Concentration Dose Ratio
Introduction
The concept of a "concentration dose ratio" describes the quantitative relationship between an administered dose (e.g., drug, environmental exposure) or a genetic "dosage" and a resulting biological concentration, effect, or measurable phenotype. This ratio is fundamental to understanding how different inputs translate into varying physiological outcomes within an individual. In genetics, "genotype dosages" are frequently used to quantify the genetic contribution of specific alleles to a trait, often expressed as a fractional value representing the estimated reference allele count ([1] ).
Biological Basis
The biological basis of the concentration dose ratio lies in the complex interplay of genetic, environmental, and physiological factors that determine an individual's response to a given dose. Genetic variations, such as single nucleotide polymorphisms (SNPs) or copy number variants (CNVs), can significantly alter drug metabolism, receptor sensitivity, or gene expression, thereby influencing the effective concentration or biological outcome for a specific dose. For instance, genetic variants in genes like VKORC1, CYP2C9, and CYP4F2 are identified as principal genetic determinants of the required warfarin dose ([2] ). This means that individuals with different genotypes for these genes may require different doses of warfarin to achieve the same therapeutic effect, reflecting a genotype-specific concentration dose relationship. Similarly, the "log R ratio" is a measure used to define CNVs, which can impact gene dosage and thus the concentration of gene products ([2] ). Studies also use an additive model of "dosage value" (estimated reference allele count) as a predictor in linear regression models to assess associations with various phenotypes, such as pulmonary function, demonstrating a direct link between genetic "dose" and biological response ([1] ).
Clinical Relevance
Understanding the concentration dose ratio is critical for the practice of personalized medicine, especially in pharmacogenomics. For drugs with a narrow therapeutic window, like warfarin, genetic differences in genes such as CYP2C9 and VKORC1 necessitate individualized dosing strategies to prevent adverse events, such as bleeding complications, and optimize therapeutic efficacy ([2] ). Genotype-guided dosing helps clinicians tailor drug prescriptions to an individual's unique genetic makeup, improving patient safety and treatment outcomes. Beyond pharmacotherapy, the concept is relevant in understanding other biological ratios, such as the FEV1/FVC ratio for assessing pulmonary function ([1] ) or the Red Cell Distribution Width (RDW) for red blood cell variability ([3] ). These ratios serve as important clinical indicators, and their relationship to various "doses" (e.g., genetic predisposition, smoking dose) provides insights into disease mechanisms and patient management.
Social Importance
The social importance of the concentration dose ratio lies in its potential to advance public health and promote health equity. By enabling more precise drug dosing and personalized treatment plans, it can reduce the incidence of adverse drug reactions, a significant public health burden, and improve the overall effectiveness of medical interventions. This approach moves away from a "one-size-fits-all" model, acknowledging the inherent biological variability among individuals and populations. Furthermore, understanding how genetic "doses" influence various health-related traits, such as anthropometric traits like waist-hip ratio ([4] ) or the 2D:4D finger-length ratio ([5] ), can inform preventative strategies and public health initiatives. Ultimately, leveraging the insights from concentration dose ratios contributes to a healthcare system that is more effective, safer, and tailored to individual needs.
Limitations
Understanding the genetic determinants of traits like concentration dose ratio, particularly for medications such as warfarin, is subject to several methodological and biological limitations. These factors can influence the power, generalizability, and completeness of findings from genome-wide association studies (GWAS), thereby impacting the interpretation of identified genetic associations.
