference genotype panels performs in comparison with that from the original individual-level GWAS data. Using population genotype data from Finland and the UK Biobank, we show here that a reference panel of 1,000 individuals from the target population is adequate for a GWAS cohort of up to 10,000 individuals, whereas smaller panels, such as those from the 1000 Genomes Project, should be avoided. We also show, both theoretically and empirically, that the size of the reference panel needs to scale with the GWAS sample size; this has important consequences for the application of these methods in ongoing GWAS meta-analyses and large biobank studies. We conclude by providing software tools and by recommending practices for sharing LD information to more efficiently exploit summary statistics in genetics research.

Comparative Analysis of Whole-Genome Sequences of Influenza A(H1N1)pdm09 Viruses Isolated from Hospitalized and Nonhospitalized Patients Identifies Missense Mutations That Might Be Associated with Patient Hospital Admissions in Finland during 2009 to 2014

ABSTRACT Here, we report 40 new whole-genome sequences of influenza A(H1N1)pdm09 viruses isolated from Finnish patients during 2009 to 2014. A preliminary analysis of these and 186 other whole genomes of influenza A(H1N1)pdm09 viruses isolated from hospitalized and nonhospitalized patients during 2009 to 2014 in Finland revealed several viral mutations that might be associated with patient hospitalizations.

Genome-Wide Meta-Analysis of Sciatica in Finnish Population

Sciatica or the sciatic syndrome is a common and often disabling low back disorder in the working-age population. It has a relatively high heritability but poorly understood molecular mechanisms. The Finnish population is a genetic isolate where small founder population and bottleneck events have led to enrichment of certain rare and low frequency variants. We performed here the first genome-wide association (GWAS) and meta-analysis of sciatica. The meta-analysis was conducted across two GWAS covering 291 Finnish sciatica cases and 3671 controls genotyped and imputed at 7.7 million autosomal variants. The most promising loci (p<1x10-6) were replicated in 776 Finnish sciatica patients and 18,489 controls. We identified five intragenic variants, with relatively low frequencies, at two novel loci associated with sciatica at genome-wide significance. These included chr9:14344410:I (rs71321981) at 9p22.3 (NFIB gene; p = 1.30x10-8, MAF = 0.08) and four variants at 15q21.2: rs145901849, rs80035109, rs190200374 and rs117458827 (MYO5A; p = 1.34x10-8, MAF = 0.06; p = 2.32x10-8, MAF = 0.07; p = 3.85x10-8, MAF = 0.06; p = 4.78x10-8, MAF = 0.07, respectively). The most significant association in the meta-analysis, a single base insertion rs71321981 within the regulatory region of the transcription factor NFIB, replicated in an independent Finnish population sample (p = 0.04). Despite identifying 15q21.2 as a promising locus, we were not able to replicate it. It was differentiated; the lead variants within 15q21.2 were more frequent in Finland (6–7%) than in other European populations (1–2%). Imputation accuracies of the three significantly associated variants (chr9:14344410:I, rs190200374, and rs80035109) were validated by genotyping. In summary, our results suggest a novel locus, 9p22.3 (NFIB), which may be involved in susceptibility to sciatica. In addition, another locus, 15q21.2, emerged as a promising one, but failed to replicate.

Genetic Loci Associated with Allergic Sensitization in Lithuanians

Allergic rhinitis (AR) is a common and complex disease. It is associated with environmental as well as genetic factors. Three recent genome-wide association studies (GWAS) reported altogether 47 single nucleotide polymorphisms (SNPs) associated with AR or allergic sensitization (AS) in Europeans and North Americans. Two follow up studies in Swedish and Chinese replicated 15 associations. In these studies individuals were selected based on the self-reported AR, or AR/AS diagnosed using blood IgE test or skin prick test (SPT), which were performed often without restriction to specific allergens. Here we performed third replication study in Lithuanians. We used SPT and carefully selected set of allergens prevalent in Lithuania, as well as Illumina Core Exome chip for SNP detection. We genotyped 270 SPT-positive individuals (137 Betulaceae -, 174 Poaceae-, 199 Artemisia-, 70 Helianthus-, 22 Alternaria-, 22 Cladosporium-, 140 mites-, 95 cat- and 97 dog dander-sensitive cases) and 162 SPT-negative controls. We found altogether 13 known SNPs associated with AS (p ≤0.05). Three SNPs were found in Lithuanians sensitive to several allergens, and 10 SNPs were found in Lithuanians sensitive to a certain allergen. For the first time, SNP rs7775228:C was associated with patient sensitivity to dog allergens (F_A=0,269, F_U=0.180, P=0.008). Thus, careful assessment of AS allowed us to detect known genetic variants associated with AS/AR in relatively small cohort of Lithuanians.

