Allele-Specific Regulation of the Candidate Autism Liability Gene RAI1 by the Enhancer Variant rs4925102 (C/G).

Retinoic acid-induced 1 (RAI1) is a dosage-sensitive gene that causes autistic phenotypes when deleted or duplicated. Observations from clinical cases and animal models also suggest that changes of RAI1 expression levels contribute to autism. Previously, we used a bioinformatic approach to identify several single nucleotide polymorphisms (SNPs) located within the 5'-region of RAI1 that correlate with RAI1 mRNA expression in the human brain. In particular, the SNP rs4925102 was identified as a candidate cis-acting regulatory variant, the genotype of which may affect the binding of transcription factors that influence RAI1 mRNA expression. In this study, we provide experimental evidence based on reporter gene, chromatin immunoprecipitation (ChIP), and chromatin conformation capture (3C) assays that rs4925102 regulates RAI1 mRNA expression in an allele-specific manner in human cell lines, including the neuroblastoma-derived cell line SH-SY5Y. We also describe a statistically significant association between rs4925102 genotype and autism spectrum disorder (ASD) diagnosis in a case-control study and near-statistically significant association in an Autism Genome Project (AGP) transmission disequilibrium (TDT) study using Caucasian subjects.

sscNOVA: a semi-supervised convolutional neural network for predicting functional regulatory variants in autoimmune diseases.

Genome-wide association studies (GWAS) have identified thousands of variants in the human genome with autoimmune diseases. However, identifying functional regulatory variants associated with autoimmune diseases remains challenging, largely because of insufficient experimental validation data. We adopt the concept of semi-supervised learning by combining labeled and unlabeled data to develop a deep learning-based algorithm framework, sscNOVA, to predict functional regulatory variants in autoimmune diseases and analyze the functional characteristics of these regulatory variants. Compared to traditional supervised learning methods, our approach leverages more variants' data to explore the relationship between functional regulatory variants and autoimmune diseases. Based on the experimentally curated testing dataset and evaluation metrics, we find that sscNOVA outperforms other state-of-the-art methods. Furthermore, we illustrate that sscNOVA can help to improve the prioritization of functional regulatory variants from lead single-nucleotide polymorphisms and the proxy variants in autoimmune GWAS data.

Novel regulatory variant in ABO intronic RUNX1 binding site inducing A3 phenotype.

BACKGROUND AND OBJECTIVES: Mixed-field agglutination in ABO phenotyping (A3, B3) has been linked to genetically different blood cell populations such as in chimerism, or to rare variants in either ABO exon 7 or regulatory regions. Clarification of such cases is challenging and would greatly benefit from sequencing technologies that allow resolving full-gene haplotypes at high resolution. MATERIALS AND METHODS: We used long-read sequencing by Oxford Nanopore Technologies to sequence the entire ABO gene, amplified in two overlapping long-range PCR fragments, in a blood donor presented with A3B phenotype. Confirmation analyses were carried out by Sanger sequencing and included samples from other family members. RESULTS: Our data revealed a novel heterozygous g.10924C>A variant on the ABO*A allele located in the transcription factor binding site for RUNX1 in intron 1 (+5.8 kb site). Inheritance was shown by the results of the donor's mother, who shared the novel variant and the anti-A specific mixed-field agglutination. CONCLUSION: We discovered a regulatory variant in the 8-bp RUNX1 motif of ABO, which extends current knowledge of three other variants affecting the same motif and also leading to A3 or B3 phenotypes. Overall, long-range PCR combined with nanopore sequencing proved powerful and showed great potential as an emerging strategy for resolving cases with cryptic ABO phenotypes.

Systematic characterization of regulatory variants of blood pressure genes.

High blood pressure (BP) is the major risk factor for cardiovascular disease. Genome-wide association studies have identified genetic variants for BP, but functional insights into causality and related molecular mechanisms lag behind. We functionally characterize 4,608 genetic variants in linkage with 135 BP loci in vascular smooth muscle cells and cardiomyocytes by massively parallel reporter assays. High densities of regulatory variants at BP loci (i.e., ULK4, MAP4, CFDP1, PDE5A) indicate that multiple variants drive genetic association. Regulatory variants are enriched in repeats, alter cardiovascular-related transcription factor motifs, and spatially converge with genes controlling specific cardiovascular pathways. Using heuristic scoring, we define likely causal variants, and CRISPR prime editing finally determines causal variants for KCNK9, SFXN2, and PCGF6, which are candidates for developing high BP. Our systems-level approach provides a catalog of functionally relevant variants and their genomic architecture in two trait-relevant cell lines for a better understanding of BP gene regulation.

