Fundamentals for predicting transcriptional regulations from DNA sequence patterns.

Cell-type-specific regulatory elements, cataloged through extensive experiments and bioinformatics in large-scale consortiums, have enabled enrichment analyses of genetic associations that primarily utilize positional information of the regulatory elements. These analyses have identified cell types and pathways genetically associated with human complex traits. However, our understanding of detailed allelic effects on these elements' activities and on-off states remains incomplete, hampering the interpretation of human genetic study results. This review introduces machine learning methods to learn sequence-dependent transcriptional regulation mechanisms from DNA sequences for predicting such allelic effects (not associations). We provide a concise history of machine-learning-based approaches, the requirements, and the key computational processes, focusing on primers in machine learning. Convolution and self-attention, pivotal in modern deep-learning models, are explained through geometrical interpretations using dot products. This facilitates understanding of the concept and why these have been used for machine learning for DNA sequences. These will inspire further research in this genetics and genomics field.

Decoding triancestral origins, archaic introgression, and natural selection in the Japanese population by whole-genome sequencing.

We generated Japanese Encyclopedia of Whole-Genome/Exome Sequencing Library (JEWEL), a high-depth whole-genome sequencing dataset comprising 3256 individuals from across Japan. Analysis of JEWEL revealed genetic characteristics of the Japanese population that were not discernible using microarray data. First, rare variant-based analysis revealed an unprecedented fine-scale genetic structure. Together with population genetics analysis, the present-day Japanese can be decomposed into three ancestral components. Second, we identified unreported loss-of-function (LoF) variants and observed that for specific genes, LoF variants appeared to be restricted to a more limited set of transcripts than would be expected by chance, with PTPRD as a notable example. Third, we identified 44 archaic segments linked to complex traits, including a Denisovan-derived segment at NKX6-1 associated with type 2 diabetes. Most of these segments are specific to East Asians. Fourth, we identified candidate genetic loci under recent natural selection. Overall, our work provided insights into genetic characteristics of the Japanese population.

GWAS for systemic sclerosis identifies six novel susceptibility loci including one in the Fcγ receptor region.

Here we report the largest Asian genome-wide association study (GWAS) for systemic sclerosis performed to date, based on data from Japanese subjects and comprising of 1428 cases and 112,599 controls. The lead SNP is in the FCGR/FCRL region, which shows a penetrating association in the Asian population, while a complete linkage disequilibrium SNP, rs10917688, is found in a cis-regulatory element for IRF8. IRF8 is also a significant locus in European GWAS for systemic sclerosis, but rs10917688 only shows an association in the presence of the risk allele of IRF8 in the Japanese population. Further analysis shows that rs10917688 is marked with H3K4me1 in primary B cells. A meta-analysis with a European GWAS detects 30 additional significant loci. Polygenic risk scores constructed with the effect sizes of the meta-analysis suggest the potential portability of genetic associations beyond populations. Prioritizing the top 5% of SNPs of IRF8 binding sites in B cells improves the fitting of the polygenic risk scores, underscoring the roles of B cells and IRF8 in the development of systemic sclerosis. The results also suggest that systemic sclerosis shares a common genetic architecture across populations.

Androgen receptor binding sites enabling genetic prediction of mortality due to prostate cancer in cancer-free subjects.

Prostate cancer (PrCa) is the second most common cancer worldwide in males. While strongly warranted, the prediction of mortality risk due to PrCa, especially before its development, is challenging. Here, we address this issue by maximizing the statistical power of genetic data with multi-ancestry meta-analysis and focusing on binding sites of the androgen receptor (AR), which has a critical role in PrCa. Taking advantage of large Japanese samples ever, a multi-ancestry meta-analysis comprising more than 300,000 subjects in total identifies 9 unreported loci including ZFHX3, a tumor suppressor gene, and successfully narrows down the statistically finemapped variants compared to European-only studies, and these variants strongly enrich in AR binding sites. A polygenic risk scores (PRS) analysis restricting to statistically finemapped variants in AR binding sites shows among cancer-free subjects, individuals with a PRS in the top 10% have a strongly higher risk of the future death of PrCa (HR: 5.57, P = 4.2 × 10-10). Our findings demonstrate the potential utility of leveraging large-scale genetic data and advanced analytical methods in predicting the mortality of PrCa.

Genetic insights into ossification of the posterior longitudinal ligament of the spine.