Refining fine-mapping: effect sizes and regional heritability

Recent statistical approaches have shown that the set of all available genetic variants explains considerably more phenotypic variance of complex traits and diseases than the individual variants that are robustly associated with these phenotypes. However, rapidly increasing sample sizes constantly improve detection and prioritization of individual variants driving the associations between genomic regions and phenotypes. Therefore, it is useful to routinely estimate how much phenotypic variance the detected variants explain for each region by taking into account the correlation structure of variants and the uncertainty in their causal status. Here we extend the FINEMAP software to estimate the effect sizes and regional heritability under the probabilistic model that assumes a handful of causal variants per each region. Using the UK Biobank data to simulate GWAS regions with only a few causal variants, we demonstrate that FINEMAP provides higher precision and enables more detailed decomposition of regional heritability into individual variants than the variance component model implemented in BOLT or the fixed-effect model implemented in HESS. Using data from 51 serum biomarkers and four lipid traits from the FINRISK study, we estimate that FINEMAP captures on average 24% more regional heritability than the variant with the lowest P-value alone and 20% less than BOLT. Our simulations suggest how an upward bias of BOLT and a downward bias of FINEMAP could together explain the observed difference between the methods. We conclude that FINEMAP enables computationally efficient estimation of effect sizes and regional heritability in the era of biobank scale data.

Interrogation of human hematopoiesis at single-cell and single-variant resolution

Incomplete annotation of cell-to-cell state variance and widespread linkage disequilibrium in the human genome represent significant challenges to elucidating mechanisms of trait-associated genetic variation. Here, using data from the UK Biobank, we perform genetic fine-mapping for 16 blood cell traits to quantify posterior probabilities of association while allowing for multiple independent signals per region. We observe an enrichment of fine-mapped variants in accessible chromatin of lineage-committed hematopoietic progenitor cells. Further, we develop a novel analytic framework that identifies “core gene” cell type enrichments and show that this approach uniquely resolves relevant cell types within closely related populations. Applying our approach to single cell chromatin accessibility data, we discover significant heterogeneity within classically defined multipotential progenitor populations. Finally, using several lines of empirical evidence, we identify relevant cell types, predict target genes, and propose putative causal mechanisms for fine-mapped variants. In total, our study provides an analytic framework for single-variant and single-cell analyses to elucidate putative causal variants and cell types from GWAS and high-resolution epigenomic assays.

Non-operative meningiomas: long-term follow-up of 136 patients

BackgroundImproving access to neuroradiology investigations has led to an increased rate of diagnosis of incidental meningiomas.MethodA cohort of 136 incidental meningioma patients collected by a single neurosurgeon in a single neurosurgical centre is retrospectively analysed between 2002 and 2016. Demographic data, imaging and clinical features are presented. The radiological factors associated with meningiomas progression are also presented.ResultsThe mean age at diagnosis was 65 (range, 33–94) years. Univariate analysis showed oedema was most strongly correlated with progression (p = 0.010) followed by hyperintensity in T2-weighted (T2W) MRI (p = 0.029) and in Flair-T2W MRI (p = 0.017). Isointensity in Flair-T2W MRI (0.004) was most strongly correlated with non-progression of the meningioma followed by calcification (p = 0.007), older age (p = 0.087), hypointensity in Flair-T2W MRI (p = 0.014) sequences and in T2W MRI (p = 0.096). In multivariate analysis, the strongest radiological factor predictive of progression was peritumoural oedema (p = 0.016) and that of non-progression was calcification (p = 0.002). At the end of the median follow-up (FU) of 43 (range, 4–150) months, 109 (80%) patients remained clinically stable, 13 (10%) became symptomatic and 14 (10%) showed clinical and radiological progression.ConclusionsOne hundred and nine (80%) patients remained stable at the end of FU. Peritumoural oedema was predictive of meningiomas progression. Further prospective study is needed to identify the combination of factors which can predict the meningioma progression for an early surgery or early discharge.

biMM: efficient estimation of genetic variances and covariances for cohorts with high-dimensional phenotype measurements

Summary: Genetic research utilizes a decomposition of trait variances and covariances into genetic and environmental parts. Our software package biMM is a computationally efficient implementation of a bivariate linear mixed model for settings where hundreds of traits have been measured on partially overlapping sets of individuals. Availability and Implementation: Implementation in R freely available at www.iki.fi/mpirinen. Contact: matti.pirinen@helsinki.fi Supplementary information: Supplementary data are available at Bioinformatics online.