A Comprehensive Investigation of Genomic Variants in Prostate Cancer Reveals 30 Putative Regulatory Variants.

Prostate cancer (PC) is the most frequently diagnosed non-skin cancer in the world. Previous studies have shown that genomic alterations represent the most common mechanism for molecular alterations responsible for the development and progression of PC. This highlights the importance of identifying functional genomic variants for early detection in high-risk PC individuals. Great efforts have been made to identify common protein-coding genetic variations; however, the impact of non-coding variations, including regulatory genetic variants, is not well understood. Identification of these variants and the underlying target genes will be a key step in improving the detection and treatment of PC. To gain an understanding of the functional impact of genetic variants, and in particular, regulatory variants in PC, we developed an integrative pipeline (AGV) that uses whole genome/exome sequences, GWAS SNPs, chromosome conformation capture data, and ChIP-Seq signals to investigate the potential impact of genomic variants on the underlying target genes in PC. We identified 646 putative regulatory variants, of which 30 significantly altered the expression of at least one protein-coding gene. Our analysis of chromatin interactions data (Hi-C) revealed that the 30 putative regulatory variants could affect 131 coding and non-coding genes. Interestingly, our study identified the 131 protein-coding genes that are involved in disease-related pathways, including Reactome and MSigDB, for most of which targeted treatment options are currently available. Notably, our analysis revealed several non-coding RNAs, including RP11-136K7.2 and RAMP2-AS1, as potential enhancer elements of the protein-coding genes CDH12 and EZH1, respectively. Our results provide a comprehensive map of genomic variants in PC and reveal their potential contribution to prostate cancer progression and development.

Identification and functional characterization of a novel susceptibility locus for small vessel vasculitis with MPO-ANCA.

OBJECTIVE: To identify and characterize genetic loci associated with the risk of developing ANCA-associated vasculitides (AAV). METHODS: Genetic association analyses were performed after Illumina sequencing of 1853 genes and subsequent replication with genotyping of selected single nucleotide polymorphisms in a total cohort of 1110 Scandinavian cases with granulomatosis with polyangiitis or microscopic polyangiitis, and 1589 controls. A novel AAV-associated single nucleotide polymorphism was analysed for allele-specific effects on gene expression using luciferase reporter assay. RESULTS: PR3-ANCA+ AAV was significantly associated with two independent loci in the HLA-DPB1/HLA-DPA1 region [rs1042335, P = 6.3 × 10-61, odds ratio (OR) 0.10; rs9277341, P = 1.5 × 10-44, OR 0.22] and with rs28929474 in the SERPINA1 gene (P = 2.7 × 10-10, OR 2.9). MPO-ANCA+ AAV was significantly associated with the HLA-DQB1/HLA-DQA2 locus (rs9274619, P = 5.4 × 10-25, OR 3.7) and with a rare variant in the BACH2 gene (rs78275221, P = 7.9 × 10-7, OR 3.0), the latter a novel susceptibility locus for MPO-ANCA+ granulomatosis with polyangiitis/microscopic polyangiitis. The rs78275221-A risk allele reduced luciferase gene expression in endothelial cells, specifically, as compared with the non-risk allele. CONCLUSION: We identified a novel susceptibility locus for MPO-ANCA+ AAV and propose that the associated variant is of mechanistic importance, exerting a regulatory function on gene expression in specific cell types.

Chronic Pancreatitis: The True Pathogenic Culprit within the SPINK1 N34S-Containing Haplotype Is No Longer at Large.