Methodological and Statistical Constraints
A primary limitation in genetic studies of dose is the statistical power to detect variants that explain only a small proportion of the phenotypic variance. For instance, while a GWAS might have sufficient power (e.g., 80%) to detect variants accounting for 1.5% or more of the warfarin dose variance, its power drops considerably (e.g., 40% or less) for variants explaining 1% or less of the variance. [2] This inherent power constraint, often exacerbated by relatively small sample sizes in initial studies, can lead to an underestimation of the true number of associated genetic variants and potentially inflated effect sizes for those that do reach significance. [6] Such limitations necessitate large-scale meta-analyses, which in turn introduce challenges related to heterogeneity between study cohorts, including differences in mean age, annual decline rates, and follow-up durations, which can impact replication consistency and overall result interpretation. [7]
Further, the possibility of false positive findings remains a concern, particularly when using standard significance thresholds across numerous analyses or in studies of admixed populations where residual population substructure might exist despite adjustments. [8] The failure of some identified loci to replicate in subsequent studies, even for established associations, highlights the difficulty in distinguishing genuine signals from statistical artifacts or population-specific effects. [8] Rigorous statistical approaches, such as genomic control corrections, are applied to mitigate inflation of test statistics due to stratification, but these do not fully eliminate all sources of bias. [9]
Phenotypic and Genomic Measurement Challenges
The precise definition and consistent measurement of complex phenotypes across diverse study populations pose significant challenges. Differences in spirometry assessment timing or the lack of detailed information on asthma sub-phenotypes or medication intake can introduce variability and limit the generalizability of findings, making it difficult to fully understand the impact of genetic variants on specific aspects of disease or drug response. [7] Moreover, the technical aspects of genetic data collection, such as the process for defining copy number variation (CNV) regions, can introduce complexities; issues like DNA quality or hybridization problems can lead to the exclusion of a substantial proportion of samples, potentially introducing selection biases. [2]
The ability to detect dose-altering variants is also contingent on the quality of genetic data and the genomic regions analyzed. While some known functional variants are directly genotyped, others may be indirectly detected through markers in linkage disequilibrium (LD), meaning variants not in sufficiently high LD with genotyped SNPs might remain undiscovered. [2] Furthermore, technical limitations can restrict the scope of analysis, such as the difficulty in imputing X-linked single nucleotide polymorphisms (SNPs), which can lead to the exclusion of entire chromosomal regions from association testing. [3] Differences in LD structure across various ancestral populations also require careful consideration, as associations identified in one population may not directly translate or be tagged by the same markers in another. [8]
Unexplained Heritability and Gene-Environment Interactions
Despite the success of GWAS in identifying numerous genetic loci, a substantial proportion of the heritability for complex traits, including those related to drug dose, remains unexplained. This "missing heritability" suggests that current GWAS approaches, which typically assess common SNPs individually, may not fully capture the true genetic architecture of these phenotypes. [10] Potential explanations include the presence of undiscovered low-frequency or rare variants with larger effects, imperfect tagging of causal variants, complex epistatic interactions between genes, and the significant influence of gene-environment interactions. [7]
The current study designs often lack the power to thoroughly investigate gene-environment interactions or to study specific subgroups of diseases or dose responses, limiting a comprehensive understanding of how genetic predispositions interact with external factors. The challenge of assessing the joint effect of multiple SNPs, each with small individual effects, and their potential interactions further complicates the unraveling of complex genetic underpinnings. Addressing these remaining knowledge gaps will require alternative analytic strategies, such as those that consider a broader spectrum of genetic variation (including rare variants) and incorporate environmental exposures more explicitly, to differentiate true associations and better explain phenotypic variation. [7]
Variants
Genetic variants, or single nucleotide polymorphisms (SNPs), play a crucial role in shaping individual biological responses, including how the body processes and reacts to various substances, which can influence the concentration dose ratio of treatments and physiological compounds. The variant rs16935279 is associated with LINC01592, a long intergenic non-coding RNA. Such non-coding RNAs are essential regulators of gene expression, affecting processes from chromatin modification to cellular differentiation. A change like rs16935279 within LINC01592 could alter its stability, expression levels, or interaction with other regulatory molecules, thereby subtly influencing the intricate networks it controls. [6] Similarly, rs9862857, linked to the non-coding RNAs U3 and LINC01985, and rs6586354, associated with RNY4P16 and RN7SL668P, highlight the impact of variants in these regulatory elements. Alterations in these regions can lead to subtle shifts in cellular responses, which might affect the efficacy, metabolism, or side effects of compounds, ultimately influencing the appropriate concentration dose required for a desired effect. [11]
