Two new books on speciation update the classic texts by Mayr and Grant and help set the stage for a renaissance of research into one of the most important processes in evolution

Despite the biases that a single author inevitably brings to a subject, only one or a few closely interacting authors can bring coherence, synthesis, and vision to a broad and complex topic. A symposium volume just doesn't do the job. Few topics in biology are as simultaneously encompassing, complex, and controversial as the origin of species, i.e., speciation. Speciation is, after all, the process responsible for biological diversity, at least of sexual organisms, so it is hardly a minor topic. But even though recent years have seen the publication of symposia on speciation and books on the ever-contentious issue of species concepts, it has been 23 years since Verne Grant's authoritative  Plant Speciation  [ 1 ] and 41 years since Ernst Mayr's magisterial and highly influential  Animal Species and Evolution  [ 2 ]—the last syntheses of research on speciation. Now, two outstanding new books not only treat speciation as a conceptually unified topic in both plants and animals for the first time, but also provide rich review and analysis of a vast subject that has progressed at least as much since Mayr and Grant wrote as in the century that preceded their work.Plant SpeciationAnimal Species and EvolutionThese books are very different, but wonderfully complementary. Gavrilets reviews and adds to mathematical theories and simulation studies of speciation and related issues, such as fitness landscapes and selection in heterogeneous environments. A deep reading of his book will require considerably more mathematical competence than most evolutionary biologists (including this reviewer) have, but Gavrilets provides excellent verbal explanations of the models' assumptions and conclusions, as well as comparisons and critiques of related models. Gavrilets cites empirical studies (with which he has very broad familiarity) plentifully, but as a theoretician, he does not evaluate them or describe them in depth. That task is undertaken by Coyne and Orr, who introduce most topics with a verbal overview of theory, review empirical evidence and its bearing on hypotheses, and conclude with incisive assessments of what they think we know and what remains uncertain or unexplored. Like Gavrilets, they offer a number of novel ideas or suggestions about how to proceed. Coyne and Orr have both worked mostly on speciation genetics in  Drosophila , so it is hardly surprising that their treatment of speciation bears a strong genetic emphasis and draws heavily on  Drosophila  work (perforce, since this is almost the only source of evidence on some topics, such as the genetics of hybrid sterility and inviability). Even the most drosophilophobic readers, however, will be pleased by the extent to which Coyne and Orr have conscientiously scoured the literature on nonmodel animals and plants.To appreciate the landmark status of these books, consider what has happened in speciation studies since Mayr and Grant published theirs. Mayr and Grant articulated positions on species and speciation that had developed during and soon after the Modern Synthesis of the 1930s and 1940s, when modern evolutionary theory developed from a reconciliation of genetics, systematics, and paleontology. Mayr and Grant drew on abundant systematic data on patterns of divergence and experimental data on genetic differences between related species. They rightly identified reproductive isolation (RI) as a critical, even defining, property of species, and allopatric divergence (i.e., in disjunct geographic areas) as the major geographic mode of speciation. They recognized that trait differences between species, including RI, usually have a polygenic basis, and that different coadapted (epistatically interacting) sets of genes underlie incompatibility (e.g., hybrid sterility). They emphasized the role of ecological selection as a driving force in speciation, largely by extrapolation from the primacy of selectionist thinking that developed during the Synthesis. They accepted that natural selection can reinforce prezygotic isolation (i.e., lack of mating or zygote formation) between species and thereby reduce production of unfit hybrids, even if Mayr did not share Dobzhansky's belief that this was the norm. Mayr combined selection with genetic drift in his theory of founder-effect speciation (divergence in populations founded by just a few individuals), which became widely accepted. (It became Eldredge and Gould's [ 3 ] theoretical foundation for punctuated equilibrium nine years after Mayr's book appeared.) Mayr and Grant wrote against a background that almost entirely lacked any mathematical theory of speciation (which I suspect neither of them would have drawn on even if it had been developed), any relevant molecular data (other than early allozyme studies by the time Grant published), and any rigorous phylogenetic methodology. Kimura's neutral theory of molecular evolution [ 4 ] had not yet been published when Mayr wrote, and had not been vindicated when Grant wrote, so genetic drift and a neutral (nonselectionist) interpretation of molecular data were still suspect. Detailed analysis of genetic architecture was decades away, and of course insights into selection and historical demography from DNA sequence data were a dim dream at best.Coyne and Orr and Gavrilets analyze a new world of speciation studies. Theoretical studies of speciation, for example, now include more than 100 papers on one topic alone, the evolution of prezygotic isolation. (Gavrilets laments that the theoretical work suffers from domination by simulation rather than analysis, so that it is often hard to draw general conclusions from models that use different assumptions, but he nevertheless draws some fairly strong conclusions, as I note below.) Molecular studies have provided important data on such issues as the absolute dates of speciation events, the duration of speciation, and the time course of the evolution of RI. The field of molecular phylogeography, which documents the history of spatial isolation and geographic expansion of populations, has developed. The relation between range overlap of related species and their molecularly dated time of divergence provides some evidence on the role of geographic versus sympatric speciation (i.e., speciation without geographic segregation). In all these areas and others, our knowledge has increased steadily. For instance, molecular markers enable more detailed dissection of the genetic architecture of species differences, and support the conclusion that they are usually rather highly polygenic, but that much of the variance can be explained by a few major gene substitutions. We now have good evidence, as Coyne and Orr emphasize, that at least in animals, hybrid infertility is caused by differences in gene action, not by structural chromosome differences or failure of meiosis.Regarding the mechanisms of speciation, evidence for the role of divergent ecological selection in allopatric speciation is sparse, because this crucial topic has been unaccountably neglected until recently. Very different kinds of data, ranging from DNA sequences to correspondence between RI and ecological divergence, support natural selection, but there is hardly enough evidence, in my opinion, to support Coyne and Orr's strong conclusion that “at least one important debate has been settled: selection plays a much larger role in speciation than does drift” (p. 410). Even more astonishing than the paucity of studies of the role of ecological selection in speciation is the fact that the likely role of sexual selection was not even recognized until almost 20 years after Mayr's book. I agree with Coyne and Orr that the theory and evidence for speciation by sexual selection is one of the most important advances in speciation studies, but it is important to recognize that the evidence consists mostly of correlations between diversification rates and indices of the likely strength of sexual selection; as Coyne and Orr note, there are no cases in which we understand just how sexual selection has caused speciation. This is a rich, largely unexplored area. Gavrilets feels that divergent evolution by sexual conflict (in which females evolve resistance to males' advances) is a potentially important process, whereas Coyne and Orr are skeptical that this will prove widespread. Coyne and Orr remark that populations may diverge in male signals because of intrasexual selection (competition among males), and that female mate preference may follow. Quite so, but even though Berglund et al. [ 5 ] summarized many examples in which male signals appear to serve both inter- and intrasexual functions, this topic has been almost ignored in the literature of both speciation and sexual selection. On a related theme, an important speciation process appears to be the extraordinarily rapid evolution of male reproductive proteins (e.g., sperm surface proteins), which may contribute to the “faster male evolution” that is a cause of “Haldane's rule” (that hybrid sterility and inviability first appear in the sex that has two unlike sex chromosomes).Despite their very different approaches, Coyne and Orr and Gavrilets arrive at rather similar conclusions on some of the most controversial issues in speciation. One such is the role of genetic drift in speciation. Gavrilets analyzes founder-effect speciation (which combines drift and selection), agrees with most other theoreticians (e.g., Barton and Charlesworth) [ 6 ] that it is very improbable, and argues instead for his model of evolution on “holey landscapes,” whereby allopatric populations can evolve by genetic drift along ridges of roughly equal fitness to different, incompatible gene constitutions. He admits that the time to speciation under this process will ordinarily be very long unless selection is involved. Coyne and Orr fully accept both Barton and Charlesworth's critique and Gavrilets's alternative model. But while admitting the plausibility of Gavrilets's models of speciation by genetic drift, they nevertheless maintain that “the models seem unnecessary when compared to adaptive ones” (p. 398).Coyne and Orr appear to adopt selection as the null hypothesis for speciation, whereas drift is generally taken as the null hypothesis in much of evolutionary genetics, for the simple reason that drift operates at all loci in all finite (i.e., real) populations, whereas selection need not. The burden of demonstrating that selection is  not  responsible for an evolutionary event (i.e., demonstrating a negative) is, of course, far heavier than the burden of demonstrating selection; indeed, Coyne and Orr do not address the difficult question of what would constitute evidence for drift. Having, perhaps, stacked the deck, Coyne and Orr find almost no evidence that drift has contributed to speciation in nature, but conclude that there is “considerable evidence” that selection has done so. However, the amount of evidence is hardly on a par with, say, the evidence for allopatric speciation. It consists of only about eight studies of ecological selection, indications that diversification rates are associated with greater scope for sexual selection, selection signatures in a few genes that underlie genetic incompatibility, and a paucity of molecular evidence for bottlenecks (i.e., opportunities for founder events) in the history of recently formed species. But the evidence on the