A diverse range of loss-of-function variants in the SPINK1 gene (encoding pancreatic secretory trypsin inhibitor) has been identified in patients with chronic pancreatitis (CP). The haplotype harboring the SPINK1 c.101A>G (p.Asn34Ser or N34S) variant (rs17107315:T>C) is one of the most important heritable risk factors for CP as a consequence of its relatively high prevalence worldwide (population allele frequency ≈ 1%) and its considerable effect size (odds ratio ≈ 11). The causal variant responsible for this haplotype has been intensively investigated over the past two decades. The different hypotheses tested addressed whether the N34S missense variant has a direct impact on enzyme structure and function, whether c.101A>G could affect pre-mRNA splicing or mRNA stability, and whether another variant in linkage disequilibrium with c.101A>G might be responsible for the observed association with CP. Having reviewed the currently available genetic and experimental data, we conclude that c.-4141G>T (rs142703147:C>A), which disrupts a PTF1L-binding site within an evolutionarily conserved HNF1A-PTF1L cis-regulatory module located ∼4 kb upstream of the SPINK1 promoter, can be designated as the causal variant beyond reasonable doubt. This case illustrates the difficulties inherent in determining the identity of the causal variant underlying an initially identified disease association.

Regulatory variants in TCF7L2 are associated with thoracic aortic aneurysm.

Thoracic aortic aneurysm (TAA) is characterized by dilation of the aortic root or ascending/descending aorta. TAA is a heritable disease that can be potentially life threatening. While 10%-20% of TAA cases are caused by rare, pathogenic variants in single genes, the origin of the majority of TAA cases remains unknown. A previous study implicated common variants in FBN1 with TAA disease risk. Here, we report a genome-wide scan of 1,351 TAA-affected individuals and 18,295 control individuals from the Cardiovascular Health Improvement Project and Michigan Genomics Initiative at the University of Michigan. We identified a genome-wide significant association with TAA for variants within the third intron of TCF7L2 following replication with meta-analysis of four additional independent cohorts. Common variants in this locus are the strongest known genetic risk factor for type 2 diabetes. Although evidence indicates the presence of different causal variants for TAA and type 2 diabetes at this locus, we observed an opposite direction of effect. The genetic association for TAA colocalizes with an aortic eQTL of TCF7L2, suggesting a functional relationship. These analyses predict an association of higher expression of TCF7L2 with TAA disease risk. In vitro, we show that upregulation of TCF7L2 is associated with BCL2 repression promoting vascular smooth muscle cell apoptosis, a key driver of TAA disease.

Allele-Specific QTL Fine Mapping with PLASMA.

Although quantitative trait locus (QTL) associations have been identified for many molecular traits such as gene expression, it remains challenging to distinguish the causal nucleotide from nearby variants. In addition to traditional QTLs by association, allele-specific (AS) QTLs are a powerful measure of cis-regulation that are concordant with traditional QTLs but typically less susceptible to technical/environmental noise. However, existing methods for estimating causal variant probabilities (i.e., fine mapping) cannot produce valid estimates from asQTL signals due to complexities in linkage disequilibrium (LD). We introduce PLASMA (Population Allele-Specific Mapping), a fine-mapping method that integrates QTL and asQTL information to improve accuracy. In simulations, PLASMA accurately prioritizes causal variants over a wide range of genetic architectures. Applied to RNA-seq data from 524 kidney tumor samples, PLASMA achieves a greater power at 50 samples than conventional QTL-based fine mapping at 500 samples, with more than 17% of loci fine mapped to within five causal variants, compared to 2% by QTL-based fine mapping, and a 6.9-fold overall reduction in median credible set size compared to QTL-based fine mapping when applied to H3K27AC ChIP-seq from just 28 prostate tumor/normal samples. Variants in the PLASMA credible sets for RNA-seq and ChIP-seq were enriched for open chromatin and chromatin looping, respectively, at a comparable or greater degree than credible variants from existing methods while containing far fewer markers. Our results demonstrate how integrating AS activity can substantially improve the detection of causal variants from existing molecular data.

From Genetic Association to Molecular Mechanisms for Islet-cell Dysfunction in Type 2 Diabetes.

Genome-wide association studies (GWAS) have identified over 400 signals robustly associated with risk for type 2 diabetes (T2D). At the vast majority of these loci, the lead single nucleotide polymorphisms (SNPs) reside in noncoding regions of the genome, which hampers biological inference and translation of genetic discoveries into disease mechanisms. The study of these T2D risk variants in normoglycemic individuals has revealed that a significant proportion are exerting their disease risk through islet-cell dysfunction. The central role of the islet is also demonstrated by numerous studies, which have shown an enrichment of these signals in islet-specific epigenomic annotations. In recent years the emergence of authentic human beta-cell lines, and advances in genome-editing technologies coupled with improved protocols differentiating human pluripotent stem cells into beta-like cells has opened up new opportunities for T2D disease modeling. Here we review the current understanding on the genetic basis of T2D focusing on approaches, which have facilitated the identification of causal variants and their effector transcripts in human islets. We will present examples of functional studies based on animal and conventional cellular systems and highlight the potential of novel stem cell-based T2D disease models.