Ossification of the posterior longitudinal ligament of the spine (OPLL) is an intractable disease leading to severe neurological deficits. Its etiology and pathogenesis are primarily unknown. The relationship between OPLL and comorbidities, especially type 2 diabetes (T2D) and high body mass index (BMI), has been the focus of attention; however, no trait has been proven to have a causal relationship. We conducted a meta-analysis of genome-wide association studies (GWASs) using 22,016 Japanese individuals and identified 14 significant loci, 8 of which were previously unreported. We then conducted a gene-based association analysis and a transcriptome-wide Mendelian randomization approach and identified three candidate genes for each. Partitioning heritability enrichment analyses observed significant enrichment of the polygenic signals in the active enhancers of the connective/bone cell group, especially H3K27ac in chondrogenic differentiation cells, as well as the immune/hematopoietic cell group. Single-cell RNA sequencing of Achilles tendon cells from a mouse Achilles tendon ossification model confirmed the expression of genes in GWAS and post-GWAS analyses in mesenchymal and immune cells. Genetic correlations with 96 complex traits showed positive correlations with T2D and BMI and a negative correlation with cerebral aneurysm. Mendelian randomization analysis demonstrated a significant causal effect of increased BMI and high bone mineral density on OPLL. We evaluated the clinical images in detail and classified OPLL into cervical, thoracic, and the other types. GWAS subanalyses identified subtype-specific signals. A polygenic risk score for BMI demonstrated that the effect of BMI was particularly strong in thoracic OPLL. Our study provides genetic insight into the etiology and pathogenesis of OPLL and is expected to serve as a basis for future treatment development.

Detection of trait-associated structural variations using short-read sequencing.

Genomic structural variation (SV) affects genetic and phenotypic characteristics in diverse organisms, but the lack of reliable methods to detect SV has hindered genetic analysis. We developed a computational algorithm (MOPline) that includes missing call recovery combined with high-confidence SV call selection and genotyping using short-read whole-genome sequencing (WGS) data. Using 3,672 high-coverage WGS datasets, MOPline stably detected ∼16,000 SVs per individual, which is over ∼1.7-3.3-fold higher than previous large-scale projects while exhibiting a comparable level of statistical quality metrics. We imputed SVs from 181,622 Japanese individuals for 42 diseases and 60 quantitative traits. A genome-wide association study with the imputed SVs revealed 41 top-ranked or nearly top-ranked genome-wide significant SVs, including 8 exonic SVs with 5 novel associations and enriched mobile element insertions. This study demonstrates that short-read WGS data can be used to identify rare and common SVs associated with a variety of traits.

Genotype imputation accuracy and the quality metrics of the minor ancestry in multi-ancestry reference panels.

Large-scale imputation reference panels are currently available and have contributed to efficient genome-wide association studies through genotype imputation. However, whether large-size multi-ancestry or small-size population-specific reference panels are the optimal choices for under-represented populations continues to be debated. We imputed genotypes of East Asian (180k Japanese) subjects using the Trans-Omics for Precision Medicine reference panel and found that the standard imputation quality metric (Rsq) overestimated dosage r2 (squared correlation between imputed dosage and true genotype) particularly in marginal-quality bins. Variance component analysis of Rsq revealed that the increased imputed-genotype certainty (dosages closer to 0, 1 or 2) caused upward bias, indicating some systemic bias in the imputation. Through systematic simulations using different template switching rates (θ value) in the hidden Markov model, we revealed that the lower θ value increased the imputed-genotype certainty and Rsq; however, dosage r2 was insensitive to the θ value, thereby causing a deviation. In simulated reference panels with different sizes and ancestral diversities, the θ value estimates from Minimac decreased with the size of a single ancestry and increased with the ancestral diversity. Thus, Rsq could be deviated from dosage r2 for a subpopulation in the multi-ancestry panel, and the deviation represents different imputed-dosage distributions. Finally, despite the impact of the θ value, distant ancestries in the reference panel contributed only a few additional variants passing a predefined Rsq threshold. We conclude that the θ value substantially impacts the imputed dosage and the imputation quality metric value.

Multi-ancestry genome-wide association analyses identify novel genetic mechanisms in rheumatoid arthritis.

Rheumatoid arthritis (RA) is a highly heritable complex disease with unknown etiology. Multi-ancestry genetic research of RA promises to improve power to detect genetic signals, fine-mapping resolution and performances of polygenic risk scores (PRS). Here, we present a large-scale genome-wide association study (GWAS) of RA, which includes 276,020 samples from five ancestral groups. We conducted a multi-ancestry meta-analysis and identified 124 loci (P < 5 × 10-8), of which 34 are novel. Candidate genes at the novel loci suggest essential roles of the immune system (for example, TNIP2 and TNFRSF11A) and joint tissues (for example, WISP1) in RA etiology. Multi-ancestry fine-mapping identified putatively causal variants with biological insights (for example, LEF1). Moreover, PRS based on multi-ancestry GWAS outperformed PRS based on single-ancestry GWAS and had comparable performance between populations of European and East Asian ancestries. Our study provides several insights into the etiology of RA and improves the genetic predictability of RA.

Genome-wide association study of colorectal polyps identified highly overlapping polygenic architecture with colorectal cancer.