role of sexual selection is very indirect, and the high levels of genetic variation revealed in molecular studies argue against past bottlenecks only if this is ancestral variation, rather than variation generated anew since a possible bottleneck—a question that has been addressed in only a few cases. Assuming that experiments with laboratory populations can be validly extrapolated to natural speciation processes, founder-effect speciation may indeed be a moribund hypothesis, but I do not believe long-term genetic drift can yet be ruled out, and cannot agree that this “important debate has been settled” (p. 410).notThe geography of speciation continues to be one of the most difficult and contentious topics, and undoubtedly will remain so despite the careful analyses by these authors. They agree that parapatric speciation (evolution of RI between neighboring populations that exchange genes) is theoretically plausible, but Gavrilets notes that although it has become clear that its likelihood is sensitive to several model parameters, parapatric speciation is difficult to model and has been shamefully neglected. Coyne and Orr do not doubt that it is a fairly common mode of speciation, yet “it is almost impossible to demonstrate parapatric speciation in nature” (p. 118), and no cases have been well documented.Gavrilets provides an exhaustive analysis of the many models of sympatric speciation, and identifies some key issues that have been underemphasized. For example, the sympatric evolution of behavioral isolation by “matching traits” (e.g., genetically independent male signal and female preference) is generally much more difficult than “similaritybased” mating (in which females choose males that have the same phenotypic trait as themselves). Just how common the latter is in animals is an open question that Coyne and Orr unfortunately do not address. Gavrilets also identifies the cost of female choosiness as a critical issue: many models of sympatric speciation depend on the assumption that females always succeed in mating even if the male type they prefer is rare, so their choosiness has no cost. Gavrilets criticizes some popular models of sympatric speciation on these and other grounds, and while granting that sympatric speciation by divergent habitat or host preference is plausible, he concludes that it need not be faster than allopatric speciation and that “contrary to common claims in recent theoretical papers, conditions for sympatric speciation are not wide and sympatric speciation does not occur easily” (p. 404).For their part, Coyne and Orr feel that the prevalence of sympatric speciation is an empirical issue (but a very difficult one), and undertake a broad, detailed review. They identify three examples of completed speciation in which a sympatric scenario “seems plausible.” I see no reason to accept one of these cases, a pair of sister species of “parasites” (fig wasps) on the same host species, since allopatric speciation of a widespread parasite need not be accompanied by speciation of its host. Moreover, Coyne and Orr note weaknesses in all three cases, as well as in examples of “host races” that have been advanced as species  in statu nascendi . Coyne and Orr's conclusion echoes Gavrilets's: “It is hard to see how the data at hand can justify the current wave of enthusiasm for sympatric speciation” (p. 178).  Bravi!in statu nascendiBravi!I have indicated some disagreements with Coyne and Orr, and could certainly cite others. But whatever weaknesses their book may have (more ecology and phylogeny, anyone?) are much less important than its strengths. The strengths of  Speciation  are not only Coyne and Orr's comprehensive, scholarly coverage of an exceedingly broad subject, but also, and especially, their rigorous, incisive analysis, coupled with strongly stated conclusions and suggestions for how to resolve controversies. Many readers will have a visceral reaction against their position on sympatric speciation, reinforcement, founder-effect speciation, or other issues—but can these readers counter Coyne and Orr's arguments with equally cogent analysis? Or are these subjects that simply require more, and perhaps more imaginative, research?SpeciationTogether, these books provide a comprehensive, thoughtful synthesis of our current understanding of one of the most important processes in evolution. They are required reading for anyone who studies species and speciation. I recommend  Speciation  and the nonmathematical final chapter (“General Conclusions”) of  Fitness Landscapes and the Origin of Species  to all evolutionary biologists, students, and professionals alike. It may not take another two decades for the next foundational books on speciation to appear, but these books will fill that role for a long time to come.SpeciationFitness Landscapes and the Origin of Species


The mystery of a sometimes debilitating speech disorder is examined by cognitive neuroscientists

Stuttering, with its characteristic disruption in verbal fluency, has been known for centuries; earliest descriptions probably date back to the Biblical Moses' “slowness of speech and tongue” and his related avoidance behavior (Exodus 4, 10–13). Stuttering occurs in all cultures and ethnic groups ( Andrews et al. 1983 ;  Zimmermann et al. 1983 ), although prevalence might differ. Insofar as many of the steps in how we produce language normally are still a mystery, disorders like stuttering are even more poorly understood. However, genetic and neurobiological approaches are now giving us clues to causes and better treatments.What Is Stuttering? Stuttering is a disruption in the fluency of verbal expression characterized by involuntary, audible or silent, repetitions or prolongations of sounds or syllables ( Figure 1 ). These are not readily controllable and may be accompanied by other movements and by emotions of negative nature such as fear, embarrassment, or irritation ( Wingate 1964 ). Strictly speaking, stuttering is a symptom, not a disease, but the term  stuttering  usually refers to both the disorder and symptom. Figure 1 Speech Waveforms and Sound Spectrograms of a Male Speaker Saying “PLoS Biology” The left column shows speech waveforms (amplitude as a function of time); the right column shows a time–frequency plot using a wavelet decomposition of these data. In the top row, speech is fluent; in the bottom row, stuttering typical repetitions occur at the “B” in “Biology.” Four repetitions can be clearly identified (arrows) in the spectrogram (lower right). Developmental stuttering evolves before puberty, usually between two and five years of age, without apparent brain damage or other known cause (“idiopathic”). It is important to distinguish between this persistent developmental stuttering (PDS), which we focus on here, and acquired stuttering. Neurogenic or acquired stuttering occurs after a definable brain damage, e.g., stroke, intracerebral hemorrhage, or head trauma. It is a rare phenomenon that has been observed after lesions in a variety of brain areas ( Grant et al. 1999 ;  Ciabarra et al. 2000 ). The clinical presentation of developmental stuttering differs from acquired stuttering in that it is particularly prominent at the beginning of a word or a phrase, in long or meaningful words, or syntactically complex utterances ( Karniol 1995 ;  Natke et al. 2002 ), and the associated anxiety and secondary symptoms are more pronounced ( Ringo and Dietrich 1995 ). Moreover, at repeated readings, stuttering frequency tends to decline (adaptation) and to occur at the same syllables as before (consistency). Nonetheless, the distinction between both types of stuttering is not strict. In children with perinatal or other brain damage, stuttering is more frequent than in age-matched controls, and both types of stuttering may overlap ( Andrews et al. 1983 ).
What Is Stuttering?
Stuttering is a disruption in the fluency of verbal expression characterized by involuntary, audible or silent, repetitions or prolongations of sounds or syllables ( Figure 1 ). These are not readily controllable and may be accompanied by other movements and by emotions of negative nature such as fear, embarrassment, or irritation ( Wingate 1964 ). Strictly speaking, stuttering is a symptom, not a disease, but the term  stuttering  usually refers to both the disorder and symptom.stutteringDevelopmental stuttering evolves before puberty, usually between two and five years of age, without apparent brain damage or other known cause (“idiopathic”). It is important to distinguish between this persistent developmental stuttering (PDS), which we focus on here, and acquired stuttering. Neurogenic or acquired stuttering occurs after a definable brain damage, e.g., stroke, intracerebral hemorrhage, or head trauma. It is a rare phenomenon that has been observed after lesions in a variety of brain areas ( Grant et al. 1999 ;  Ciabarra et al. 2000 ).The clinical presentation of developmental stuttering differs from acquired stuttering in that it is particularly prominent at the beginning of a word or a phrase, in long or meaningful words, or syntactically complex utterances ( Karniol 1995 ;  Natke et al. 2002 ), and the associated anxiety and secondary symptoms are more pronounced ( Ringo and Dietrich 1995 ). Moreover, at repeated readings, stuttering frequency tends to decline (adaptation) and to occur at the same syllables as before (consistency). Nonetheless, the distinction between both types of stuttering is not strict. In children with perinatal or other brain damage, stuttering is more frequent than in age-matched controls, and both types of stuttering may overlap ( Andrews et al. 1983 ).Who Is Affected? PDS is a very frequent disorder, with approximately 1% of the population suffering from this condition. An estimated 3 million people in the United States and 55 million people worldwide stutter. Prevalence is similar in all social classes. In many cases, stuttering severely impairs communication, with devastating socioeconomic consequences. However, there are also many stutterers who, despite their disorder, have become famous. For instance, Winston Churchill had to rehearse all his public speeches to perfection and even practiced answers to possible questions and criticisms to avoid stuttering. Charles Darwin also stuttered; interestingly, his grandfather Erasmus Darwin suffered from the same condition, highlighting the fact that stuttering runs in families and is likely to have a genetic basis. The incidence of PDS is about 5%, and its recovery rate is up to about 80%, resulting in a prevalence of PDS in about 1% of the adult population. As recovery is considerably more frequent in girls than in boys, the male-to-female ratio increases during childhood and adolescence to reach three or four males to every one female in adulthood. It is not clear to what extent this recovery is spontaneous or induced by early speech therapy. Also, there is no good way of predicting whether an affected child will recover ( Yairi and Ambrose 1999 ). The presence of affected family members suggests a hereditary component. The concordance rate is about 70% for monozygotic twins ( Andrews et al. 1983 ;  Felsenfeld et al. 2000 ), about 30% for dizygotic twins ( Andrews et al. 1983 ;  Felsenfeld et al. 2000 ), and 18% for siblings of the same sex ( Andrews et al. 1983 ). Given the high recovery rate, it may well be that the group abnormalities observed in adults reflects impaired recovery rather than the causes of stuttering ( Andrews et al. 1983 ).
Who Is Affected?