Sex-specific effects of a microsatellite polymorphism on human growth hormone receptor gene expression.

Growth hormone (GH) binds to its specific receptor (GHR) at the surface of target cells activating multiple signaling pathways implicated in growth and metabolism. Dysregulation of GHRs leads to pathophysiological states that most commonly affect stature. We previously showed the association of a polymorphic (n = 15-37) GT microsatellite in the human GHR gene promoter with short stature in a sex-specific manner. In the present study we evaluated the functional relevance of this polymorphism in regulating GHR expression. Using luciferase reporter assays, we found that the GT repeat had a significant cis regulatory effect in response to HIF1α and a potential repressor role following C/EBPß stimulation. Using a digital PCR application to measure allelic imbalance (AI), we showed a high prevalence of AI (∼76%) at the GHR locus in lymphoblastoid cell lines (LCLs), with a significantly higher degree of imbalance in LCLs derived from males. Examination of expression of GHR as well as other members of the GH-IGF1 axis in the LCLs revealed significant associations of GHR, IGF1 and BCL2 expression with GT genotype in a sex-specific manner. Our results suggest that this GT microsatellite exerts both cis and trans effects in a sex-specific context, revealing a new mechanism by which GHR gene expression is regulated.

Craniofrontonasal Syndrome Caused by Introduction of a Novel uATG in the 5'UTR of EFNB1.

Craniofrontonasal syndrome (CFNS) is an X-linked disorder caused by EFNB1 mutations in which females are more severely affected than males. Severe male phenotypes are associated with mosaicism, supporting cellular interference for sex bias in this disease. Although many variants have been found in the coding region of EFNB1, only 2 pathogenic variants have been identified in the same nucleotide in 5'UTR, disrupting the stop codon of an upstream open reading frame (uORF). uORFs are known to be part of a wide range of post-transcriptional regulation processes, and just recently, their association with human diseases has come to light. In the present study, we analyzed EFNB1 in a female patient with typical features of CFNS. We identified a variant, located at c.-411, creating a new upstream ATG (uATG) in the 5'UTR of EFNB1, which is predicted to alter an existing uORF. Dual-luciferase reporter assays showed significant reduction in protein translation, but no difference in the mRNA levels. Our study demonstrates, for the first time, the regulatory impact of uATG formation on EFNB1 levels and suggests that this should be the target region in molecular diagnosis of CFNS cases without pathogenic variants in the coding and splice sites regions of EFNB1.

Functional characterization of the C7ORF76 genomic region, a prominent GWAS signal for osteoporosis in 7q21.3.

Genome-wide association studies (GWAS) have repeatedly identified genetic variants associated with bone mineral density (BMD) and osteoporotic fracture in non-coding regions of C7ORF76, a poorly studied gene of unknown function. The aim of the present study was to elucidate the causality and molecular mechanisms underlying the association. We re-sequenced the genomic region in two extreme BMD groups from the BARCOS cohort of postmenopausal women to search for functionally relevant variants. Eight selected variants were tested for association in the complete cohort and 2 of them (rs4342521 and rs10085588) were found significantly associated with lumbar spine BMD and nominally associated with osteoporotic fracture. cis-eQTL analyses of these 2 SNPs, together with SNP rs4727338 (GWAS lead SNP in Estrada et al., Nat Genet. 44:491-501, 2012), performed in human primary osteoblasts, disclosed a statistically significant influence on the expression of the proximal neighbouring gene SLC25A13 and a tendency on the distal SHFM1. We then studied the functionality of a putative upstream regulatory element (UPE), containing rs10085588. Luciferase reporter assays showed transactivation capability with a strong allele-dependent effect. Finally, 4C-seq experiments in osteoblastic cell lines showed that the UPE interacted with different tissue-specific enhancers and a lncRNA (LOC100506136) in the region. In summary, this study is the first one to analyse in depth the functionality of C7ORF76 genomic region. We provide functional regulatory evidence for the rs10085588, which may be a causal SNP within the 7q21.3 GWAS signal for osteoporosis.