Other variants impact genes involved in critical signaling and metabolic pathways. For example, rs17154917 is linked to SEMA3C and EIF4EP4. SEMA3C is a semaphorin protein involved in axon guidance, immune responses, and angiogenesis, while EIF4EP4 plays a role in protein synthesis initiation. A variant in these genes could alter protein function or expression, thereby impacting cell signaling cascades or metabolic rates, which are fundamental to how the body processes drugs or nutrients. The variant rs10968749 is found within LINGO2, a gene implicated in neuronal differentiation and neurodevelopment. Variations in LINGO2 can affect the precise wiring and function of the nervous system, potentially altering neurological responses to medications. Furthermore, rs17673138 is associated with NRG1, Neuregulin 1, a gene crucial for cell-cell communication, nervous system development, and cardiac function. Variants affecting NRG1 could modulate receptor binding or downstream signaling, impacting a broad range of physiological processes and influencing how the body responds to specific doses of therapeutic agents. [2] Such genetic variations collectively contribute to the individual variability observed in drug pharmacokinetics and pharmacodynamics, necessitating careful consideration of concentration dose ratios. [3]
Variants affecting transcriptional regulation and cellular components also have significant implications for concentration dose ratios. rs10405744 is associated with ZNF93, a zinc finger protein that likely functions as a transcription factor. Variants in ZNF93 could alter its DNA-binding affinity, leading to changes in the expression of target genes, which in turn might affect metabolic enzymes or drug transporters. The variant rs2302045 is linked to SNED1 and MTERF4. SNED1 is a secreted protein involved in extracellular matrix organization, while MTERF4 is a mitochondrial transcription termination factor that plays a role in mitochondrial biogenesis and energy metabolism. Alterations in these genes could impact cellular energy production or structural integrity, influencing the cellular environment where drugs exert their effects. Moreover, rs17066873 is associated with KCTD12 and BTF3P11. KCTD12 is involved in ion channel function and neurological processes, while BTF3P11 is a pseudogene that may have regulatory roles. Lastly, rs11829119 is associated with CAPZA3 and RPL7P6. CAPZA3 is a capping protein involved in actin filament regulation, crucial for cell motility and structure, and RPL7P6 is another pseudogene. Variants in these genes can alter fundamental cellular processes, from gene expression and mitochondrial function to cytoskeletal dynamics, collectively affecting how cells respond to and process drugs, thereby influencing the optimal concentration dose ratio for various treatments. [12]
Key Variants
| RS ID | Gene | Related Traits |
|---|---|---|
| rs16935279 | LINC01592 | concentration dose ratio |
| rs17154917 | SEMA3C - EIF4EP4 | concentration dose ratio |
| rs9862857 | U3 - LINC01985 | concentration dose ratio |
| rs6586354 | RNY4P16 - RN7SL668P | concentration dose ratio |
| rs10968749 | LINGO2 | concentration dose ratio |
| rs2302045 | SNED1, MTERF4 | concentration dose ratio |
| rs17066873 | KCTD12 - BTF3P11 | concentration dose ratio |
| rs17673138 | NRG1 | concentration dose ratio |
| rs10405744 | ZNF93 | concentration dose ratio |
| rs11829119 | CAPZA3 - RPL7P6 | concentration dose ratio |
Biological Background
The relationship between the concentration of a substance and its administered dose is a fundamental aspect of biology, influencing everything from drug efficacy and toxicity to physiological responses and disease susceptibility. This ratio is governed by complex biological mechanisms involving genetic predispositions, molecular pathways, cellular functions, and systemic homeostatic controls. Understanding these underlying processes is crucial for comprehending how an individual's unique biological makeup dictates their response to various internal and external stimuli.
Genetic Determinants of Drug Metabolism and Action
The body's ability to process and respond to xenobiotics, such as medications, is heavily influenced by an individual's genetic profile. Key enzymes involved in drug metabolism, particularly those belonging to the cytochrome P450 (CYP) family, exhibit genetic variations that can alter their activity. For instance, variants in CYP2C9 (rs1799853) significantly impact the metabolism of drugs like warfarin, a common anticoagulant. [2] Similarly, the CYP4F2 gene (rs2108622) also contributes to warfarin dose requirements, explaining approximately 1% of the dose variance. [2] Beyond metabolism, genetic variations in drug targets, such as VKORC1 (Vitamin K epoxide reductase complex subunit 1), directly affect drug action by altering the sensitivity of the target protein to the medication. [2] These genetic differences mean that a standard dose can lead to vastly different effective concentrations and physiological responses among individuals, necessitating personalized dosing strategies.
Molecular and Cellular Signaling Pathways
At the cellular level, the concentration of biomolecules and external substances dictates the activation of specific signaling pathways, which in turn regulate cellular functions. For example, in the differentiation of hematopoietic stem cells into erythroid lineages, precise concentrations of growth factors like erythropoietin, interleukin-3 (IL-3), and stem cell factor are critical for inducing specific gene expression patterns and driving cell development. [13] Neurobiological pathways also demonstrate this concentration-dependent response; for instance, nicotine at certain concentrations can activate POMC neurons, leading to a decrease in food intake. [14] These examples illustrate how the precise concentration of a signaling molecule or drug can trigger a cascade of molecular events, influencing everything from cellular proliferation and differentiation to metabolic regulation and neuronal activity.