PDS is a very frequent disorder, with approximately 1% of the population suffering from this condition. An estimated 3 million people in the United States and 55 million people worldwide stutter. Prevalence is similar in all social classes. In many cases, stuttering severely impairs communication, with devastating socioeconomic consequences. However, there are also many stutterers who, despite their disorder, have become famous. For instance, Winston Churchill had to rehearse all his public speeches to perfection and even practiced answers to possible questions and criticisms to avoid stuttering. Charles Darwin also stuttered; interestingly, his grandfather Erasmus Darwin suffered from the same condition, highlighting the fact that stuttering runs in families and is likely to have a genetic basis.The incidence of PDS is about 5%, and its recovery rate is up to about 80%, resulting in a prevalence of PDS in about 1% of the adult population. As recovery is considerably more frequent in girls than in boys, the male-to-female ratio increases during childhood and adolescence to reach three or four males to every one female in adulthood. It is not clear to what extent this recovery is spontaneous or induced by early speech therapy. Also, there is no good way of predicting whether an affected child will recover ( Yairi and Ambrose 1999 ).The presence of affected family members suggests a hereditary component. The concordance rate is about 70% for monozygotic twins ( Andrews et al. 1983 ;  Felsenfeld et al. 2000 ), about 30% for dizygotic twins ( Andrews et al. 1983 ;  Felsenfeld et al. 2000 ), and 18% for siblings of the same sex ( Andrews et al. 1983 ). Given the high recovery rate, it may well be that the group abnormalities observed in adults reflects impaired recovery rather than the causes of stuttering ( Andrews et al. 1983 ).Changing Theories Over the centuries, a variety of theories about the origin of stuttering and corresponding treatment approaches have been proposed. In ancient Greece, theories referred to dryness of the tongue. In the 19 th  century, abnormalities of the speech apparatus were thought to cause stuttering. Thus, treatment was based on extensive “plastic” surgery, often leading to mutilations and additional disabilities. Other treatment options were tongue-weights or mouth prostheses ( Katz 1977 ) ( Figure 2 ). In the 20th century, stuttering was primarily thought to be a psychogenic disorder. Consequently, psychoanalytical approaches and behavioral therapy were applied to solve possible neurotic conflicts ( Plankers 1999 ). However, studies of personality traits and child–parent interactions did not detect psychological patterns consistently associated with stuttering ( Andrews et al. 1983 ). Figure 2 Two Different Apparatuses to Prevent Stuttering On the left is a device by Gardner from 1899 to artificially add weight to the tongue (United States patent number 625,879). On the right is a more complex speech apparatus by Peate from 1912 (United States patent number 1,030,964). Other theories regard stuttering as a learned behavior resulting from disadvantageous external, usually parental, reactions to normal childhood dysfluencies ( Johnson 1955 ). While this model has failed to explain the core symptoms of stuttering ( Zimmermann et al. 1983 ), it may well explain secondary symptoms ( Andrews et al. 1983 ), and guided early parental intervention may prevent persistence into adulthood ( Onslow et al. 2001 ). The severity of PDS is clearly modulated by arousal, nervousness, and other factors ( Andrews et al. 1983 ). This has led to a two-factor model of PDS. The first factor is believed to cause the disorder and is most likely a structural or functional central nervous system (CNS) abnormality, whereas the second factor reinforces the first one, especially through avoidance learning. However, one should be careful to call the latter factor “psychogenic” or “psychological,” because neuroscience has shown that learning is not simply “psychogenic” but leads to measurable changes in the brain ( Kandel and O'Dell 1992 ). In some cases, arousal actually improves stuttering instead of making it worse. Consequently, some famous stutterers have “treated” their stuttering by putting themselves on the spot. Anecdotally, the American actor Bruce Willis, who began stuttering at the age of eight, joined a drama club in high school and his stuttering vanished in front of an audience.
Changing Theories
Over the centuries, a variety of theories about the origin of stuttering and corresponding treatment approaches have been proposed. In ancient Greece, theories referred to dryness of the tongue. In the 19 th  century, abnormalities of the speech apparatus were thought to cause stuttering. Thus, treatment was based on extensive “plastic” surgery, often leading to mutilations and additional disabilities. Other treatment options were tongue-weights or mouth prostheses ( Katz 1977 ) ( Figure 2 ). In the 20th century, stuttering was primarily thought to be a psychogenic disorder. Consequently, psychoanalytical approaches and behavioral therapy were applied to solve possible neurotic conflicts ( Plankers 1999 ). However, studies of personality traits and child–parent interactions did not detect psychological patterns consistently associated with stuttering ( Andrews et al. 1983 ).Other theories regard stuttering as a learned behavior resulting from disadvantageous external, usually parental, reactions to normal childhood dysfluencies ( Johnson 1955 ). While this model has failed to explain the core symptoms of stuttering ( Zimmermann et al. 1983 ), it may well explain secondary symptoms ( Andrews et al. 1983 ), and guided early parental intervention may prevent persistence into adulthood ( Onslow et al. 2001 ). The severity of PDS is clearly modulated by arousal, nervousness, and other factors ( Andrews et al. 1983 ). This has led to a two-factor model of PDS. The first factor is believed to cause the disorder and is most likely a structural or functional central nervous system (CNS) abnormality, whereas the second factor reinforces the first one, especially through avoidance learning. However, one should be careful to call the latter factor “psychogenic” or “psychological,” because neuroscience has shown that learning is not simply “psychogenic” but leads to measurable changes in the brain ( Kandel and O'Dell 1992 ).In some cases, arousal actually improves stuttering instead of making it worse. Consequently, some famous stutterers have “treated” their stuttering by putting themselves on the spot. Anecdotally, the American actor Bruce Willis, who began stuttering at the age of eight, joined a drama club in high school and his stuttering vanished in front of an audience.Is Stuttering a Sensory, Motor, or Cognitive Disorder? Stuttering subjects as a group differ from fluent control groups by showing, on average, slightly lower intelligence scores on both verbal and nonverbal tasks and by delays in speech development ( Andrews et al. 1983 ;  Paden et al. 1999 ). However, decreased intelligence scores need to be interpreted carefully, as stutterers show a schooling disadvantage of several months ( Andrews et al. 1983 ). Associated symptoms comprise delays in tasks requiring a vocal response ( Peters et al. 1989 ) and in complex bimanual timed tasks such as inserting a string in the eye of a needle ( Vaughn and Webster 1989 ), whereas many other studies on sensory–motor reaction times yielded inconsistent results ( Andrews et al. 1983 ). Alterations of auditory feedback (e.g., delayed auditory feedback, frequency-altered feedback), various forms of other auditory stimulation (e.g., chorus reading), and alteration of speech rhythm (e.g., syllable-timed speech) yield a prompt and marked reduction of stuttering frequency, which has raised suspicions of impaired auditory processing or rhythmic pacemaking in stuttering subjects ( Lee 1951 ;  Brady and Berson 1975 ;  Hall and Jerger 1978 ;  Salmelin et al. 1998 ). Other groups have also reported discoordinated and delayed onset of complex articulation patterns in stuttering subjects ( Caruso et al. 1988 ;  van Lieshout et al. 1993 ). The assumption that stuttering might be a form of dystonia—involuntary muscle contractions produced by the CNS—specific to language production ( Kiziltan and Akalin 1996 ) was not supported by a study on motor cortex excitability ( Sommer et al. 2003 ). Neurochemistry, however, may link stuttering with disorders of a network of structures involved in the control of movement, the basal ganglia. An increase of the neurotransmitter dopamine has been associated with movement disorders such as Tourette syndrome ( Comings et al. 1996 ;  Abwender et al. 1998 ), which is a neurological disorder characterized by repeated and involuntary body movements and vocal sounds (motor and vocal tics). Accordingly, like Tourette syndrome, stuttering improves with antidopaminergic medication, e.g., neuroleptics such as haloperidol, risperidone, and olanzapine ( Brady 1991 ;  Lavid et al. 1999 ;  Maguire et al. 2000 ), and anecdotal reports suggest that it is accentuated or appears under treatment with dopaminergic medication ( Koller 1983 ;  Anderson et al. 1999 ;  Shahed and Jankovic 2001 ). Hence, a hyperactivity of the dopaminergic neurotransmitter system has been hypothesized to contribute to stuttering ( Wu et al. 1995 ). Although dopamine antagonists have a positive effect on stuttering, they all have side effects that have prevented them from being a first line treatment of stuttering.
Is Stuttering a Sensory, Motor, or Cognitive Disorder?