Functional SNPs in the Human Autoimmunity-Associated Locus 17q12-21.

Genome-wide association studies (GWASes) revealed several single-nucleotide polymorphisms (SNPs) in the human 17q12-21 locus associated with autoimmune diseases. However, follow-up studies are still needed to identify causative SNPs directly mediating autoimmune risk in the locus. We have chosen six SNPs in high linkage disequilibrium with the GWAS hits that showed the strongest evidence of causality according to association pattern and epigenetic data and assessed their functionality in a local genomic context using luciferase reporter system. We found that rs12946510, rs4795397, rs12709365, and rs8067378 influenced the reporter expression level in leukocytic cell lines. The strongest effect visible in three distinct cell types was observed for rs12946510 that is predicted to alter MEF2A/C and FOXO1 binding sites.

A common regulatory variant in SLC35B4 influences the recurrence and survival of prostate cancer.

Single nucleotide polymorphisms (SNPs) within the regulatory elements of a gene can alter gene expression, making these SNPs of prime importance for candidate gene association studies. We aimed to determine whether such regulatory variants are associated with clinical outcomes in three cohorts of patients with prostate cancer. We used RegulomeDB to identify potential regulatory variants based on in silico predictions and reviewed genome-wide experimental findings. Overall, 131 putative regulatory SNPs with the highest confidence score on predicted functionality were investigated in two independent localized prostate cancer cohorts totalling 458 patients who underwent radical prostatectomy. The statistically significant SNPs identified in these two cohorts were then tested in an additional cohort of 504 patients with advanced prostate cancer. We identified one regulatory SNPs, rs1646724, that are consistently associated with increased risk of recurrence in localized disease (P = .003) and mortality in patients with advanced prostate cancer (P = .032) after adjusting for known clinicopathological factors. Further investigation revealed that rs1646724 may affect expression of SLC35B4, which encodes a glycosyltransferase, and that down-regulation of SLC35B4 by transfecting short hairpin RNA in DU145 human prostate cancer cell suppressed proliferation, migration and invasion. Furthermore, we found increased SLC35B4 expression correlated with more aggressive forms of prostate cancer and poor patient prognosis. Our study provides robust evidence that regulatory genetic variants can affect clinical outcomes.

Genome-wide Association Study Identifies a Regulatory Variant of RGMA Associated With Opioid Dependence in European Americans.

BACKGROUND: Opioid dependence (OD) is at epidemic levels in the United States. Genetic studies can provide insight into its biology. METHODS: We completed an OD genome-wide association study in 3058 opioid-exposed European Americans, 1290 of whom met criteria for a DSM-IV diagnosis of OD. Analysis used DSM-IV criterion count. RESULTS: By meta-analysis of four cohorts, Yale-Penn 1 (n = 1388), Yale-Penn 2 (n = 996), Yale-Penn 3 (n = 98), and SAGE (Study of Addiction: Genetics and Environment) (n = 576), we identified a variant on chromosome 15, rs12442183, near RGMA, associated with OD (p = 1.3 × 10-8). The association was also genome-wide significant in Yale-Penn 1 taken individually and nominally significant in two of the other three samples. The finding was further supported in a meta-analysis of all available opioid-exposed African Americans (n = 2014 [1106 meeting DSM-IV OD criteria]; p = 3.0 × 10-3) from three cohorts; there was nominal significance in two of these samples. Thus, of seven subsamples examined in two populations, one was genome-wide significant, and four of six were nominally (or nearly) significant. RGMA encodes repulsive guidance molecule A, which is a central nervous system axon guidance protein. Risk allele rs12442183*T was correlated with higher expression of a specific RGMA transcript variant in frontal cortex (p = 2 × 10-3). After chronic morphine injection, the homologous mouse gene (Rgma) was upregulated in C57BL/6J striatum. Coexpression analysis of 1301 brain samples revealed that RGMA messenger RNA expression was associated with that of four genes implicated in other psychiatric disorders, including GRIN1. CONCLUSIONS: This is the first study to demonstrate an association of RGMA with OD. It provides a new lead into our understanding of OD pathophysiology.

cepip: context-dependent epigenomic weighting for prioritization of regulatory variants and disease-associated genes.