No genome-wide association studies (GWAS) were reported for colorectal polyps and the overlap in polygenic backgrounds conferring risk of colorectal cancer and polyps remains unclear. We performed GWAS on subjects with colorectal polyps using the BioBank Japan data with 4447 cases and 157,226 controls. We evaluated genetic correlations between colorectal polyps and cancer, and effects on colorectal polyps of single nucleotide polymorphisms (SNPs) known to be associated with colorectal cancer. We identified CUX2, a known genetic locus to colorectal cancer, as a susceptibility locus to colorectal polyps (p value = 1.1 × 10-15). Subsequent fine-mapping analysis indicated that rs11065828 in CUX2 is the causal variant for colorectal polyps. We found that known colorectal cancer-susceptible SNPs were also associated with colorectal polyps. The genetic correlation between colorectal cancer and polyps is very high (r = 0.98 and p value = 0.0006). We additionally identified 14 significant loci of colorectal polyps and three significant loci of colorectal cancer by applying the multi-trait analysis of GWAS of colorectal cancer and colorectal polyps. We showed very similar germline polygenic features, which gives us the additional insight into potential cancers at polygenic levels for patients with polyps who are followed up at outpatients' clinic; thus, close observation and polypectomy is critical to prevent colorectal cancers.

Novel susceptibility loci for steroid-associated osteonecrosis of the femoral head in systemic lupus erythematosus.

Osteonecrosis of the femoral head (ONFH) involves necrosis of bone and bone marrow of the femoral head caused by ischemia with unknown etiology. Previous genetic studies on ONFH failed to produce consistent results, presumably because ONFH has various causes with different genetic backgrounds and the underlying diseases confounded the associations. Steroid-associated ONFH (S-ONFH) accounts for one-half of all ONFH, and systemic lupus erythematosus (SLE) is a representative disease underlying S-ONFH. We performed a genome-wide association study (GWAS) to identify genetic risk factors for S-ONFH in patients with SLE. We conducted a two-staged GWAS on 636 SLE patients with S-ONFH and 95 588 non-SLE controls. Among the novel loci identified, we determined S-ONFH-specific loci by comparing allele frequencies between SLE patients without S-ONFH and non-SLE controls. We also used Korean datasets comprising 148 S-ONFH cases and 37 015 controls to assess overall significance. We evaluated the functional annotations of significant variants by in silico analyses. The Japanese GWAS identified 4 significant loci together with 12 known SLE susceptibility loci. The four significant variants showed comparable effect sizes on S-ONFH compared with SLE controls and non-SLE controls. Three of the four loci, MIR4293/MIR1265 [odds ratio (OR) = 1.99, P-value = 1.1 × 10-9)], TRIM49/NAALAD2 (OR = 1.65, P-value = 4.8 × 10-8) and MYO16 (OR = 3.91, P-value = 4.9 × 10-10), showed significant associations in the meta-analysis with Korean datasets. Bioinformatics analyses identified MIR4293, NAALAD2 and MYO16 as candidate causal genes. MIR4293 regulates a PPARG-related adipogenesis pathway relevant to S-ONFH. We identified three novel susceptibility loci for S-ONFH in SLE.

Susceptibility loci and polygenic architecture highlight population specific and common genetic features in inguinal hernias: genetics in inguinal hernias.

BACKGROUND: The underlying pathology of inguinal hernia is still not fully known; thus, further investigations of genetic backgrounds is needed. Here, we aimed to identify genetic factors attributing to inguinal hernias and explore the polygenic architecture of which some components are population-specific, while others are more common among populations. METHODS: We performed a genome-wide association study (GWAS) on subjects with inguinal hernias using BioBank Japan (BBJ) data with 1,983 cases and 172,507 controls, followed by a trans-ethnic meta-analysis with UK Biobank (UKBB) data. We performed downstream analyses in order to identify the mechanisms underlying inguinal hernias supported by genetic findings. FINDINGS: We identified a locus closest to ELN, which encodes elastin, at the GWAS significant level. The trans-ethnic meta-analysis revealed 23 additional significant loci, including five loci newly identified not significant in BBJ or UKBB GWAS: TGFB2, RNA5SP214/VGLL2, LOC646588, HMCN2, and ATP5F1CP1/CDKN3. Downstream analyses revealed the overlap of GWAS significant signals in extracellular components, including elastin fiber formation. We also found a highly shared polygenic architecture across different populations (trans-ethnic genetic-effect correlation = 0•77, standard error = 0•26) and population-specific lead variants in ELN, indicating the critical role of elastin in inguinal hernias. INTERPRETATION: We identified a significant locus of the ELN gene in the Japanese population and five additional loci across different populations. Downstream analyses revealed highly shared genetic architectures across populations and highlighted the important roles of extracellular components in the development of inguinal hernias. These findings deepen our understanding of the mechanisms underlying inguinal hernia. FUNDING: The Japan Agency for Medical Research and Development (AMED) (Grant Number: JP19km0605001).