Stuttering subjects as a group differ from fluent control groups by showing, on average, slightly lower intelligence scores on both verbal and nonverbal tasks and by delays in speech development ( Andrews et al. 1983 ;  Paden et al. 1999 ). However, decreased intelligence scores need to be interpreted carefully, as stutterers show a schooling disadvantage of several months ( Andrews et al. 1983 ). Associated symptoms comprise delays in tasks requiring a vocal response ( Peters et al. 1989 ) and in complex bimanual timed tasks such as inserting a string in the eye of a needle ( Vaughn and Webster 1989 ), whereas many other studies on sensory–motor reaction times yielded inconsistent results ( Andrews et al. 1983 ). Alterations of auditory feedback (e.g., delayed auditory feedback, frequency-altered feedback), various forms of other auditory stimulation (e.g., chorus reading), and alteration of speech rhythm (e.g., syllable-timed speech) yield a prompt and marked reduction of stuttering frequency, which has raised suspicions of impaired auditory processing or rhythmic pacemaking in stuttering subjects ( Lee 1951 ;  Brady and Berson 1975 ;  Hall and Jerger 1978 ;  Salmelin et al. 1998 ). Other groups have also reported discoordinated and delayed onset of complex articulation patterns in stuttering subjects ( Caruso et al. 1988 ;  van Lieshout et al. 1993 ). The assumption that stuttering might be a form of dystonia—involuntary muscle contractions produced by the CNS—specific to language production ( Kiziltan and Akalin 1996 ) was not supported by a study on motor cortex excitability ( Sommer et al. 2003 ).Neurochemistry, however, may link stuttering with disorders of a network of structures involved in the control of movement, the basal ganglia. An increase of the neurotransmitter dopamine has been associated with movement disorders such as Tourette syndrome ( Comings et al. 1996 ;  Abwender et al. 1998 ), which is a neurological disorder characterized by repeated and involuntary body movements and vocal sounds (motor and vocal tics). Accordingly, like Tourette syndrome, stuttering improves with antidopaminergic medication, e.g., neuroleptics such as haloperidol, risperidone, and olanzapine ( Brady 1991 ;  Lavid et al. 1999 ;  Maguire et al. 2000 ), and anecdotal reports suggest that it is accentuated or appears under treatment with dopaminergic medication ( Koller 1983 ;  Anderson et al. 1999 ;  Shahed and Jankovic 2001 ). Hence, a hyperactivity of the dopaminergic neurotransmitter system has been hypothesized to contribute to stuttering ( Wu et al. 1995 ). Although dopamine antagonists have a positive effect on stuttering, they all have side effects that have prevented them from being a first line treatment of stuttering.Lessons from Imaging the Brain Given reports on acquired stuttering after brain trauma ( Grant et al. 1999 ;  Ciabarra et al. 2000 ), one might think that a lesion analysis (i.e., asking the question where do all lesions that lead to stuttering overlap) could help to find the location of an abnormality linked to stuttering. Unfortunately, lesions leading to stuttering are widespread and do not seem to follow an overlapping pattern. Even the contrary has been observed, a thalamic stroke after which stuttering was “cured” in a patient ( Muroi et al. 1999 ). In fluent speakers, the left language-dominant brain hemisphere is most active during speech and language tasks. However, early studies on EEG lateralization already strongly suggested abnormal hemispheric dominance ( Moore and Haynes 1980 ) in stutterers. With the advent of other noninvasive brain imaging techniques like positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), it became possible to visualize brain activity of stutterers and compare these patterns to fluent controls. Following prominent theories that linked stuttering with an imbalance of hemispherical asymmetry ( Travis 1978 ;  Moore and Haynes 1980 ), an important PET study ( Fox et al. 1996 ) reported increased activation in the right hemisphere in a language task in developmental stutterers. Another PET study ( Braun et al. 1997 ) confirmed this result, but added an important detail to the previous study: Braun and colleagues found that activity in the left hemisphere was more active during the production of stuttered speech, whereas activation of the right hemisphere was more correlated with fluent speech. Thus, the authors concluded that the primary dysfunction is located in the left hemisphere and that the hyperactivation of the right hemisphere might not be the cause of stuttering, but rather a compensatory process. A similar compensatory process has been observed after stroke and aphasia, where an intact right hemisphere can at least partially compensate for a loss of function ( Weiller et al. 1995 ). Right hemisphere hyperactivation during fluent speech has been more recently confirmed with fMRI ( Neumann et al. 2003 ). PET and fMRI have high spatial resolution, but because they only indirectly index brain activity through blood flow, their temporal resolution is rather limited. Magnetoencephalography (MEG) is the method of choice to investigate fine-grained temporal sequence of brain activity. Consequently, MEG was used to investigate stutterers and fluent controls reading single words ( Salmelin et al. 2000 ). Importantly, stutterers were reported to have read most single words fluently. Nevertheless, the data showed a clear-cut difference between stutterers and controls. Whereas fluent controls activated left frontal brain areas involved in language planning before central areas involved in speech execution, this pattern was absent, even reversed, in stutterers. This was the first study to directly show a neuronal correlate of a hypothesized speech timing disorder in stutterers ( Van Riper 1982 ). Thus, functional neuroimaging studies have revealed two important facts: (i) in stutterers, the right hemisphere seems to be hyperactive, and (ii) a timing problem seems to exist between the left frontal and the left central cortex. The latter observation also fits various observations that have shown that stutterers have slight abnormalities in complex coordination tasks, suggesting that the underlying problem is located around motor and associated premotor brain areas. Are there structural abnormalities that parallel the functional abnormalities? The first anatomical study to investigate this question used high-resolution MR scans and found abnormalities of speech–language areas (Broca's and Wernicke's area) ( Foundas et al. 2001 ). In addition, these researchers reported abnormalities in the gyrification pattern. Gyrification is a complex developmental procedure, and abnormalities in this process are an indicator of a developmental disorder. Another recent study investigated the hypothesis that impaired cortical connectivity might underlie timing disturbances between frontal and central brain regions observed in MEG studies ( Figure 3 ). Using a new MRI technique, diffusion tensor imaging (DTI), that allows the assessment of white matter ultrastructure, investigators saw an area of decreased white matter tract coherence in the Rolandic operculum ( Sommer et al. 2002 ). This structure is adjacent to the primary motor representation of tongue, larynx, and pharynx ( Martin et al. 2001 ) and the inferior arcuate fascicle linking temporal and frontal language areas, which both form a temporofrontal language system involved in word perception and production ( Price et al. 1996 ). It is thus conceivable that disturbed signal transmission through fibers passing the left Rolandic operculum impairs the fast sensorimotor integration necessary for fluent speech production. This theory also explains why the normal temporal pattern of activation between premotor and motor cortex is disturbed ( Salmelin et al. 2000 ) and why, as a consequence, the right hemisphere language areas try to compensate for this deficit ( Fox et al. 1996 ). Figure 3 Decreased Fiber Coherence Decreased fiber coherences, as observed with DTI, in persistent developmental stutterers compared with a fluent control group. A red dot indicates the peak difference in a coronal (top left), axial (top right), and a sagittal (bottom) slice. These new data also provide a theory to explain the mechanism of common fluency-inducing maneuvers like chorus reading, singing, and metronome reading that reduce stuttering instantaneously. All these procedures involve an external signal (i.e., other readers in chorus reading, the music in singing, and the metronome itself). All these external signals feed into the “speech production system” through the auditory cortex. It is thus possible that this external trigger signal reaches speech-producing central brain areas by circumventing the frontocentral disconnection and is able to resynchronize frontocentral decorrelated activity. In simple terms, these external cues can be seen as an external “pacemaker.”
Lessons from Imaging the Brain
Given reports on acquired stuttering after brain trauma ( Grant et al. 1999 ;  Ciabarra et al. 2000 ), one might think that a lesion analysis (i.e., asking the question where do all lesions that lead to stuttering overlap) could help to find the location of an abnormality linked to stuttering. Unfortunately, lesions leading to stuttering are widespread and do not seem to follow an overlapping pattern. Even the contrary has been observed, a thalamic stroke after which stuttering was “cured” in a patient ( Muroi et al. 1999 ).In fluent speakers, the left language-dominant brain hemisphere is most active during speech and language tasks. However, early studies on EEG lateralization already strongly suggested abnormal hemispheric dominance ( Moore and Haynes 1980 ) in stutterers. With the advent of other noninvasive brain imaging techniques like positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), it became possible to visualize brain activity of stutterers and compare these patterns to fluent controls. Following prominent theories that linked stuttering with an imbalance of hemispherical asymmetry ( Travis 1978 ;  Moore and Haynes 1980 ), an important PET study ( Fox et al. 1996 ) reported increased activation in the right hemisphere in a language task in developmental stutterers. Another PET study ( Braun et al. 1997 ) confirmed this result, but added an important detail to the previous study: Braun and colleagues found that activity in the left hemisphere was more active during the production of stuttered speech, whereas activation of the right hemisphere was more correlated with fluent speech. Thus, the authors concluded that the primary dysfunction is located in the left hemisphere and that the hyperactivation of the right hemisphere might not be the cause of stuttering, but rather a compensatory process. A similar compensatory process has been observed after stroke and aphasia, where an intact right hemisphere can at least partially compensate for a loss of function ( Weiller et al. 1995 ). Right hemisphere hyperactivation during fluent speech has been more recently confirmed with fMRI ( Neumann et al. 2003 ).PET and fMRI have high spatial resolution, but because they only indirectly index brain activity through blood flow, their temporal resolution is rather limited. Magnetoencephalography (MEG) is the method of choice to investigate fine-grained temporal sequence of brain activity. Consequently, MEG was used to investigate stutterers and fluent controls reading single words ( Salmelin et al. 2000 ). Importantly, stutterers were reported to have read most single words fluently. Nevertheless, the data showed a clear-cut difference between stutterers and controls. Whereas fluent controls activated left frontal brain areas involved in language planning before central areas involved in speech execution, this pattern was absent, even reversed, in stutterers. This was the first study to directly show a neuronal correlate of a hypothesized speech timing disorder in stutterers ( Van Riper 1982 ).Thus, functional neuroimaging studies have revealed two important facts: (i) in stutterers, the right hemisphere seems to be hyperactive, and (ii) a timing problem seems to exist between the left frontal and the left central cortex. The latter observation also fits various observations that have shown that stutterers have slight abnormalities in complex coordination tasks, suggesting that the underlying problem is located around motor and associated premotor brain areas.Are there structural abnormalities that parallel the functional abnormalities? The first anatomical study to investigate this question used high-resolution MR scans and found abnormalities of speech–language areas (Broca's and Wernicke's area) ( Foundas et al. 2001 ). In addition, these researchers reported abnormalities in the gyrification pattern. Gyrification is a complex developmental procedure, and abnormalities in this process are an indicator of a developmental disorder.Another recent study investigated the hypothesis that impaired cortical connectivity might underlie timing disturbances between frontal and central brain regions observed in MEG studies ( Figure 3 ). Using a new MRI technique, diffusion tensor imaging (DTI), that allows the assessment of white matter ultrastructure, investigators saw an area of decreased white matter tract coherence in the Rolandic operculum ( Sommer et al. 2002 ). This structure is adjacent to the primary motor representation of tongue, larynx, and pharynx ( Martin et al. 2001 ) and the inferior arcuate fascicle linking temporal and frontal language areas, which both form a temporofrontal language system involved in word perception and production ( Price et al. 1996 ). It is thus conceivable that disturbed signal transmission through fibers passing the left Rolandic operculum impairs the fast sensorimotor integration necessary for fluent speech production. This theory also explains why the normal temporal pattern of activation between premotor and motor cortex is disturbed ( Salmelin et al. 2000 ) and why, as a consequence, the right hemisphere language areas try to compensate for this deficit ( Fox et al. 1996 ).These new data also provide a theory to explain the mechanism of common fluency-inducing maneuvers like chorus reading, singing, and metronome reading that reduce stuttering instantaneously. All these procedures involve an external signal (i.e., other readers in chorus reading, the music in singing, and the metronome itself). All these external signals feed into the “speech production system” through the auditory cortex. It is thus possible that this external trigger signal reaches speech-producing central brain areas by circumventing the frontocentral disconnection and is able to resynchronize frontocentral decorrelated activity. In simple terms, these external cues can be seen as an external “pacemaker.”Future Directions in Research There are numerous outstanding issues in stuttering. If structural changes in the brain cause PDS, the key question is when this lesion appears. Although symptoms are somewhat different, it would be interesting to find out to what extent transient stuttering (which occurs in 3%–5% in childhood) is linked to PDS. It is possible that all children who show signs of stuttering develop a structural abnormality during development, but this is transient in those who become fluent speakers. If this is the case, it is even more important that therapy starts as early as possible if it is to have most impact. This question can now be answered with current methodology, i.e., noninvasive brain imaging using MRI. Given that boys are about four times less likely to recover from stuttering than girls, it is tempting to speculate that all stutterers have a slight abnormality, but only those that can use the right hemisphere for language can develop into fluent speakers. Language lateralization is less pronounced in women ( McGlone 1980 ) and might therefore be related to the fact that women show an overall lower incidence in PDS. Again, a developmental study comparing children who stutter with fluent controls and, most importantly, longitudinal studies on these children should be able to answer these questions. It is unlikely that stuttering is inherited in a simple fashion. Currently, a multifactorial model for genetic transmission is most likely. Moreover, it is unclear whether a certain genotype leads to stuttering or only represents a risk factor and that other environmental factors are necessary to develop PDS. Again, this question might be answered in the near future, as the National Institutes of Health has recently completed the data collection phase of a large stuttering sample for genetic linkage analysis.