Systemic Homeostasis and Pathophysiological Responses
The body maintains a delicate balance, or homeostasis, which can be disrupted by genetic factors, environmental exposures, or their interactions, leading to various physiological and pathophysiological states. For instance, genetic variants in the FTO gene are strongly associated with body mass index (BMI) and predispose individuals to obesity [15] demonstrating how genetic makeup can influence metabolic regulation and energy balance. Furthermore, genes like GRB10 play a central role in regulating islet function, which is critical for glucose homeostasis and insulin secretion. [16] Environmental factors, such as "smoking dose" (packs/day and duration in years), interact with genetic predispositions to influence complex traits like pulmonary function, where a higher cumulative dose of exposure can lead to altered physiological outcomes. [1] These interactions highlight how a given dose or exposure, combined with an individual's genetic background, can lead to disruptions in systemic processes and contribute to disease development.
Gene Expression and Regulatory Networks
The ultimate manifestation of a dose-concentration relationship often lies in changes in gene expression, which are controlled by intricate regulatory networks. Genetic variations, including single nucleotide polymorphisms (SNPs) and copy number variations (CNVs), can influence the levels and patterns of gene expression . [17], [18] These changes can be tissue-specific, meaning that a particular genetic variant might affect gene expression differently in various tissues, leading to diverse physiological impacts. [19] For example, quantitative trait loci (QTL) within the Major Histocompatibility Complex (MHC) region regulate the CD4:CD8 lymphocyte ratio, with distinct QTLs influencing CD4 and CD8 levels, respectively. [20] This demonstrates how genetic elements act as regulatory switches, influencing the cellular machinery that translates genetic information into functional proteins, thereby modulating an individual's response to various biological challenges or therapeutic interventions.
Clinical Relevance
Understanding the factors that influence an individual's drug dose requirements or the expression of physiological traits has profound clinical relevance, driving advancements in personalized medicine and risk assessment. This understanding, often reflected in what can be conceptualized as a "concentration dose ratio," allows for more precise therapeutic interventions and improved patient outcomes.
Personalized Medicine and Dosing Strategies
The relationship between genetic factors and an individual's required drug dose is a cornerstone for optimizing therapeutic regimens and enabling personalized medicine. [2] For instance, in anticoagulation therapy with warfarin, genetic variants within VKORC1, CYP2C9, and CYP4F2 are key determinants of the stable daily dose needed to achieve therapeutic anticoagulation. [2] By integrating this genetic information, clinicians can refine initial dosing algorithms, potentially minimizing the duration of trial-and-error dosing and reducing the risk of either sub-therapeutic or supra-therapeutic effects. [2] This precision facilitates more effective treatment selection and the development of tailored monitoring strategies, thereby enhancing both patient safety and treatment efficacy.
Prognostic Value in Disease Management
The ability to predict an individual's response to medication or their susceptibility to adverse events based on their genetic profile offers significant prognostic value in disease management. [2] For drugs such as warfarin, specific genetic variants serve as powerful predictors not only of the required dose but also of the likelihood of complications like over-anticoagulation (defined as an International Normalized Ratio, INR, above 4.0) during the initial treatment phase. [2] Identifying these genetic determinants allows for proactive risk assessment, enabling clinicians to manage high-risk patients through individualized dose adjustments or intensified monitoring. This approach helps prevent severe adverse outcomes and informs long-term strategies for managing chronic conditions.
Genetic Determinants and Risk Stratification
Genetic factors are instrumental in stratifying individuals based on their risk for particular drug responses or variations in physiological traits. For example, genome-wide association studies have identified specific genetic variants, such as rs9923231 in VKORC1, rs1799853 (associated with CYP2C9*2) and CYP2C9*3 in CYP2C9, and rs2108622 in CYP4F2, as primary genetic determinants of warfarin dose. [2] The contribution of these variants to the overall dose variance allows for the identification of individuals who may require substantially different warfarin doses, facilitating targeted prevention strategies against adverse drug reactions. [2] Similarly, the "dosage value" of estimated reference alleles for single nucleotide polymorphisms (SNPs) has been employed as a predictor in linear regression models to investigate associations with pulmonary function traits like FEV1 and FEV1/FVC, even after adjusting for covariates such as smoking status, highlighting the utility of genetic information in comprehensive risk assessment for complex physiological phenotypes. [1]
Genetic Influences on Drug Metabolism and Pharmacokinetics
Genetic variations in drug-metabolizing enzymes significantly influence the concentration dose ratio of many medications. For example, variants in cytochrome P450 enzymes, particularly CYP2C9, play a critical role in the metabolism of drugs like warfarin, a widely used anticoagulant. Polymorphisms such as CYP2C9*2 and CYP2C9*3 are associated with reduced enzyme activity, leading to slower drug clearance and consequently higher circulating drug concentrations for a given dose. [2] This necessitates lower warfarin doses to achieve the desired therapeutic effect and mitigates the risk of adverse drug reactions, such as severe bleeding, which can arise from over-anticoagulation [2], [20], [21], [22], [23], [24], [2108622], [9923231] Patients with genotypes associated with increased VKORC1 sensitivity to warfarin may require lower doses, while those with reduced sensitivity may need higher doses to attain adequate anticoagulation, illustrating the profound impact of target protein variants on the pharmacodynamic profile.