It remains challenging to predict regulatory variants in particular tissues or cell types due to highly context-specific gene regulation. By connecting large-scale epigenomic profiles to expression quantitative trait loci (eQTLs) in a wide range of human tissues/cell types, we identify critical chromatin features that predict variant regulatory potential. We present cepip, a joint likelihood framework, for estimating a variant's regulatory probability in a context-dependent manner. Our method exhibits significant GWAS signal enrichment and is superior to existing cell type-specific methods. Furthermore, using phenotypically relevant epigenomes to weight the GWAS single-nucleotide polymorphisms, we improve the statistical power of the gene-based association test.

A candidate regulatory variant at the TREM gene cluster associates with decreased Alzheimer's disease risk and increased TREML1 and TREM2 brain gene expression.

INTRODUCTION: We hypothesized that common Alzheimer's disease (AD)-associated variants within the triggering receptor expressed on myeloid (TREM) gene cluster influence disease through gene expression. METHODS: Expression microarrays on temporal cortex and cerebellum from ∼400 neuropathologically diagnosed subjects and two independent RNAseq replication cohorts were used for expression quantitative trait locus analysis. RESULTS: A variant within a DNase hypersensitive site 5' of TREM2, rs9357347-C, associates with reduced AD risk and increased TREML1 and TREM2 levels (uncorrected P = 6.3 × 10-3 and 4.6 × 10-2, respectively). Meta-analysis on expression quantitative trait locus results from three independent data sets (n = 1006) confirmed these associations (uncorrected P = 3.4 × 10-2 and 3.5 × 10-3, Bonferroni-corrected P = 6.7 × 10-2 and 7.1 × 10-3, respectively). DISCUSSION: Our findings point to rs9357347 as a functional regulatory variant that contributes to a protective effect observed at the TREM locus in the International Genomics of Alzheimer's Project genome-wide association study meta-analysis and suggest concomitant increase in TREML1 and TREM2 brain levels as a potential mechanism for protection from AD.

Regulatory Single-Nucleotide Variant Predictor Increases Predictive Performance of Functional Regulatory Variants.

In silico methods for detecting functionally relevant genetic variants are important for identifying genetic markers of human inherited disease. Much research has focused on protein-coding variants since coding regions have well-defined physicochemical and functional properties. However, many bioinformatics tools are not applicable to variants outside coding regions. Here, we increase the classification performance of our regulatory single-nucleotide variant predictor (RSVP) for variants that cause regulatory abnormalities from an AUC of 0.90-0.97 by incorporating genomic regions identified by the ENCODE project into RSVP. RSVP is comparable to a recently published tool, Genome-Wide Annotation of Variants (GWAVA); both RSVP and GWAVA perform better on regulatory variants than a traditional variant predictor, combined annotation-dependent depletion (CADD). However, our method outperforms GWAVA on variants located at similar distances to the transcription start site as the positive set (AUC: 0.96) as compared with GWAVA (AUC: 0.71). Much of this disparity is due to RSVP's incorporation of features pertaining to the nearest gene (expression, GO terms, etc.), which are not included in GWAVA. Our findings hold out the promise of a framework for the assessment of all functional regulatory variants, providing a means to predict which rare or de novo variants are of pathogenic significance.

Genes associated with diabetes: potential for novel therapeutic targets?

INTRODUCTION: Type 2 diabetes (T2D) is a complex disease caused by an interaction between multiple genetic and environmental factors. T2D-associated loci identified by genome-wide association studies (GWAS) harbor the genes targeted by many clinically available drugs, supporting the idea that GWAS have the potential to discover novel genes for drug development. AREAS COVERED: This paper outlines, among the genes at those T2D-associated loci, the functional analysis of FTO, TCF7L2, SLC30A8, and MTNR1B, illustrating caveats we should be cautious about. This paper also reviews the current status of the compounds targeting the T2D-associated genes GCK, GKRP, ADIPOQ, and ADRA2A in clinical and preclinical phases. EXPERT OPINION: Functional analysis of those loci has fallen too far behind identification of T2D-associated loci. It is mandatory to define the true causal gene at the T2D-associated loci by using a variety of experimental techniques. The biggest challenge lies in the limited access to human tissues relevant to the pathogenesis of T2D. The ultimate goal of human genetic study is enabling personalized medicine based on the genetic information of individuals. More research will be needed to achieve this goal.