Future Directions in Research
There are numerous outstanding issues in stuttering. If structural changes in the brain cause PDS, the key question is when this lesion appears. Although symptoms are somewhat different, it would be interesting to find out to what extent transient stuttering (which occurs in 3%–5% in childhood) is linked to PDS. It is possible that all children who show signs of stuttering develop a structural abnormality during development, but this is transient in those who become fluent speakers. If this is the case, it is even more important that therapy starts as early as possible if it is to have most impact. This question can now be answered with current methodology, i.e., noninvasive brain imaging using MRI.Given that boys are about four times less likely to recover from stuttering than girls, it is tempting to speculate that all stutterers have a slight abnormality, but only those that can use the right hemisphere for language can develop into fluent speakers. Language lateralization is less pronounced in women ( McGlone 1980 ) and might therefore be related to the fact that women show an overall lower incidence in PDS. Again, a developmental study comparing children who stutter with fluent controls and, most importantly, longitudinal studies on these children should be able to answer these questions.It is unlikely that stuttering is inherited in a simple fashion. Currently, a multifactorial model for genetic transmission is most likely. Moreover, it is unclear whether a certain genotype leads to stuttering or only represents a risk factor and that other environmental factors are necessary to develop PDS. Again, this question might be answered in the near future, as the National Institutes of Health has recently completed the data collection phase of a large stuttering sample for genetic linkage analysis.


Background In a retrospective study of HIV-infected patients, we investigated the influence of the MDR1 genotype (G2677T/A and C3435T) on the virological and immunological response of treatment naïve patients.
Background
In a retrospective study of HIV-infected patients, we investigated the influence of the MDR1 genotype (G2677T/A and C3435T) on the virological and immunological response of treatment naïve patients.Methods The MDR1 genotype was analysed from 72 patients in whom antiretroviral therapy was initiated between 1998 and 2004. Data were obtained at week 4, 12, 24 and 48 and were analysed by the Kruskal-Wallis test.
Methods
The MDR1 genotype was analysed from 72 patients in whom antiretroviral therapy was initiated between 1998 and 2004. Data were obtained at week 4, 12, 24 and 48 and were analysed by the Kruskal-Wallis test.Results During the first 48 weeks of antiretroviral therapy, there were no significant differences in the virological and immunological response with respect to the MDR1 2677 and 3435 genotypes and the 2677/3435 haplotype.
Results
During the first 48 weeks of antiretroviral therapy, there were no significant differences in the virological and immunological response with respect to the MDR1 2677 and 3435 genotypes and the 2677/3435 haplotype.Conclusions In view of different results from several studies concerning the influence of MDR1 polymorphisms on the immunological and virological response to antiretroviral therapy, further studies with larger patient groups and longer follow-up are necessary in order to resolve conflicting issues.
Conclusions
In view of different results from several studies concerning the influence of MDR1 polymorphisms on the immunological and virological response to antiretroviral therapy, further studies with larger patient groups and longer follow-up are necessary in order to resolve conflicting issues.

Background The P-glycoprotein (P-gp) is an ATP-dependent efflux transporter (ABCB1) encoded by the multidrug resistance gene (MDR1) which extrudes large lipophilic, positvely charged molecules from cells, among them HIV-1 protease inhibitors [ 1 , 2 ]. P-gp is expressed on a variety of cells including human lymphocytes, the target cells of HIV and of antiretroviral substances [ 3 ]. 48 single nucleotide polymorphisms (SNP) have been described so far for the MDR1 gene [ 4 ]. Though there is still controversy about the biological relevance of these SNPs, there appears to be an association between specific genotypes and mRNA expression, P-gp expression and/or P-gp function (reviewed in [ 5 , 6 ]). Recently, Fellay  et al . found lower nelfinavir and efavirenz plasma levels associated with the TT genotype of the SNP C3435T in exon 26 and a greater rise of the CD4 cell count 6 months after initiation of antiretroviral therapy in patients with this genotype [ 7 ]. However, the mechanisms underlying this observation remain unclear. In contrast to protease inhibitors (PI), non-nucleoside reverse transcriptase inhibitors (NNRTI) such as efavirenz are not substrates of the P-gp. Therefore, it has been speculated that the P-gp may modulate the clinical course of HIV infection independent from its role in drug transport. Indeed, there have been reports showing inhibition of apoptosis and decreased HIV production in cells overexpressing P-gp [ 8 - 12 ]. However, these observations from in vitro studies have not been confirmed in vivo when the disease progression before treatment was assessed in HIV infected individuals with different MDR1 genotypes [ 13 ]. The genetic variant C3435T in exon 26 is a synonymous polymorphism that does not alter the amino acid sequence. How this variant could affect P-gp expression is still unknown [ 6 ]. According to one hypothesis, functional effects of the C3435T SNP may not be genotype- but haplotype-dependent. The exon 26 C3435T polymorphism is in linkage disequlibrium with the polymorphism G2677T in exon 21, which results in the amino acid change Ala893Ser [ 6 ]. 2677A leading to Ala893Thr is an infrequent third allel of this SNP. The results of several studies on the functional effects of mutations at position 2677 in exon 21 have shown conflicting results [ 6 ]. Because of the unresolved issues surrounding the potential effects of MDR1 polymorphisms and P-gp function in HIV infection, we investigated whether there was an association between the MDR1 polymorphisms 3435 and 2677 and the immunological response in HIV infected individuals after initiation of antiretroviral therapy.
Background
The P-glycoprotein (P-gp) is an ATP-dependent efflux transporter (ABCB1) encoded by the multidrug resistance gene (MDR1) which extrudes large lipophilic, positvely charged molecules from cells, among them HIV-1 protease inhibitors [ 1 , 2 ]. P-gp is expressed on a variety of cells including human lymphocytes, the target cells of HIV and of antiretroviral substances [ 3 ]. 48 single nucleotide polymorphisms (SNP) have been described so far for the MDR1 gene [ 4 ]. Though there is still controversy about the biological relevance of these SNPs, there appears to be an association between specific genotypes and mRNA expression, P-gp expression and/or P-gp function (reviewed in [ 5 , 6 ]). Recently, Fellay  et al . found lower nelfinavir and efavirenz plasma levels associated with the TT genotype of the SNP C3435T in exon 26 and a greater rise of the CD4 cell count 6 months after initiation of antiretroviral therapy in patients with this genotype [ 7 ]. However, the mechanisms underlying this observation remain unclear. In contrast to protease inhibitors (PI), non-nucleoside reverse transcriptase inhibitors (NNRTI) such as efavirenz are not substrates of the P-gp. Therefore, it has been speculated that the P-gp may modulate the clinical course of HIV infection independent from its role in drug transport. Indeed, there have been reports showing inhibition of apoptosis and decreased HIV production in cells overexpressing P-gp [ 8 - 12 ]. However, these observations from in vitro studies have not been confirmed in vivo when the disease progression before treatment was assessed in HIV infected individuals with different MDR1 genotypes [ 13 ].et alThe genetic variant C3435T in exon 26 is a synonymous polymorphism that does not alter the amino acid sequence. How this variant could affect P-gp expression is still unknown [ 6 ]. According to one hypothesis, functional effects of the C3435T SNP may not be genotype- but haplotype-dependent. The exon 26 C3435T polymorphism is in linkage disequlibrium with the polymorphism G2677T in exon 21, which results in the amino acid change Ala893Ser [ 6 ]. 2677A leading to Ala893Thr is an infrequent third allel of this SNP. The results of several studies on the functional effects of mutations at position 2677 in exon 21 have shown conflicting results [ 6 ].Because of the unresolved issues surrounding the potential effects of MDR1 polymorphisms and P-gp function in HIV infection, we investigated whether there was an association between the MDR1 polymorphisms 3435 and 2677 and the immunological response in HIV infected individuals after initiation of antiretroviral therapy.Methods Patients Of the HIV 1 infected patients seen at the Department of Infectious Diseases of the University of Würzburg, Germany, 72 patients (18 women, 54 men; mean age 39.5 years, range: 26 – 59 years; 64 Caucasians, 5 African, 3 Asian), started antiretroviral therapy between 1998 and 2004. The therapy consisted of three nucleoside reverse transcriptase inhibitors (NRTI) (n = 12), two NRTIs plus at least one PI (n = 40; including RTV n = 26) or two NRTIs plus one NNRTI (n = 20). HIV load and CD4 cell count were determined four weeks after initiation of therapy and approximately every three months thereafter. In patients who received NNRTI or PI drugs as part of their therapy, plasma levels were monitored and adjusted to therapeutic drug levels when necessary as previously described [ 14 , 15 ]. The treatment was based on current international treatment guidelines [ 16 ], taking into account individual circumstances of each patient (e.g. known intolerabilities, side-effects of previous therapies, concomitant medication). The study was in accordance with the Helsinki Declaration and was approved by the local ethics committee. Patients gave informed consent for the study. Genotype analysis DNA was extracted from 200 μl blood and the MDR1 3435 genotype was determined with genotype specific hybridisation probes and melting curve analysis on the LightCycler (Roche, Mannheim, Germany) as previously described [ 17 ]. The 2677 genotype was determined in a similar fashion [ 18 ]. Briefly, DNA was amplified on the LightCycler with the Quantitect Probe PCR Kit (Qiagen, Hilden, Germany) by using the primers 5'-gcaggagttgttgaaatgaaaatg-3' (forward) and 5'-cgcctgctttagtttgactca-3' (reverse). Hybridization probes were added to the master mix to a final concentration of 0.05 μM (sensor probe: 5'-ttcccagTaccttct-fluorescein; locked nucleic acid base in upper case letter) and 0.15 μM (anchor probe: 5'-LC Red640-ctttcttatctttcagtgcttgtcc-p). Primers and probes were obtained from TIB Molbiol (Berlin, Germany). The melting points were 41°C, 47°C, and 52°C for the T-, G-, and A-alleles, respectively. The results of 30 samples were confirmed by sequencing. Statistical analysis Data were analysed by the Kruskal-Wallis test, which as a nonparametric test compairs three or more unpaired groups. Because of the small number of samples a nonparametric test was needed. SPSS version 12.0 (SPSS GmbH, Munich, Germany) was used for statistical analysis. A  P -value of 0.05 was considered to be significant. Analogous to [ 13 ], the SNPs 3435 and 2677 were analyzed both separately and in combination as composite genotypes: H1: 2677GG and 3435CC (wild type); H2: 2677GT or TT and 3435CT or TT (2677T/3435T haplotype carrier); H3: 2677GG and 3435CT or TT; H4: 2677GT or TT and 3435CC; and H5: 2677AG or AT and any 3435 genotype (2677A carrier).