Integrated Pharmacokinetic and Pharmacodynamic Effects on Response
The combined influence of genetic variants affecting both drug metabolism (pharmacokinetics) and drug targets (pharmacodynamics) collectively dictates an individual's overall response to medication. For warfarin, the genotypes of CYP2C9 and VKORC1 together explain approximately 40% of the observed variability in dose requirements. [2] Individuals who possess genetic predispositions for both slower drug metabolism and increased target sensitivity face a significantly elevated risk of over-anticoagulation, characterized by an INR above 4.0, which can lead to severe bleeding complications [2], [20], [21], [22], [23], [25], [2108622] The accumulating evidence supports the integration of pharmacogenetic testing into clinical guidelines to facilitate more precise drug selection and dosing recommendations, ultimately leading to improved patient outcomes through personalized medicine.
Frequently Asked Questions About Concentration Dose Ratio
These questions address the most important and specific aspects of concentration dose ratio based on current genetic research.
1. Why did my doctor adjust my medicine dose so much?
It's very common because your genes significantly affect how your body processes medicines. For drugs like warfarin, variations in genes such as CYP2C9 and VKORC1 mean that people need different doses to get the same therapeutic effect, helping prevent side effects and ensuring the medicine works best for you.
2. Why does a drug work for others but not quite for me?
It's often due to your unique genetic makeup. Your genes influence how quickly you metabolize a drug or how sensitive your body's receptors are to it. This means a standard dose might be too high or too low for you compared to someone else, highlighting why personalized medicine is so important.
3. Is my waist-hip ratio mostly genetic?
Your waist-hip ratio, like many body traits, has a significant genetic component. Studies have identified specific genetic "doses" that influence fat distribution. While lifestyle plays a role, your genes contribute to how your body stores fat, affecting this ratio.
4. My family has strong lungs, but mine aren't great. Why?
Even within families, genetic "dosages" for traits like pulmonary function can vary. While your family might have a general predisposition, specific genetic variations you inherited can influence your individual lung capacity, such as the FEV1/FVC ratio, differently.
5. Should I get a DNA test to help with my medicine?
For certain medications, especially those with a narrow therapeutic window like warfarin, a DNA test can be very helpful. It can identify genetic variations in genes such as CYP2C9 or VKORC1 that tell your doctor how to tailor your dose, making treatment safer and more effective.
6. What does my RDW number on a blood test mean for my genes?
Your Red Cell Distribution Width (RDW) is a measure of red blood cell variability, and it's influenced by your genetics. Specific genetic "doses" contribute to how consistently your body produces red blood cells, making RDW an indicator tied to your inherited traits.
7. Are my lung capacity numbers linked to my family's health history?
Yes, your lung capacity, often measured by ratios like FEV1/FVC, can be strongly linked to your family's genetic history. Your inherited "dosage" of certain genes can predispose you to better or worse pulmonary function, even independently of environmental factors like smoking.
8. Can my genes really influence something like my finger length?
Surprisingly, yes! Your genes play a role in many physical traits, including subtle ones like the 2D:4D finger-length ratio. Specific genetic variations can act as a "dose" during development, influencing how these ratios form.
9. If my parents needed a special drug dose, will I too?
There's a good chance you might. If your parents' need for a special drug dose was due to genetic factors, you could have inherited similar genetic variations. These variations can influence your drug metabolism, making personalized dosing important for you as well.
10. Can my genetics really be thought of as a "dose"?
Absolutely. In genetics, your "genotype dosage" refers to the specific number of certain gene variants you have, often expressed as an estimated reference allele count. This genetic "dose" directly influences the concentration of gene products and ultimately affects various biological outcomes or traits.
This FAQ was automatically generated based on current genetic research and may be updated as new information becomes available.
Disclaimer: This information is for educational purposes only and should not be used as a substitute for professional medical advice. Always consult with a healthcare provider for personalized medical guidance.
References
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