bioRxiv ScienceSearch

Biology subjects

Sekar Kathiresan

Publications and source records attributed to Sekar Kathiresan.

4 recordsLinked to original sources

Comprehensive population-based genome sequencing provides insight into hematopoietic regulatory mechanisms

Genetic variants affecting hematopoiesis can influence commonly measured blood cell traits. To identify factors that affect hematopoiesis, we performed association studies for blood cell traits in the population-based Estonian Biobank using high coverage whole genome sequencing (WGS) in 2,284 samples and SNP genotyping in an additional ~17,000 samples. Our analyses identified 17 associations across 14 blood cell traits. Integration of WGS-based fine-mapping and complementary epigenomic data sets provided evidence for causal mechanisms at several loci, including at a novel basophil count-associated locus near the master hematopoietic transcription factor CEBPA. The fine-mapped variant at this basophil count association near CEBPA overlapped an enhancer active in common myeloid progenitors and influenced its activity. In situ perturbation of this enhancer by CRISPR/Cas9 mutagenesis in hematopoietic stem and progenitor cells demonstrated that it is necessary for and specifically regulates CEBPA expression during basophil differentiation. We additionally identified basophil count-associated variation at another more pleiotropic myeloid enhancer near GATA2, highlighting regulatory mechanisms for ordered expression of master hematopoietic regulators during lineage specification. Our study illustrates how population-based genetic studies can provide key insights into poorly understood cell differentiation processes of considerable physiologic relevance.

Genetics

Ultra-rare disruptive and damaging mutations influence educational attainment in the general population

Ultra-rare inherited and de novo disruptive variants in highly constrained (HC) genes are enriched in neurodevelopmental disorders 1-5. However, their impact on cognition in the general population has not been explored. We hypothesize that disruptive and damaging ultra-rare variants (URVs) in HC genes not only confer risk to neurodevelopmental disorders, but also influence general cognitive abilities measured indirectly by years of education (YOE). We tested this hypothesis in 14,133 individuals with whole exome or genome sequencing data. The presence of one or more URVs was associated with a decrease in YOE (3.1 months less for each additional mutation; P-value=3.3x10-8) and the effect was stronger in HC genes enriched for brain expression (6.5 months less, P-value=3.4x10-5). The effect of these variants was more pronounced than the estimated effects of runs of homozygosity and pathogenic copy number variation 6-9. Our findings suggest that effects of URVs in HC genes are not confined to severe neurodevelopmental disorder, but influence the cognitive spectrum in the general population

Genetics

Human knockouts in a cohort with a high rate of consanguinity

A major goal of biomedicine is to understand the function of every gene in the human genome.1 Null mutations can disrupt both copies of a given gene in humans and phenotypic analysis of such human knockouts can provide insight into gene function. To date, comprehensive analysis of genes knocked out in humans has been limited by the fact that null mutations are infrequent in the general population and so, observing an individual homozygous null for a given gene is exceedingly rare.2,3 However, consanguineous unions are more likely to result in offspring who carry homozygous null mutations. In Pakistan, consanguinity rates are notably high.4 Here, we sequenced the protein-coding regions of 7,078 adult participants living in Pakistan and performed phenotypic analysis to identify homozygous null individuals and to understand consequences of complete gene disruption in humans. We enumerated 36,850 rare (<1 % minor allele frequency) null mutations. These homozygous null mutations led to complete inactivation of 961 genes in at least one participant. Homozygosity for null mutations at APOC3 was associated with absent plasma apolipoprotein C-III levels; at PLAG27, with absent enzymatic activity of soluble lipoprotein-associated phospholipase A2; at CYP2F1, with higher plasma interleukin-8 concentrations; and at either A3GALT2 or NRG4, with markedly reduced plasma insulin C-peptide concentrations. After physiologic challenge with oral fat, APOC3 knockouts displayed marked blunting of the usual post-prandial rise in plasma triglycerides compared to wild-type family members. These observations provide a roadmap to understand the consequences of complete disruption of a large fraction of genes in the human genome.

Genomics

Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores

Polygenic risk scores have shown great promise in predicting complex disease risk, and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves LD-pruning markers and applying a P-value threshold to association statistics, but this discards information and may reduce predictive accuracy. We introduce a new method, LDpred, which infers the posterior mean causal effect size of each marker using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the pruning/thresholding approach, particularly at large sample sizes. Accordingly, prediction R2 increased from 20.1% to 25.3% in a large schizophrenia data set and from 9.8% to 12.0% in a large multiple sclerosis data set. A similar relative improvement in accuracy was observed for three additional large disease data sets and when predicting in non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase.

Bioinformatics