Methods
Patients Of the HIV 1 infected patients seen at the Department of Infectious Diseases of the University of Würzburg, Germany, 72 patients (18 women, 54 men; mean age 39.5 years, range: 26 – 59 years; 64 Caucasians, 5 African, 3 Asian), started antiretroviral therapy between 1998 and 2004. The therapy consisted of three nucleoside reverse transcriptase inhibitors (NRTI) (n = 12), two NRTIs plus at least one PI (n = 40; including RTV n = 26) or two NRTIs plus one NNRTI (n = 20). HIV load and CD4 cell count were determined four weeks after initiation of therapy and approximately every three months thereafter. In patients who received NNRTI or PI drugs as part of their therapy, plasma levels were monitored and adjusted to therapeutic drug levels when necessary as previously described [ 14 , 15 ]. The treatment was based on current international treatment guidelines [ 16 ], taking into account individual circumstances of each patient (e.g. known intolerabilities, side-effects of previous therapies, concomitant medication). The study was in accordance with the Helsinki Declaration and was approved by the local ethics committee. Patients gave informed consent for the study.
Patients
Of the HIV 1 infected patients seen at the Department of Infectious Diseases of the University of Würzburg, Germany, 72 patients (18 women, 54 men; mean age 39.5 years, range: 26 – 59 years; 64 Caucasians, 5 African, 3 Asian), started antiretroviral therapy between 1998 and 2004. The therapy consisted of three nucleoside reverse transcriptase inhibitors (NRTI) (n = 12), two NRTIs plus at least one PI (n = 40; including RTV n = 26) or two NRTIs plus one NNRTI (n = 20). HIV load and CD4 cell count were determined four weeks after initiation of therapy and approximately every three months thereafter. In patients who received NNRTI or PI drugs as part of their therapy, plasma levels were monitored and adjusted to therapeutic drug levels when necessary as previously described [ 14 , 15 ]. The treatment was based on current international treatment guidelines [ 16 ], taking into account individual circumstances of each patient (e.g. known intolerabilities, side-effects of previous therapies, concomitant medication).The study was in accordance with the Helsinki Declaration and was approved by the local ethics committee. Patients gave informed consent for the study.Genotype analysis DNA was extracted from 200 μl blood and the MDR1 3435 genotype was determined with genotype specific hybridisation probes and melting curve analysis on the LightCycler (Roche, Mannheim, Germany) as previously described [ 17 ]. The 2677 genotype was determined in a similar fashion [ 18 ]. Briefly, DNA was amplified on the LightCycler with the Quantitect Probe PCR Kit (Qiagen, Hilden, Germany) by using the primers 5'-gcaggagttgttgaaatgaaaatg-3' (forward) and 5'-cgcctgctttagtttgactca-3' (reverse). Hybridization probes were added to the master mix to a final concentration of 0.05 μM (sensor probe: 5'-ttcccagTaccttct-fluorescein; locked nucleic acid base in upper case letter) and 0.15 μM (anchor probe: 5'-LC Red640-ctttcttatctttcagtgcttgtcc-p). Primers and probes were obtained from TIB Molbiol (Berlin, Germany). The melting points were 41°C, 47°C, and 52°C for the T-, G-, and A-alleles, respectively. The results of 30 samples were confirmed by sequencing.
Genotype analysis
DNA was extracted from 200 μl blood and the MDR1 3435 genotype was determined with genotype specific hybridisation probes and melting curve analysis on the LightCycler (Roche, Mannheim, Germany) as previously described [ 17 ]. The 2677 genotype was determined in a similar fashion [ 18 ]. Briefly, DNA was amplified on the LightCycler with the Quantitect Probe PCR Kit (Qiagen, Hilden, Germany) by using the primers 5'-gcaggagttgttgaaatgaaaatg-3' (forward) and 5'-cgcctgctttagtttgactca-3' (reverse). Hybridization probes were added to the master mix to a final concentration of 0.05 μM (sensor probe: 5'-ttcccagTaccttct-fluorescein; locked nucleic acid base in upper case letter) and 0.15 μM (anchor probe: 5'-LC Red640-ctttcttatctttcagtgcttgtcc-p). Primers and probes were obtained from TIB Molbiol (Berlin, Germany). The melting points were 41°C, 47°C, and 52°C for the T-, G-, and A-alleles, respectively. The results of 30 samples were confirmed by sequencing.Statistical analysis Data were analysed by the Kruskal-Wallis test, which as a nonparametric test compairs three or more unpaired groups. Because of the small number of samples a nonparametric test was needed. SPSS version 12.0 (SPSS GmbH, Munich, Germany) was used for statistical analysis. A  P -value of 0.05 was considered to be significant. Analogous to [ 13 ], the SNPs 3435 and 2677 were analyzed both separately and in combination as composite genotypes: H1: 2677GG and 3435CC (wild type); H2: 2677GT or TT and 3435CT or TT (2677T/3435T haplotype carrier); H3: 2677GG and 3435CT or TT; H4: 2677GT or TT and 3435CC; and H5: 2677AG or AT and any 3435 genotype (2677A carrier).
Statistical analysis
Data were analysed by the Kruskal-Wallis test, which as a nonparametric test compairs three or more unpaired groups. Because of the small number of samples a nonparametric test was needed. SPSS version 12.0 (SPSS GmbH, Munich, Germany) was used for statistical analysis. A  P -value of 0.05 was considered to be significant. Analogous to [ 13 ], the SNPs 3435 and 2677 were analyzed both separately and in combination as composite genotypes: H1: 2677GG and 3435CC (wild type); H2: 2677GT or TT and 3435CT or TT (2677T/3435T haplotype carrier); H3: 2677GG and 3435CT or TT; H4: 2677GT or TT and 3435CC; and H5: 2677AG or AT and any 3435 genotype (2677A carrier).PResults At initiation of antiretroviral therapy 8 patients had viral loads of <10.000 copies/ml, 24 patients between >10.000 and <100.000 copies/ml, and 40 patients >100.000 copies/ml. 39 patients had a CD4 cell count of <200 cells/μl, 16 patients between >200 and <350 cells/μl, and 17 patients >350 cells/μl. Determination of NNRTI- and PI drug levels indicated compliance of the patients with a NNRTI or PI containing regimen, because the measured drug levels were in the therapeutic range. Genotype analysis of the MDR1 gene at position 3435 in exon 26 revealed 20 patients with the CC genotype, 33 with the CT genotype and 19 with the TT genotype (5 patients of African origin: 4 with CC and 1 with CT genotype; 3 patients o f Asisan origen: 2 with CT and 1 with TT genotye). Analysis of the 2677 polymorphism in exon 21 demonstrated that 24 patients had the GG-, 23 the GT-, 18 the TT-, 4 the AG-, and 3 the AT genotype; the AA genotype was not found in this group (5 patients of African origin: 4 with GG and 1 with GT genotype; 3 patients of Asian origin: 3 with TT genotype). Detailed genotype and haplotype results with respect to the initial viral load and CD4 cell count are presented in table  1 . Table 1 Genotype analysis of 72 treatment naive HIV-positive patients with respect to baseline CD4 cell count and viral load. CD4 [cells/μl] VL [copies/μl] n = 2677 3435 2677/3435 $ GG GT TT AG AT AA CC CT TT H1 H2 H3 H4 H5 <200 >10 5 27 7 7 8 3 2 - 7 10 10 5 15 2 - 5 10 4  – 10 5 8 4 3 1 - - - 2 6 - 2 4 2 - - <10 4 4 2 1 1 - - - 1 2 1 1 2 1 - - 200 >10 5 6 2 3 1 - - - 1 4 1 1 4 1 - - -350 10 4  – 10 5 9 3 3 3 - - - 3 3 3 3 6 - - - <10 4 1 1 - - - - - 1 - - 1 - - - - >350 >10 5 7 1 4 2 - - - 1 3 3 1 6 - - - 10 4  – 10 5 7 1 2 2 1 1 - 2 4 1 1 4 - - 2 <10 4 3 3 - - - - - 2 1 - 2 - 1 - - total 72 24 23 18 4 3 0 20 33 19 17 41 7 - 7 $ composite genotypes: H1: 2677GG and 3435CC (wild type); H2: 2677GT or TT and 3435CT or TT (2677T/3435T haplotype carrier); H3: 2677GG and 3435CT or TT; H4: 2677GT or TT and 3435CC; and H5: 2677AG or AT and any 3435 genotype (2677A carrier) Table  2  and  3  show the median and mean values of the viral load decline and the CD4-cell increase, respectively, determined at week 4, 12, 24 and 48 after initiation of therapy. There were no significant differences of the viral load decline neither between patient groups with different genotypes at positions 2677 or 3435 nor between patient groups with different 2677/3435 haplotypes. As to the CD4-cell response, there were no significant differences between the different genotypes and haplotypes, either. There was a trend of a more pronounced mean CD4-cell increase at week 12 and 24 in patients with the 3435TT genotype. However, this trend did not persist at week 48 and was not confirmed by the corresponding median values. A graphical presentation of the mean viral load decrease and CD4-cell increase with respect to the 2677/3435 haplotypes is given in fig.  1 . Analysis of patients with different therapy-regimens (only NRTI, NRTI + NNRTI, or NRTI + PI) revealed no differences in the virological and immunological response between the different genotypes either, but was limited by small patient numbers in the subgroups (data not shown). Table 2 VL-decrease [log copies/ml] at week 4, 12, 24 and 48 after initiation of antiretroviral therapy with respect to the MDR1 2677 and 3435 genotypes. Statistical analysis was done with the Kruskall-Wallis test. week 4 week 12 week 24 week 48 MDR1 n = median [log/ml] mean [log/ml] SA p  = n = median [log/ml] mean [log/ml] SA p  = n = median [log/ml] mean [log/ml] SA p  = n = median [log/ml] mean [log/ml] SA p  = 2677 GG 22 -2,301 -2,210 0,590 >0.3 22 -3,048 -3,287 0,682 >0.05 20 -3,943 -3,876 0,748 >0.9 15 -3,716 -3,835 0,777 >0.5 GT 21 -2,602 -2,537 0,566 19 -3,786 -3,794 0,635 17 -3,929 -3,933 0,499 16 -3,942 -3,946 0,488 TT 17 -2,495 -2,372 0,651 16 -3,739 -3,602 0,595 17 -4,000 -3,850 0,708 14 -3,977 -3,795 0,615 AG 3 -2,301 -2,689 0,606 § 4 -3,952 -4,167 0,884 § 4 -4,500 -4,537 0,702 § 4 -4,151 -4,362 0,726 § AT 3 -1,875 -2,032 0,493 § 3 -4,176 -3,752 0,690 § 3 -4,176 -4,085 0,223 § 3 -4,176 -4,085 0,223 § 3435 CC 17 -2,301 -2,382 0,501 >0.6 19 -3,301 -3,416 0,699 >0.4 17 -4,000 -3,974 0,685 >0.7 13 -3,716 -3,818 0,709 >0.6 CT 32 -2,247 -2,363 0,640 29 -3,778 -3,742 0,737 28 -3,812 -3,830 0,704 25 -3,929 -3,984 0,614 TT 17 -2,398 -2,348 0,668 17 -3,602 -3,530 0,595 17 -4,176 -4,054 0,571 15 -4,114 -3,849 0,609 2677/3435 † H1 15 -2,398 -2,398 0,531 >0.8 16 -3,199 -3,361 0,724 >0.08 14 -3,943 -3,926 0,715 >0.8 10 -3,659 -3,774 0,787 >0.4 H2 38 -2,548 -2,463 0,611 35 -3,778 -3,706 0,624 34 -3,954 -3,891 0,614 30 -3,954 -3,875 0,556 H3 7 -1,778 -1,806 0,502 § 6 -2,827 -3,089 0,506 § 6 -3,827 -3,761 0,807 § 5 -4,176 -3,958 0,741 § H5 6 -2,261 -2,361 0,642 § 7 -4,176 -3,989 0,833 § 7 -4,301 -4,343 0,594 § 7 -4,176 -4,243 0,584 § total 66 64 61 52 † composite genotypes: see methods;  § excluded from statistical analysis Table 3 CD4-cell increase [cells/μl] at week 4, 12, 24 and 48 after initiation of antiretroviral therapy with respect to the MDR1 2677 and 3435 genotypes. Statistical analysis was done with the Kruskall-Wallis test. week 4 week 12 week 24 week 48 MDR1 n = median [cells/μl] mean [cells/μl] SA p  = n = median [cells/μl] mean [cells/μl] SA p  = n = median [cells/μl] mean [cells/μl] SA p  = n = median [cells/μl] mean [cells/μl] SA p  = 2677 GG 24 56,5 69,8 81,5 >0.3 22 97,0 130,6 132,4 >0.5 21 107,0 136,1 120,5 >0.8 15 244,0 235,7 132,1 >0.1 GT 23 24,0 37,8 82,5 20 84,5 144,3 157,2 17 132,0 180,8 178,0 16 161,5 238,3 218,6 TT 18 9,5 67,4 117,7 16 70,0 143,9 222,3 16 95,0 154,5 162,0 14 107,5 143,9 159,1 AG 4 70,5 85,8 68,5 § 4 82,5 74,8 34,4 § 4 54,5 80,3 81,3 § 4 131,5 126,5 71,0 § AT 3 112,0 105,7 13,4 § 3 176,0 180,7 63,8 § 2 154,5 154,5 54,5 § 3 172,0 248,0 118,2 § 3435 CC 20 76,0 84,8 78,6 >0.1 19 91,0 123,0 113,0 >0.9 18 106,5 132,4 112,4 >0.5 13 191,0 220,1 121,5 >0.6 CT 34 25,5 47,2 76,1 30 85,0 123,7 135,3 28 131,0 134,2 106,8 25 159,0 187,7 118,4 TT 18 12,0 61,6 119,1 17 74,0 175,9 228,1 16 134,0 212,2 214,7 15 122,0 223,9 259,3 2677/3435 † H1 17 72,0 83,1 78,7 >0.1 16 115,0 132,1 119,8 >0.8 15 107,0 142,2 113,3 >0.9 10 194,0 239,6 128,4 >0.5 H2 41 20,0 50,8 100,6 36 74,5 144,1 188,9 33 130,0 168,1 170,9 30 134,5 194,2 198,8 H3 7 19,0 37,3 79,1 § 6 92,0 126,7 161,2 § 6 122,0 120,8 135,7 § 5 302,0 227,8 138,9 § H5 7 87,0 94,3 53,5 § 7 105,0 120,1 71,9 § 7 100,0 131,0 98,7 § 7 172,0 178,6 111,7 § total 72 65 61 52 † composite genotypes: see methods;  § excluded from statistical analysis Figure 1 Composite genotypes (see methods) and response to antiretroviral treatment. Suppression of viraemia (lower panel) and CD4-cell count increase (upper panel) are shown. Data are mean values ± standard error.
Results
At initiation of antiretroviral therapy 8 patients had viral loads of <10.000 copies/ml, 24 patients between >10.000 and <100.000 copies/ml, and 40 patients >100.000 copies/ml. 39 patients had a CD4 cell count of <200 cells/μl, 16 patients between >200 and <350 cells/μl, and 17 patients >350 cells/μl. Determination of NNRTI- and PI drug levels indicated compliance of the patients with a NNRTI or PI containing regimen, because the measured drug levels were in the therapeutic range. Genotype analysis of the MDR1 gene at position 3435 in exon 26 revealed 20 patients with the CC genotype, 33 with the CT genotype and 19 with the TT genotype (5 patients of African origin: 4 with CC and 1 with CT genotype; 3 patients o f Asisan origen: 2 with CT and 1 with TT genotye). Analysis of the 2677 polymorphism in exon 21 demonstrated that 24 patients had the GG-, 23 the GT-, 18 the TT-, 4 the AG-, and 3 the AT genotype; the AA genotype was not found in this group (5 patients of African origin: 4 with GG and 1 with GT genotype; 3 patients of Asian origin: 3 with TT genotype). Detailed genotype and haplotype results with respect to the initial viral load and CD4 cell count are presented in table  1 .Genotype analysis of 72 treatment naive HIV-positive patients with respect to baseline CD4 cell count and viral load.total72242318430203319174177$ composite genotypes: H1: 2677GG and 3435CC (wild type); H2: 2677GT or TT and 3435CT or TT (2677T/3435T haplotype carrier); H3: 2677GG and 3435CT or TT; H4: 2677GT or TT and 3435CC; and H5: 2677AG or AT and any 3435 genotype (2677A carrier)Table  2  and  3  show the median and mean values of the viral load decline and the CD4-cell increase, respectively, determined at week 4, 12, 24 and 48 after initiation of therapy. There were no significant differences of the viral load decline neither between patient groups with different genotypes at positions 2677 or 3435 nor between patient groups with different 2677/3435 haplotypes. As to the CD4-cell response, there were no significant differences between the different genotypes and haplotypes, either. There was a trend of a more pronounced mean CD4-cell increase at week 12 and 24 in patients with the 3435TT genotype. However, this trend did not persist at week 48 and was not confirmed by the corresponding median values. A graphical presentation of the mean viral load decrease and CD4-cell increase with respect to the 2677/3435 haplotypes is given in fig.  1 . Analysis of patients with different therapy-regimens (only NRTI, NRTI + NNRTI, or NRTI + PI) revealed no differences in the virological and immunological response between the different genotypes either, but was limited by small patient numbers in the subgroups (data not shown).VL-decrease [log copies/ml] at week 4, 12, 24 and 48 after initiation of antiretroviral therapy with respect to the MDR1 2677 and 3435 genotypes. Statistical analysis was done with the Kruskall-Wallis test.pppp>0.3>0.05>0.9>0.5>0.6>0.4>0.7>0.6>0.8>0.08>0.8>0.4† composite genotypes: see methods;  § excluded from statistical analysisCD4-cell increase [cells/μl] at week 4, 12, 24 and 48 after initiation of antiretroviral therapy with respect to the MDR1 2677 and 3435 genotypes. Statistical analysis was done with the Kruskall-Wallis test.pppp>0.3>0.5>0.8>0.1>0.1>0.8>0.9>0.5total† composite genotypes: see methods;  § excluded from statistical analysisDiscussion In an analysis of the virological and immunological response of treatment naïve patients with respect to the MDR1 G2677T/A and C3435T polymorphisms, virus load and CD4 cell count were assessed longitunally after initiation of antiretroviral therapy. We did not find an association between the CD4-cell increase or the HIV load decline and the MDR1 2677 or 3435 genotype during the first year of therapy. Our data are in contrast to a report of Fellay  et al . that showed a significantly greater mean CD4-cell rise in patients with the MDR1 3435TT genotype during an observation period of 24 weeks [ 7 ]. The number of patients in the previous report (n = 96) was slightly larger than our population (n = 72), but the number of homozygotes of the 3435 polymorphism was very similar (22CC/20TT in [ 7 ], 20CC/19TT this study). Though we saw a trend towards a greater mean CD4-cell rise in patients with the 3435TT genotype as well, we doubt that this is indication of a real difference, because this trend was not seen when median values were considered. In our study, neither median values nor mean values were significantly different by Kruskal-Wallis test and ANOVA, respectively. For genotype subgroup sizes as in this study, analysis of the mean values is probably less robust. If there was a real difference between the immunological response of patients with the 3435CC and TT genotype, it did not persist at week 48. At this time point, mean and median values in the two groups were almost identical. A possible explanation for the diverse results is the selection of the study patients. While we included all treatment naïve patients in whom therapy was started between 1998 and 2004, Fellay  et al . selected part of the patients on the basis of long-term viral suppression. In both studies, a variety of antiretroviral regimens was used. While all of the patients in the study of Fellay  et al . received either nelfinavir or efavirenz, the treatment regimens in our study were more heterogenous and did not allow a meaningful separate analysis. The results of our study are supported by Nasi  et al . [ 19 ] who analysed data of 149 treatment naïve patients who were treated with a PI-containing regimen (n = 106) or a NNRTI-containing regimen (n = 46) and found no association between the MDR1 genotype at position 3435 and the CD4 cell increases or plasma viral load decreases during the first six months of treatment among individuals with different genotypes. Likewise, in 142 patients enrolled in an open-label, randomized phase IIIb study comparing nelfinavir and efavirenz for treatment of HAART-naïve individuals the CD4 cell counts did not increase to a higher level in individuals with the homozygous variant genotype (TT) at the MDR1 C3435T locus in either the nelfinavir or the efavirenz treatment groups [ 20 ]. The MDR1 3435 polymorphism is a synonymous polymorphism. The TT genotype may have a reduced translation efficiency or lead to post-translational differences [ 21 - 23 ]. It has been shown, that a linkage disequilibirum exists between the exon 26 C3435T and the exon 21 G2677T/A polymorphism [ 6 ]. Therefore, we investigated both SNPs in our study. Neither the 2677 polymorphism alone nor the 2677/3435 haplotype was associated with differences in the virological or immunological response of treatment naïve patients. These data are in agreement with those of Haas  et al . [ 24 ], who showed that the phase 1 and phase 2 viral decay as well as changes in CD4- and CD8-T-cells during triple therapy with ritonavir, zidovudine, and lamivudine in 31 treatment naïve patients were not associated with the MDR1 2677 and 3435 genotypes. In a retrospective study of 455 treatment naïve patients initiating antiretroviral therapy with 40 months of follow-up [ 25 ], there was a trend to earlier virological failure in the 3435CC group ( p  = 0.07) with no effect of the C3435T polymorphism in the MDR-1 gene on immunological failure. However, the difference in the virological response was not observed during the first 10 months. Further follow-up of our patient group is ongoing in order to detect long-term effects that may not have been apparent during the observation period analysed in this report.
Discussion
In an analysis of the virological and immunological response of treatment naïve patients with respect to the MDR1 G2677T/A and C3435T polymorphisms, virus load and CD4 cell count were assessed longitunally after initiation of antiretroviral therapy. We did not find an association between the CD4-cell increase or the HIV load decline and the MDR1 2677 or 3435 genotype during the first year of therapy.Our data are in contrast to a report of Fellay  et al . that showed a significantly greater mean CD4-cell rise in patients with the MDR1 3435TT genotype during an observation period of 24 weeks [ 7 ]. The number of patients in the previous report (n = 96) was slightly larger than our population (n = 72), but the number of homozygotes of the 3435 polymorphism was very similar (22CC/20TT in [ 7 ], 20CC/19TT this study). Though we saw a trend towards a greater mean CD4-cell rise in patients with the 3435TT genotype as well, we doubt that this is indication of a real difference, because this trend was not seen when median values were considered. In our study, neither median values nor mean values were significantly different by Kruskal-Wallis test and ANOVA, respectively. For genotype subgroup sizes as in this study, analysis of the mean values is probably less robust. If there was a real difference between the immunological response of patients with the 3435CC and TT genotype, it did not persist at week 48. At this time point, mean and median values in the two groups were almost identical. A possible explanation for the diverse results is the selection of the study patients. While we included all treatment naïve patients in whom therapy was started between 1998 and 2004, Fellay  et al . selected part of the patients on the basis of long-term viral suppression. In both studies, a variety of antiretroviral regimens was used. While all of the patients in the study of Fellay  et al . received either nelfinavir or efavirenz, the treatment regimens in our study were more heterogenous and did not allow a meaningful separate analysis.et alet alet alThe results of our study are supported by Nasi  et al . [ 19 ] who analysed data of 149 treatment naïve patients who were treated with a PI-containing regimen (n = 106) or a NNRTI-containing regimen (n = 46) and found no association between the MDR1 genotype at position 3435 and the CD4 cell increases or plasma viral load decreases during the first six months of treatment among individuals with different genotypes. Likewise, in 142 patients enrolled in an open-label, randomized phase IIIb study comparing nelfinavir and efavirenz for treatment of HAART-naïve individuals the CD4 cell counts did not increase to a higher level in individuals with the homozygous variant genotype (TT) at the MDR1 C3435T locus in either the nelfinavir or the efavirenz treatment groups [ 20 ].et alThe MDR1 3435 polymorphism is a synonymous polymorphism. The TT genotype may have a reduced translation efficiency or lead to post-translational differences [ 21 - 23 ]. It has been shown, that a linkage disequilibirum exists between the exon 26 C3435T and the exon 21 G2677T/A polymorphism [ 6 ]. Therefore, we investigated both SNPs in our study. Neither the 2677 polymorphism alone nor the 2677/3435 haplotype was associated with differences in the virological or immunological response of treatment naïve patients. These data are in agreement with those of Haas  et al . [ 24 ], who showed that the phase 1 and phase 2 viral decay as well as changes in CD4- and CD8-T-cells during triple therapy with ritonavir, zidovudine, and lamivudine in 31 treatment naïve patients were not associated with the MDR1 2677 and 3435 genotypes.et alIn a retrospective study of 455 treatment naïve patients initiating antiretroviral therapy with 40 months of follow-up [ 25 ], there was a trend to earlier virological failure in the 3435CC group ( p  = 0.07) with no effect of the C3435T polymorphism in the MDR-1 gene on immunological failure. However, the difference in the virological response was not observed during the first 10 months. Further follow-up of our patient group is ongoing in order to detect long-term effects that may not have been apparent during the observation period analysed in this report.pConclusions During a follow-up of 48 weeks, we found no evidence for an association between the MDR1 G2677T/A and C3435T polymorphisms and the virological and immunological response to therapy in HIV-positive drug-naïve patients. The individual response to antiretroviral therapy is a complex phenomenon, which is influenced by a large number of biological variables. Further studies on the role of polymorphisms of the MDR1 and other transporters and enzymes involved in drug metabolism are necessary in order to elucidate the role of pharmacogenetic effects in HIV therapy.
Conclusions
During a follow-up of 48 weeks, we found no evidence for an association between the MDR1 G2677T/A and C3435T polymorphisms and the virological and immunological response to therapy in HIV-positive drug-naïve patients. The individual response to antiretroviral therapy is a complex phenomenon, which is influenced by a large number of biological variables. Further studies on the role of polymorphisms of the MDR1 and other transporters and enzymes involved in drug metabolism are necessary in order to elucidate the role of pharmacogenetic effects in HIV therapy.Competing interests None declared.
Competing interests
None declared.Authors' contributions RW participated in the design of the study and the molecular genetic studies, performed the statistical analysis and drafted the manuscript. PL participated in the design of the study, obtained and reviewed clinical data and helped in the data analysis. MZ participated in the clinical management of the study patients. FT and JS participated in the molecular genetic studies and the virological and immunological analysis. HK participated in the study design and coordinated clinical management of the study patients. BW participated in the study design and coordination and made contributions to the manuscript. All authors read and approved the final manuscript.
Authors' contributions
RW participated in the design of the study and the molecular genetic studies, performed the statistical analysis and drafted the manuscript. PL participated in the design of the study, obtained and reviewed clinical data and helped in the data analysis. MZ participated in the clinical management of the study patients. FT and JS participated in the molecular genetic studies and the virological and immunological analysis. HK participated in the study design and coordinated clinical management of the study patients. BW participated in the study design and coordination and made contributions to the manuscript. All authors read and approved the final manuscript.